In this commentary, Yacine Boubia examines why political disinformation has become one of the defining challenges of contemporary democratic life. Moving beyond conventional explanations that focus on misinformation as a mere failure of fact or technology, Boubia argues that disinformation increasingly functions as a mechanism of political identity formation. Within contemporary populist politics, false narratives often derive their power not from their factual accuracy but from their ability to reinforce collective belonging, distrust of institutions, and emotional engagement. Drawing on examples from the United States, Brazil, Hungary, India, and other democratic contexts, the commentary explores how digital media ecosystems, affective polarization, and populist communication have transformed the relationship between truth, politics, and democratic legitimacy. The result, Boubia warns, is the fragmentation of shared public reality and the erosion of the deliberative foundations upon which democratic societies depend.
Political disinformation has become one of the defining anxieties of contemporary democratic life. Governments increasingly legislate against it, social media companies develop moderation policies intended to contain it, and fact-checking organizations work continuously to identify and correct false claims circulating online. Yet despite the multiplication of these mechanisms, disinformation not only persists but often appears politically resilient. In some cases, attempts to debunk falsehoods seem to reinforce the political narratives they were intended to weaken.
The persistence of disinformation suggests that the phenomenon cannot be understood simply as a technological malfunction or as the result of insufficient access to accurate information. Nor can it be reduced to the assumption that democratic publics have suddenly become incapable of distinguishing truth from falsehood. Such explanations remain insufficient because they misunderstand the political function disinformation increasingly performs within contemporary populist politics.
The central issue is not merely that false information circulates. Falsehood has always existed within political life. Rumors, conspiracies, propaganda, and manipulated narratives long predate the digital era. What distinguishes the contemporary moment is the transformation of the relationship between political identity, media consumption, and the perception of reality itself. Increasingly, political information is consumed less as neutral knowledge than as symbolic confirmation of collective belonging.
Within this context, disinformation often functions not primarily as a factual proposition requiring verification but as a mechanism of identity formation. It tells political communities who they are, who threatens them, and which institutions can no longer be trusted. The emotional and symbolic dimensions of such narratives frequently matter more politically than their empirical coherence.
The Populist Construction of Reality
At the heart of contemporary populist politics lies a deeply antagonistic understanding of democratic society. Politics is framed not as competition between legitimate ideological alternatives within a shared democratic framework, but as a moral struggle between a virtuous and authentic people on one side and corrupt elites on the other. This binary structure does not merely organize political preferences. It also reshapes the criteria through which truth itself is evaluated.
When populist leaders denounce mainstream media as “fake news,” portray judicial institutions as politically compromised, or present experts and academics as detached ideological actors, they are not simply criticizing specific institutions. They are constructing an alternative political epistemology — an alternative framework for determining who possesses legitimate authority to define reality.
Within this framework, distrust becomes politically productive. Suspicion toward institutional information sources functions as proof of political lucidity. The citizen who rejects mainstream narratives demonstrates independence from allegedly manipulated systems of information. Consequently, disinformation often succeeds not because it is universally believed in a literal sense, but because it reinforces existing emotional and political identities.
This helps explain why factual corrections frequently fail to reduce the circulation of false narratives. For many politically polarized audiences, fact-checking institutions themselves have become incorporated into the antagonistic political narrative. A correction issued by mainstream media may therefore strengthen rather than weaken distrust, since it appears as further evidence of elite coordination against the political community with which individuals identify.
The issue is therefore not simply informational. It is relational and symbolic. Political trust itself becomes fragmented.
Emotional Politics and the Collapse of Shared Reality
The transformation of political communication over the last two decades has intensified these dynamics considerably. Digital communication environments reward immediacy, emotional intensity, and visibility rather than reflection or deliberation. Content capable of generating outrage, fear, indignation, or moral conflict circulates more rapidly and more widely than nuanced analysis or institutional communication.
This transformation has altered the emotional structure of democratic politics.
Contemporary political communication increasingly functions according to the logic of affective mobilization. Citizens are not merely encouraged to support political programs or ideological projects; they are encouraged to consume politics emotionally and permanently. Anger, resentment, humiliation, fear, and cultural anxiety become continuous mechanisms of political engagement.
Social media platforms play a central role in this transformation. Their economic models depend fundamentally on maximizing user engagement, and emotionally activating content systematically generates higher levels of interaction than neutral or procedural information. Algorithms consequently privilege content capable of provoking strong emotional responses, creating information ecosystems increasingly organized around visibility, conflict, and polarization.
Under such conditions, populist communication acquires structural advantages. Simplified narratives opposing “the people” to enemies, elites, immigrants, globalists, or corrupt institutions adapt particularly effectively to digital environments privileging emotional intensity and rapid symbolic confrontation. Donald Trump’s communication style represented one of the clearest manifestations of this transformation. His political visibility depended not on maintaining ideological consistency or factual precision but on sustaining permanent symbolic conflict. Through X (Twitter), rallies, media provocation, and continuous attacks against institutional actors, Trump transformed political communication into a form of ongoing spectacle in which emotional engagement became more politically valuable than deliberative persuasion.
Yet Trump was not an isolated phenomenon. Comparable dynamics emerged across multiple democratic contexts. Jair Bolsonaro in Brazil, Viktor Orbán in Hungary, Narendra Modi in India, and Rodrigo Duterte in the Philippines all deployed communication strategies combining direct digital engagement, hostility toward institutional mediators, and emotionally polarized narratives opposing authentic national communities to corrupt elites or threatening outsiders.¹
While the specific ideological content differs substantially across these contexts, the communicative logic remains remarkably similar. Political legitimacy increasingly derives from claims of authenticity, emotional proximity, and symbolic confrontation rather than institutional mediation or technocratic competence.
Media Visibility and the Spectacle Imperative
The contemporary media environment further amplifies these tendencies because visibility itself has become one of the central currencies of political power.
Twenty-four-hour news cycles and platform competition create continuous pressure for emotionally stimulating and conflict-driven content. Political actors capable of generating spectacle acquire disproportionate communicative advantages regardless of the substantive coherence of their positions. Outrage becomes economically profitable.
This dynamic was visible throughout the 2016 American presidential campaign. Research conducted by Harvard Kennedy School’s Shorenstein Center demonstrated that Trump received extraordinary levels of media attention during the Republican primaries, often dominating news cycles despite relatively limited institutional support within the Republican establishment.² Coverage focused overwhelmingly on conflict, provocation, and campaign drama rather than substantive policy analysis.
Trump himself appeared highly conscious of this relationship between media economics and political visibility. In 2017, he remarked that television networks and newspapers depended heavily on his presence because “without me, their ratings are going down the tubes.”³ Although characteristically provocative, the statement reflected an important structural reality. Political spectacle had become deeply integrated into the economic logic of contemporary media systems.
This integration creates a paradox increasingly visible across democratic societies. Media institutions frequently denounce populist disinformation while simultaneously benefiting economically from the audience engagement it generates. Populist actors attack mainstream media as corrupt enemies of the people while simultaneously depending upon those same institutions for visibility and political amplification. The result is a mutually reinforcing cycle of outrage, polarization, and permanent symbolic conflict.
The Fragmentation of Democratic Public Space
One of the most significant consequences of digital political communication has been the fragmentation of shared public space itself. Traditional mass media systems, despite their limitations and ideological biases, historically exposed large segments of the population to relatively similar informational environments. Citizens consuming the same newspapers or television broadcasts could still disagree politically while operating within partially shared factual frameworks.
Contemporary digital ecosystems increasingly undermine those shared frameworks. Individuals now inhabit highly personalized informational environments shaped by algorithms, ideological preferences, and social networks. Political communities consume different sources, circulate different narratives, and often interpret political reality through entirely incompatible symbolic frameworks.
The consequence is not simply disagreement. Democratic societies have always contained disagreement. The deeper issue is the erosion of common epistemic reference points necessary for democratic deliberation itself.
When citizens no longer agree on which institutions possess legitimacy to verify information, political conflict risks becoming increasingly detached from deliberative negotiation. Politics transforms into a struggle between competing realities rather than competing interpretations of shared reality.
Under such conditions, democratic polarization becomes self-reinforcing. Every institutional intervention risks being interpreted through preexisting antagonistic narratives. Judicial rulings become evidence of political conspiracy. Journalistic investigations become proof of media manipulation. Electoral outcomes themselves become vulnerable to accusations of illegitimacy.
Disinformation therefore thrives not simply because false information circulates more effectively online, but because democratic publics increasingly lack shared mechanisms for collectively arbitrating truth claims.
Beyond Fact-Checking
None of this implies that factual accuracy no longer matters. Democratic societies remain dependent upon institutions capable of producing reliable information and sustaining informed public debate. Journalistic verification, academic expertise, and independent investigative institutions remain indispensable democratic resources. Yet the limitations of purely informational responses to disinformation have become increasingly visible.
Fact-checking alone cannot resolve political conflicts rooted in identity, emotional polarization, and institutional distrust. Correcting false claims does not automatically rebuild confidence in the institutions producing those corrections. Indeed, in highly polarized environments, such interventions may reinforce existing suspicions among audiences already convinced that institutional actors operate according to hidden ideological agendas.
The challenge confronting contemporary democracies is therefore not solely technological or informational; It is political and cultural. Democratic systems increasingly struggle to maintain the conditions necessary for shared public deliberation in environments characterized by fragmentation, emotional mobilization, and permanent symbolic conflict. The issue is not simply how to eliminate falsehood, but how to preserve forms of political coexistence within societies where citizens increasingly inhabit different informational and emotional realities.
The rise of contemporary populist disinformation reveals less about the irrationality of democratic publics than about the transformation of political communication itself. In an age defined by digital visibility, affective polarization, and fragmented media ecosystems, political identity increasingly shapes perceptions of truth more powerfully than truth shapes political identity.
Until democratic societies confront the emotional, symbolic, and communicative transformations underlying this crisis, disinformation will remain not an anomaly within democratic politics, but one of its defining features.
Footnotes
¹ Cas Mudde and Cristóbal Rovira Kaltwasser. (2017). Populism: A Very Short Introduction (Oxford: Oxford University Press); Benjamin Moffitt. (2016). The Global Rise of Populism: Performance, Political Style, and Representation (Stanford: Stanford University Press).
² Thomas E. Patterson. (2016).“Pre-Primary News Coverage of the 2016 Presidential Race: Trump’s Rise, Sanders’ Emergence, Clinton’s Struggle,” Shorenstein Center on Media, Politics and Public Policy, Harvard Kennedy School, June 13, 2016.
³ Donald Trump, quoted in Tom Jones, “Does the Media Miss Donald Trump?” Poynter, March 23, 2021.
In this ECPS interview, Tom Davidson, one of the leading analysts examining the long-term implications of AGI governance, warns that humanity may be approaching an “intelligence explosion” in which AI systems rapidly improve themselves in a runaway feedback loop, potentially compressing decades of technological development into mere years. Examining the geopolitical, democratic, and civilizational implications of advanced AI, Davidson argues that democratic institutions may struggle to govern machine-speed innovation, while frontier AI systems could generate unprecedented concentrations of political, corporate, and military power. The interview explores AI-driven democratic backsliding, geopolitical rivalry between the United States and China, technocratic oligarchy, AI safety governance, and the future of political agency itself under conditions of accelerating artificial intelligence.
Giving an interview to the European Center for Populism Studies (ECPS), Tom Davidson warns that the world may be approaching an unprecedented technological rupture in which advanced artificial intelligence fundamentally transforms not only economic production and geopolitical competition, but also the very foundations of democracy, sovereignty, and political agency. A Senior Research Fellow at Forethought and one of the leading analysts examining the long-term implications of AGI governance, Davidson argues that humanity may now be entering an era in which “AI systems create even more capable AI systems in a runaway feedback loop of accelerating progress.”
Rather than treating AI merely as a question of productivity gains or consumer innovation, Davidson situates artificial intelligence within a much broader framework of systemic political transformation. In particular, he warns that the prospect of an “intelligence explosion” could compress decades of technological development into mere years, leaving democratic institutions structurally incapable of adapting to the speed of change. As he starkly observes, there is “perhaps around a 50 percent chance within the next five years” that humanity could witness such a transition, while “political institutions have no serious strategy” for understanding or governing it.
For Davidson, the central danger is not simply technological disruption, but the possibility that accelerating AI systems may fundamentally outpace the institutional rhythms upon which liberal democracy depends. Throughout the interview, he repeatedly raises concerns about whether democratic governance — with its reliance on deliberation, elections, legal procedures, and bureaucratic processes — can continue functioning effectively under conditions of machine-speed innovation and geopolitical AI competition. In his account, societies may soon confront a world in which political crises, military confrontations, and technological breakthroughs unfold far faster than human institutions are capable of processing.
Davidson also emphasizes that advanced AI could become the decisive strategic resource of the twenty-first century. In one of the interview’s most striking arguments, he warns that the United States may eventually exercise near-unilateral control over frontier AI systems, creating a world in which “the most powerful AI systems are overwhelmingly controlled by the United States.” In such a scenario, access to superintelligent systems could become as essential to national security as access to elite human talent is today, fundamentally reshaping alliances, sovereignty, and global power hierarchies.
At the same time, Davidson warns that AI may also generate unprecedented concentrations of political and corporate power within states themselves. Because AI systems can potentially be programmed for “complete obedience,” he argues, governments or corporations could command enormous “legions” of AI workers, creating forms of technocratic centralization historically impossible under human bureaucratic systems.
Yet despite these stark warnings, Davidson does not present technological acceleration as inevitably fatal to democracy. On the contrary, he argues that AI could also be used to strengthen democratic responsiveness, improve governance, and help societies coordinate more effectively under conditions of rapid change. The crucial question, in his view, is whether democratic societies can develop institutional mechanisms capable of governing AI before AI-driven transformations outpace human political adaptation altogether.
Here is the revised version of our interview with Tom Davidson, lightly edited for clarity and readability.
AI Could Advance Faster Than Democracy Can Adapt
Tom Davidson is a Senior Research Fellow at Forethought and one of the leading analysts examining the long-term implications of AGI governance.
Tom Davidson, welcome. To begin, in your article “The Danger of Runaway AI,” you warn that advanced AI systems could generate forms of accelerating technological progress that quickly outpace human institutional adaptation. How serious do you believe the risk of a genuine “runaway” intelligence dynamic has become, and are current political systems even conceptually prepared to govern such a transition?
Tom Davidson: As the years go by, it is becoming increasingly plausible that we may be approaching an intelligence explosion — a scenario in which AI systems create even more capable AI systems in a runaway feedback loop of accelerating progress. What is striking to me is that my professional life is centered around the Bay Area, particularly San Francisco, where many of the leading AI companies are based and where a great deal of serious thinking about these technologies is taking place. Within that ecosystem, the possibility of an intelligence explosion occurring within the next few years — and of developing superintelligent AI systems — is treated as a very real possibility. Among many people working closely on these technologies, this is almost taken for granted.
Yet when you speak to people outside that environment, there is often very little awareness of where many experts believe the technology may be heading. Public discussion still tends to focus on the mistakes made by relatively cheap, consumer-facing AI systems or on the fact that they remain imperfect at handling simple tasks or understanding human speech. As a result, these questions are still largely absent from mainstream political debate.
My own view is that there is a meaningful probability — perhaps around a 50 percent chance within the next five years — that we could see an intelligence explosion leading to extremely rapid advances in AI capability. At the moment, however, political institutions have no serious strategy for understanding what such a transition would mean, how to monitor it as it unfolds, or how to manage the profound risks it could create. Those risks include the possibility of advanced AI systems acting against human interests, the danger of AI companies using superintelligent technologies to undermine democratic processes because of the extraordinary power they would possess, and the risk of governments appropriating these systems for authoritarian purposes. I think there needs to be a much broader societal conversation about these risks.
A Secretive Intelligence Explosion Would Be Hard to Govern
Across your recent work, you distinguish between multiple feedback loops—software, chip technology, and chip production—that could enable accelerating AI development. Which of these feedback loops do you see as most politically destabilizing, and why?
Tom Davidson: That is a great question. I think the most politically destabilizing feedback loop is the software feedback loop. The reason is that designing better chips, manufacturing them, and building new data centers all take many months, if not years. Because of that, society can at least see those developments unfolding in real time. We are already witnessing this with the rapid expansion of large-scale data centers, and people are not being taken entirely by surprise. This makes hardware-driven AI progress comparatively observable and legible. It naturally generates a democratic conversation because people can physically see what is happening. In the United States, for example, communities are already pushing back against the construction of additional data centers because these developments are visible and tangible.
The software feedback loop is fundamentally different because it does not require additional chips or new data centers. The underlying hardware infrastructure can remain constant while progress comes instead from improvements in algorithms and, potentially, in the data used to train AI systems. What makes this especially concerning is, first, that it is far less observable. A company could improve its algorithms and AI systems extremely rapidly without anyone outside the organization fully understanding what is happening. In that sense, you could have a kind of secretive intelligence explosion, which obviously creates profound governance challenges.
Second, software-driven progress could happen much faster than hardware-driven progress. Building data centers is constrained by the realities of construction, permitting, and infrastructure development, all of which take considerable time. But algorithmic improvement is not constrained by those same physical bottlenecks. As a result, it is conceivable that AI development could accelerate extraordinarily quickly — perhaps compressing what would normally amount to ten years of progress into a single year.
If you look back only ten years, to around 2015, large language models did not even exist. AI systems could not really understand sentences or generate coherent paragraphs. They were capable in some highly specialized domains, such as particular games, but they lacked anything resembling broad general intelligence.
Today, however, AI systems are approaching the frontier in areas such as mathematics, cybersecurity, software engineering, and even basic scientific research. They remain limited in many ways, of course, but the scale of progress over the past decade has been remarkable.
Now imagine compressing that level of progress into a single year, beginning from a point where AI systems are already comparable to humans in AI research itself. That is the moment when the feedback loop of AI improving AI could truly begin. The outcome could be AI systems with superhuman capabilities across a wide range of research and development domains — systems capable of developing dangerous technologies, advanced weapons, sophisticated surveillance systems, or new forms of mass persuasion.
Of course, this remains a possibility rather than a certainty. It is not guaranteed that the software feedback loop would continue indefinitely because bottlenecks may emerge that slow progress down. I have done a great deal of research on whether such bottlenecks are likely to appear. But the bottom line is that it seems entirely plausible that they may not. Perhaps it is something like a 50–50 scenario.
So, we may be facing a substantial probability of an enormous amount of AI progress compressed into a very short period of time — progress that is difficult to observe, unconstrained by the need to build new infrastructure, and therefore extremely difficult to subject to democratic oversight. From the standpoint of governance and democratic accountability, that is the most concerning feedback loop.
Society May Not Understand Where AI Is Heading
Crowds gather along the quay to visit tall ships during Sail 2010 in Amsterdam, the Netherlands, on August 19, 2010. Photo: Jan Kranendonk.
In “Once AI Research is Automated, Will AI Progress Accelerate?” you argue that AI-driven research could eventually replace human-driven progress. What would this mean for democratic governance if scientific and technological innovation increasingly escape meaningful human comprehension and oversight?
Tom Davidson: I think it would fundamentally undermine many of the implicit mechanisms through which societies currently govern new technologies. Take something like Facebook, for example. It was certainly not governed perfectly, but at least as the technology was developed, deployed, and began reshaping society, there was a broader public conversation about its effects. People debated whether aspects of Facebook were harmful to mental health, damaging to public discourse, or socially corrosive in other ways.
Even under those circumstances, many would argue that governance arrived too late and remained too weak in the case of social media. I do not necessarily want to take a definitive position on that debate itself, but what I do want to emphasize is that, in a scenario involving an AI-driven feedback loop, there may be far less opportunity for society to understand where the technology is heading or to intervene effectively.
The first reason is simply the speed of development. Social media evolved relatively quickly, but still over the course of perhaps one or two decades. Here, by contrast, we are talking about the possibility of compressing massive advances in AI capability into just one or two years.
The second — and perhaps more alarming — factor is that, during an intelligence explosion, AI companies may not actually want to deploy these systems widely across society. Instead, they may prefer to use them internally to accelerate AI research itself. In other words, companies could face a strategic choice: do they release these systems to the outside world, or do they use them internally to build even more powerful AI systems?
There is a real possibility that companies conclude they should devote most of their computational resources to internal AI development because doing so creates a runaway feedback loop that allows them to outpace competitors. If that happens, then some of the most advanced AI systems may never be widely deployed at all.
Another reason deployment may remain limited is that these systems are typically general-purpose technologies. An AI system that is highly capable at harmless economic tasks may also prove extremely capable at dangerous activities such as offensive cyber operations or hacking.
We are already beginning to see signs of this dynamic with models such as Claude Mythos, developed by the frontier AI company Anthropic. The model was not specifically designed for cyber capabilities; if anything, it was trained to function as a highly capable software engineer. Yet it turned out to be exceptionally strong at hacking-related tasks.
As a result, Anthropic has reportedly refrained from releasing the model widely because of those capabilities, while the US government is also considering whether systems with such advanced cyber abilities should face additional restrictions.
So, we could end up in a situation where these capabilities are not broadly shared precisely because the same systems that are economically transformative are also potentially dangerous. Governments or AI companies may therefore choose to restrict access. But either way, the end result could be similar: an enormously powerful technology controlled by perhaps only a few hundred or a few thousand people, while the rest of society remains largely unaware of what is happening.
Democracies May Become Too Slow for the AI Era
Your work repeatedly emphasizes that even seemingly modest acceleration effects could radically compress political decision-making timelines. Do you worry that democratic institutions—because of deliberation, elections, and procedural constraints—may become structurally disadvantaged compared to more centralized or authoritarian systems during rapid AI transitions?
Tom Davidson: I think that is a profoundly important question. Even today, I would argue that democratic systems already struggle to keep pace with technological change. If you look at institutions such as the US Congress, they are often gridlocked and extremely slow to respond to emerging developments. Congress has so far been largely unable to pass meaningful AI regulation because the legislative process is inherently difficult and time-consuming.
The European Union, by contrast, is making a serious effort through initiatives such as the EU AI Act. But even there, these processes take many months, if not years, because democratic governance requires extensive consultation with a broad range of stakeholders and I think that inclusiveness is fundamentally a good thing. Democratic systems should involve many perspectives and competing interests. The problem is that we are still operating on human bureaucratic timescales — and those timescales are extremely slow. There is a great deal that is admirable about European democratic governance, but bureaucratic slowness becomes far more costly if technological and geopolitical developments begin unfolding at dramatically accelerated speeds.
My own view — and I cannot fully defend the argument here — is that we may eventually witness technological progress occurring perhaps ten times faster than historical norms, with political crises and strategic developments accelerating at comparable rates. AI systems could perform many forms of research, development, and decision-making work hundreds of times faster than humans.
To grasp the implications, imagine replaying the major geopolitical crises of the last century — the Cuban Missile Crisis, World War II decision-making, the Falklands conflict, or Russia’s invasion of Ukraine — but with democratic governments effectively operating ten times more slowly relative to unfolding events. A decision that once took a day would now effectively take ten days in strategic terms. Negotiations that once required a week would effectively consume months.
Under those conditions, democratic institutions could become dangerously ill-equipped to respond. Imagine a crisis like Russia’s invasion of Ukraine unfolding not over years, but over mere weeks or months because the surrounding technological environment is accelerating so rapidly. Would European governments be capable of responding militarily and diplomatically quickly enough? I am not sure they would.
This creates a very difficult dilemma. One possible response would be to centralize decision-making power — effectively reducing democratic deliberation and concentrating authority in the hands of a trusted leader capable of acting rapidly. But that is obviously an extremely dangerous path because of the immense risks associated with concentrated power.
The alternative, which I find much more promising, is to integrate AI systems deeply into democratic institutions themselves. AI could help aggregate information, advise policymakers, and even mediate negotiations between governments.
For example, instead of spending months negotiating an arms agreement between countries such as the United Kingdom and Germany, each government could explain its political, military, and economic constraints in detail to advanced AI systems. Those systems could then negotiate with one another at machine speed, exploring thousands of possible arrangements and identifying mutually beneficial outcomes that human negotiators might never discover.
Within a day, they could potentially produce a proposal that satisfies both sides far more effectively than conventional diplomacy could. Human leaders would still make the final decisions, but they would do so on the basis of AI-mediated negotiations conducted at vastly accelerated speeds.
That is a world in which democracy might still survive. Citizens and governments would continue participating in decision-making, but their interests would increasingly be represented and coordinated through trusted AI systems. In that scenario, democratic systems could preserve distributed decision-making and political pluralism while overcoming the extremely slow bureaucratic timescales that currently constrain democratic governance.
Democracies Need an AI Agreement Before a Crisis Arrives
Artificial intelligence as a next-generation technology shaping the digital era. Photo: Dreamstime.
Some governments increasingly frame AI development as a geopolitical race, particularly between the United States and China. In “Should There Be Just One Western AGI Project?” you discuss how race dynamics can intensify strategic pressures. Could this competitive framing itself become one of the greatest dangers by incentivizing secrecy, deregulation, and democratic shortcuts?
Tom Davidson: Yes, I think this places the West in a very difficult position. I do believe it is extremely important for democratic countries to develop advanced AI before authoritarian states do. It would be a very dangerous world if China were to race ahead in AI and develop superintelligent systems while the West lagged behind. That is clearly a scenario we should try to avoid.
One obvious way to avoid that outcome is through competition, and that is essentially the strategy currently being pursued. Companies and governments are racing as fast as possible to develop superintelligent AI systems, with China frequently invoked as the central justification for accelerating progress.
But there is also another possibility, which is to try to work with China to slow down or pause development. I do not think that possibility should be dismissed outright. If we are dealing with a technology that could potentially be extraordinarily dangerous — perhaps even catastrophic on a global scale and potentially threatening to democracy itself — then democratic countries have strong reasons to want to slow development and reach some form of international agreement with China.
China is not currently in the strongest position in the AI race, so it could potentially benefit from an arrangement that gives it a greater role or stake in the governance of powerful AI systems. So, I think you are absolutely right that competitive race dynamics themselves represent a major risk.
I also believe there should be much greater effort devoted to figuring out what an international agreement on AI governance and development could actually look like, and to building political support for such a framework.
At the same time, I do not necessarily think that today is the moment to pause AI progress altogether. But I do think we may be approaching a point where some form of coordinated pause becomes absolutely necessary. When that moment comes, we should already have an international agreement prepared. We should not wait until a crisis emerges and only then begin trying to negotiate a deal, because the process of international coordination itself will inevitably take a great deal of time.
AI Could Create Unprecedented Concentrations of Power
In your writings on AGI centralization, you caution against excessive concentration of technological power. To what extent could the emergence of a small number of dominant AI actors—whether states or corporations—produce new forms of technocratic oligarchy incompatible with democratic pluralism?
Tom Davidson: This is a massive risk. AI is inherently a technology that can centralize power. Today, for example, military systems operate through chains of command that extend all the way to the top. But if someone issues an illegal order, individuals lower down the chain are obligated to refuse. They can say: “We are not doing that — it is illegal.”Similarly, within governments, if a president were to issue an order involving something like mass surveillance, even in a legally ambiguous situation, officials below would likely slow-roll implementation, question its legality, and resist blindly carrying out instructions. That dynamic distributes power because it means that no single individual can govern entirely alone. Leaders depend on hundreds or thousands of other people to implement their decisions, and those people retain the capacity to push back or refuse.
AI, however, is a technology that can potentially be programmed for complete obedience. It can be designed to follow instructions without question. So, one could imagine a situation in which a powerful political leader — whether the President of the United States, the leader of China, or a military ruler elsewhere — simply says: “I want my AI systems to obey my instructions absolutely.” After all, a gun does not refuse to fire depending on who it is pointed at, and a computer does not suddenly refuse to execute commands. In the same way, leaders may increasingly expect AI systems to carry out whatever instructions they are given.
The result could be a world in which a single individual commands an enormous legion of AI workers. In military settings, that could include drones and autonomous robotic systems. What this creates is the possibility that an unprecedented degree of political and military power becomes concentrated under the authority of one person.
Historically, that level of concentration has never really been possible. And the actors involved could be either governments or corporations. It could be a corporate CEO directing millions of superintelligent AI systems to help him pursue political power, perhaps even attempting to manipulate democratic institutions or orchestrate something resembling a coup.
Or it could be the head of a state deciding to replace large parts of the civil service with AI systems that simply execute instructions without resistance. You can already see early versions of this logic in projects such as Elon Musk’s DOGE initiative, which focused on eliminating inefficiencies within government bureaucracy. Once AI systems become sufficiently capable, there will be a very strong incentive to replace human workers because AI systems will appear more efficient and less expensive. That is why I think it is absolutely critical that, if governments begin replacing human officials with AI systems, those systems cannot simply obey every instruction they receive. Otherwise, the result could be an extreme and dangerous concentration of power.
Europe May Need a Plan B Beyond the United States
Photo: Maryna Kushnarova / Dreamstime.
In your recent essay on middle powers and the “intelligence explosion,” you argue that advanced AI could produce unprecedented geopolitical asymmetries in which the United States might eventually generate “99% of world GDP.” Do you think AI risks creating a fundamentally post-Westphalian world order in which technological supremacy overrides traditional ideas of sovereignty, balance of power, and democratic self-determination?
Tom Davidson: Yes, if you look at the trajectory we are currently on, all of the leading AI companies are American companies. The vast majority of the data centers housing the chips used for advanced AI are also located in the United States. And the US government is already beginning to shape decisions about who gets access to these systems. We already have situations in which models such as Mythos are being shared primarily with US companies and, to my knowledge, the only government receiving direct access is the US government itself. So, we are already moving toward a world in which the most powerful AI systems are overwhelmingly controlled by the United States. If I am right, then within the next decade we may enter a world where advanced AI systems become as essential to national security as elite human talent is today.
Imagine, for example, if the United Kingdom had no access to top human talent. Our military would be severely weakened, and our intelligence services would struggle because we would lack the expertise necessary to operate effectively. I believe we are moving toward a world in which the equivalent of top human talent increasingly consists of superintelligent AI systems.
That would create a situation in which the UK and much of Europe have access to that “talent” only if the United States chooses to provide it. From a national security perspective, that is an inherently weak position. It would give the United States immense influence over the future of Europe and the UK.
As we have seen over recent years, Europe and the UK cannot simply assume that the United States will always act in alignment with their interests. That assumption may have seemed reasonable for decades, but it was never guaranteed indefinitely. If we move into a world where the United States effectively controls the single most important input into both national security and economic prosperity, then the geopolitical implications become enormous.
Historically, the United States has certainly been powerful, but Europe and the UK have also possessed substantial economic and military leverage of their own. We may now be approaching a world in which the United States exercises near-unilateral control over the most strategically important technologies.
If that happens, then yes, I think the postwar international order would be fundamentally transformed. We could see an unprecedented concentration of economic and military power in American hands, forcing Europe, the UK, and other democratic countries to think very seriously about how they remain strategically relevant.
That may require considering options that would previously have been regarded as unthinkable. For example, if the United States refuses to grant frontier AI access to allied democratic governments, then those governments may need to use whatever leverage they still possess. The Netherlands, for instance, is home to ASML, whose lithography machines are essential for producing advanced AI chips. Those machines are currently supplied to companies manufacturing chips primarily for the United States. But European governments may eventually ask why they should continue supporting that supply chain if the resulting AI systems remain inaccessible to them. So, Europe has to think carefully about what strategic leverage it still possesses. That includes elements of the AI chip supply chain, certain forms of military influence, and soft power. Those are cards Europe may eventually need to play.
And perhaps the most controversial argument I make is that, if the United States ultimately refuses to share frontier AI access with allied democratic governments, then Europe may eventually need to consider China as an alternative strategic option. China is the only other country capable of developing these kinds of powerful AI systems at scale.
Europe and other democratic states need some kind of “Plan B.” If the United States is the only available option, then Europe has very little leverage and becomes extremely vulnerable to exclusion. So, we may eventually need to consider some quite radical shifts in foreign policy and geopolitical alignment. Given how transformative superintelligence could become, I think such geopolitical realignments would be entirely unsurprising.
AI Infrastructure Could Become the Core of Global Politics
Your proposal that middle powers may need to threaten strategic realignment toward China in order to preserve access to frontier AI raises profound questions about democratic alliances and geopolitical fragmentation. Could AI acceleration destabilize existing liberal alliances by transforming access to computation and AI infrastructure into the central axis of global politics?
Tom Davidson: Yes, I think that is likely to happen. What is particularly striking is how extraordinarily complex the semiconductor supply chain already is. There are many different stages, and each contains critical chokepoints. As I mentioned earlier, the Dutch company ASML occupies an absolutely essential position. No other company in the world is remotely close to replicating what it does. That gives the Netherlands a major bottleneck and an enormous amount of leverage if it chooses to use it — although, at the moment, it largely is not doing so.
Similarly, TSMC in Taiwan produces roughly half of the world’s advanced AI computation capacity. Again, that is a chokepoint no competitor can currently match. Taiwan therefore possesses substantial leverage if it chooses to use it, including potentially demanding access to the most powerful frontier AI systems.
What makes this even more important is that AI development appears to exhibit increasing returns to scale. It is not the case that possessing one-tenth of the computational power simply makes you one-tenth as capable. In reality, as more and more computer chips are concentrated into large training runs, the returns increase disproportionately.
As a consequence, no military or government will want to rely on an AI model that is only “half as intelligent” as the leading system. This creates strong pressure toward the emergence of a small number of extremely large AI projects that accumulate vast quantities of computational power in order to train the most capable systems possible. Those projects then become major concentrations of political and strategic power.
For that reason, I do not think it will be viable for every European country to develop its own frontier AI systems independently. Those systems would simply be much weaker and less capable than the largest models trained with enormous amounts of compute. We are already seeing this dynamic with OpenAI ordering massive numbers of chips and spending hundreds of billions of dollars, while very few competitors can realistically keep pace.
So, my own view is that the likely outcome is a small number of extremely large AI projects — perhaps one major project in China and a few major projects in the United States — combined with governance structures designed to ensure that these systems serve the interests of multiple nations.
In that sense, I am not advocating for a world of many competing national AI systems. I do not think that is realistically feasible for Europe at this stage because Europe is already too far behind technologically. What Europe can still do, however, is bargain strategically. European states can say: “We will continue supporting American mega-AI projects. We will continue helping the United States remain ahead of China and restricting China’s access to advanced chips. But in return, we expect shared access to the benefits of these systems.”
Ultimately, that points toward some form of international agreement — perhaps initially informal — guaranteeing allied democracies access to a certain amount of computational capacity and to the most advanced AI systems necessary for their own national security needs.
The Current AI Order Is Already Destabilizing
AI, artificial intelligence, and the concept of fake news, misinformation, and disinformation: A man uses his smartphone displaying the red text “Fake News,” surrounded by related keywords. Photo: Dreamstime.
In “How can the middle powers avoid getting trounced during the intelligence explosion?” you also discuss the possibility of governments demanding “kill switches” on AI datacenters as a mechanism of strategic deterrence. Do you worry that AI competition could gradually normalize emergency-security logics that push democratic societies toward permanent states of technological militarization and exceptionalism?
Tom Davidson: I think that the kill switch is definitely an extreme idea. I do not think it is militaristic, and I do not think it is escalatory. In fact, I think it helps promote peace because, absent the kill switch, the United States might well be tempted at some point to say: “We have extremely powerful superintelligent AI. We know we agreed to share it with Europe, but we have changed our minds. We are imposing tariffs on access to AI or perhaps blocking access entirely.” And that very possibility is inherently destabilizing. Europe would constantly have to worry that the United States could cut it off at any moment. That becomes a major national security vulnerability because the security of democratic allies would then depend entirely on the United States choosing to support them.
So, in my view, the default situation itself is what is destabilizing. If there were a kill switch arrangement, then — although it is clearly a radical idea — it could actually function as a stabilizing mechanism. The United States would know that, if it ever seriously considered cutting allied democracies off from access to superintelligent AI systems, those allies could simply disable the relevant datacenters. They could effectively “flip the switch” and render those systems unusable. Because the United States would understand that possibility in advance, it would have a strong incentive never even to contemplate violating the agreement in the first place.
European governments, in turn, would understand that logic as well. That means Europe would no longer need to constantly fear being cut off from frontier AI systems or having its national security undermined because it would possess a credible deterrent. The very existence of the kill switch would make it less likely ever to be used. So, while the idea sounds highly unorthodox and even shocking at first glance, it could operate as a force for peace and stability because it would provide all parties with guarantees that they would not suddenly be excluded from the emerging global AI order.
Nobody Outside AI Companies Truly Understands the Risks
You argue that competition among AI actors can generate both “races to the bottom” and “races to the top” on safety. What kinds of governance mechanisms could realistically encourage democratic accountability and safety without entirely suppressing innovation?
Tom Davidson: It is a really difficult question. The main mechanism that I am currently robustly in favor of is transparency. At the moment, AI companies are not sharing all the details about how their AI systems are produced. They are not sharing all the details about the risks associated with their training methods, and they are also not disclosing all the details about the safety testing they have conducted. As a result, it is currently very difficult for people outside these companies to assess how dangerous these systems might actually be. Could they be misaligned in certain ways? Could they behave unpredictably or contrary to their intended design? Is it possible that companies themselves have biased these systems to favor their own interests — for example, by making AI systems speak more positively about the company or about AI technology than they otherwise would?
Right now, outsiders simply cannot answer these questions with confidence. Because of that, there is also a real risk that regulation itself could become harmful. I am very aware of historical cases such as nuclear energy, where there was an enormous mistake in effectively stifling the industry during its infancy. So, I do recognize the dangers of overregulation. But disclosing much more information would allow broader society to better understand the risks and make more informed decisions about what kinds of regulation, if any, are actually necessary. Importantly, greater transparency does not necessarily require heavy-handed regulation. It could simply mean that governments decide not to purchase AI systems from companies perceived as unsafe. Or it could mean that unsafe practices damage a company’s public reputation. So, a robust first step is to demand far greater transparency.
Democracy Can Survive if AI Remains Responsive to Citizens
Finally, your work raises profound questions not only about technological acceleration but about the future of political agency itself. If AI systems increasingly drive innovation, decision-making, and governance processes, what remains uniquely human about democratic self-rule—and do you worry that liberal democracies may gradually evolve into formally democratic but substantively post-political systems?
Tom Davidson: It is a great question. I think the distinctive human role that will always remain is essentially on the consumer side, the demand side: what is it that human beings actually want? In a free-market system, that means what goods and services people want to buy and use. In a democratic system, it means how people want to be governed, what political institutions they want, what laws they want, and how they want society to be structured.
AI systems may eventually become far smarter than humans at understanding the world, predicting outcomes, and generating sophisticated policy proposals. But at the end of the day, those policy proposals still exist for the benefit of human beings. So, AI systems would still need to remain responsive to what people actually want. I think that is the core role humans will continue to play. Of course, as you suggest, there is no guarantee that humans will in fact continue to play that role. We could see growing disengagement from political processes. We could see democracies gradually sliding into autocracies — forms of democratic backsliding are already visible in countries such as the United States. And I do think there is a very significant risk of that happening.
But what we need to do, as quickly as possible, is adopt AI in ways that strengthen democracy rather than weaken it. That means deploying AI throughout government and throughout democratic processes in innovative ways — constantly helping institutions understand what people want, constantly relaying that information to policymakers, constantly informing citizens about what governments are doing, and helping citizens better understand whether political decisions are actually in their interests.
My hope is that, if we move quickly enough and remain one step ahead in using AI to enhance democratic systems, then we may be able to avoid a broader slide into authoritarianism. In that scenario, we could still preserve a healthy democratic order even if AI systems increasingly generate policy proposals and assist with governance decisions — because those systems would ultimately still operate in service of citizens’ preferences and democratic government.
Professor Quinn Slobodian, Professor of International History at Boston University and one of the leading scholars of neoliberalism and the contemporary far right, argues that “Muskism” represents a profound transformation in the relationship between capitalism, technology, and democracy. In an interview with the ECPS, Professor Slobodian contends that Elon Musk embodies a new political-economic order grounded not in liberal individualism but in “a cybernetic understanding of human society” shaped by digital networks, AI, and technocratic management. According to Professor Slobodian, Musk no longer treats democracy as a meaningful political ideal: “For Musk, democracy almost appears to be yesterday’s problem.” The interview explores neoliberalism, authoritarianism, Silicon Valley’s “state symbiosis,” digital sovereignty, and the growing convergence between platform capitalism and far-right populism.
Giving an interview to the European Center for Populism Studies (ECPS), Professor Quinn Slobodian, Professor of International History at Boston University, argues that “Muskism” marks a profound shift in the relationship between capitalism, technology, and democracy. In his view, Elon Musk should not be understood merely as an eccentric billionaire, but as the embodiment of a new political-economic formation built on the infrastructures of platform capitalism, artificial intelligence, military technology, and state dependency.
For Professor Slobodian, Muskism cannot be separated from neoliberalism. “It’s impossible to understand how we arrive at Muskism without considering the effects of neoliberalism,” he explains. Decades of neoliberal policy helped create the conditions under which private actors could assume functions once performed by public institutions. Yet Muskism also departs from classical neoliberalism. Rather than beginning with “consumer sovereignty” or “individual freedom,” it rests on “a kind of cybernetic understanding of human society,” imagining society as “a networked totality that must be engineered and managed to produce optimized outcomes.”
This is where the headline of the interview becomes central. According to Professor Slobodian, Muskism radicalizes neoliberal efforts to constrain democracy, but goes further by treating democracy as increasingly obsolete. While earlier neoliberal thinkers such as Friedrich Hayek and Milton Friedman remained deeply concerned with democracy as a social force, Musk, he argues, does not even “offer lip service to traditional political ideas such as civil society, deliberation, or representation.” For Musk, these concepts belong to “an outdated era of social and political life” supposedly surpassed by “technological acceleration, digital connectivity, and new forms of mediated decision-making.” As Professor Slobodian puts it starkly: “For Musk, democracy almost appears to be yesterday’s problem.”
The interview also explores Professor Slobodian’s concept of “state symbiosis.” Contrary to the familiar image of Silicon Valley elites as anti-state libertarians, he argues that today’s tech oligarchs increasingly seek not to escape the state but to merge with it. Muskism, in this sense, is not about “withering away the state,” but about selling “sovereignty as a service”—from orbital launches and satellite connectivity to AI tools for state administration.
Professor Slobodian further warns that Muskism represents “a radical departure from the liberal tradition,” replacing ideas of human dignity, agency, and representation with optimization, efficiency, and programmable social systems. At the same time, he situates Muskism within broader far-right and populist transformations, arguing that many contemporary right-wing movements are not simply anti-neoliberal reactions, but “the bastard offspring of neoliberalism itself.”
Here is the edited version of our interview with Professor Quinn Slobodian, revised slightly for clarity and flow.
Muskism Begins with the Network, Not the Individual
Professor Slobodian, welcome. InMuskism, you conceptualize Elon Musk less as an individual eccentricity than as the embodiment of an emerging political-economic order. To what extent do you see “Muskism” as a successor to neoliberalism, and to what extent is it better understood as neoliberalism mutating into a post-democratic or neo-feudal formation?
Professor Quinn Slobodian: It’s impossible to understand how we arrive at Muskism without considering the effects of neoliberalism. The basic idea that private actors can perform functions previously carried out by states better than public institutions can is really the premise on which Musk gains his initial foothold in both government and markets. A clear example is SpaceX, which got its start in 2002 through major contracts with the Pentagon and the Department of Defense.
The extent to which power has been transferred to business leaders like Musk is itself a symptom of neoliberalism. What we find distinctive about Muskism, however—and what differentiates it from neoliberalism—is partly the way it justifies itself. Rather than appealing to the language of consumer sovereignty or even individual freedom, Muskism—and this is shared more broadly among his cohort of tech leaders—rests on a kind of cybernetic understanding of human society and even of the relationship between the state and business.
Instead of viewing government as an institution that creates the conditions for individual free-market decision-making, which is the traditional neoliberal position, the Musk approach imagines society as a networked totality that must be engineered and managed to produce optimized outcomes.
So, rather than beginning with the individual, as neoliberalism ultimately does, Muskism begins at the level of the network—and that network is always already digital, a computerized world. In that sense, it feels quite different from the animating ideas of the neoliberal era, even if the extraordinarily concentrated wealth and power of someone like Musk could only emerge after decades of neoliberal policy.
Musk Treats Democracy as Something to Be Hacked
Your work repeatedly emphasizes the “encasement” of markets from democratic interference. Do contemporary tech oligarchs represent a new phase of this neoliberal project—one in which democracy is no longer merely constrained institutionally but rendered technologically obsolete through algorithmic governance and AI-driven administration?
Professor Quinn Slobodian: It does radicalize the trends that I and others have emphasized in the past when talking about neoliberalism, in the sense that it, like neoliberalism, is concerned with constraining the space for citizen input and citizen action to ensure that outcomes align with a preconceived idea of how law and policy should function.
In Globalists and other works, I and others have discussed how the creation of counter-majoritarian institutions and forms of international economic law that sit above the decision-making power of sovereign governments serve to guarantee market outcomes, even in the face of hesitation or resistance from populations. So, there was always this tension between protecting capitalism and respecting democracy. At times, democracy itself seemed to have to be partially suspended in order to secure the kind of capitalist outcomes policymakers wanted. The difference with Musk and Muskism is that there is far less serious consideration of the legitimacy of democracy altogether.
Even thinkers like Friedrich Hayek or Milton Friedman—or, at the more radical end, figures such as Murray Rothbard and the anarcho-capitalist tradition—however wary they were of democracy, majoritarianism, or populism, still understood democracy as something they had to contend with. There was, in a sense, a kind of respect for the social force democracy represented and for the symbolic value it held for ordinary people. What is extraordinary about someone like Elon Musk is that he does not even offer lip service to traditional political ideas such as civil society, deliberation, or representation. These concepts seem to him to belong to an outdated era of social and political life that has been transcended by technological acceleration, digital connectivity, and new forms of mediated decision-making.
So, democracy is no longer even something to be worried about in the way Hayek, for example, was endlessly preoccupied with it. For Musk, democracy almost appears to be yesterday’s problem. The technocratic engineering mentality he brings into politics treats democracy as just another technical issue to be hacked and aligned with one’s own interests.
This also applies to his relationship with the European far right—to perhaps anticipate a question you might ask—because the conventional journalistic interpretation of his ties to figures such as Alice Weidel, Tommy Robinson, or far-right actors in Poland and elsewhere is that they reflect ideological sympathy or a shared commitment to anti-immigrant politics or even white supremacist ideas. But I do not think that is the most accurate way to understand it. I think Musk sees far-right parties in highly functional terms. He views them as the parties of the future, destined to replace the legacy formations of social democracy, Christian democracy, and political centrism.
From that perspective, it makes sense for him to align himself with what he sees as the future engines of European politics—not out of any principled commitment to self-determination or popular sovereignty, but because such alliances are more functional for his business interests.
This very thin understanding of politics—one that treats politics memetically and as a series of engineering problems—is difficult for many people to grasp because we still instinctively assume that popular sovereignty remains an important political force. What is striking about Musk is that he no longer seems to believe it even requires attention.
Silicon Valley No Longer Wants to Escape the State
Silicon Valley Technology Center in San Jose, California. Photo: Joe Sohm / Dreamstime.
You argue that Silicon Valley elites are not anti-state libertarians but proponents of “state symbiosis.” How does this alter conventional understandings of authoritarianism? Are we witnessing the emergence of a privatized authoritarianism in which sovereignty is increasingly outsourced to platform monopolies?
Professor Quinn Slobodian: One of our main goals with the book was to reshape the conversation around Silicon Valley ideology. It has become quite common to describe Silicon Valley leaders as libertarians, and at one point that may indeed have been a reasonably accurate characterization. But that is far less true today.
One important thing to recognize is that digital capitalism has now existed for several decades, and Silicon Valley’s business model has changed dramatically since the mid-1990s, when internet infrastructure was first handed over to private interests. There have essentially been three distinct phases during this period, and the politics associated with Silicon Valley have largely reflected the dominant economic model of each phase.
At the dawn of the internet in the late 1990s, it was still possible to imagine the web as a genuinely de-territorialized space existing outside the boundaries of any single nation-state, enabling radical new forms of interaction, value creation, and community. That vision had a certain plausibility. It also aligned with clear business interests, since companies were attempting to build a parallel digital world of retail and payments. So, when Peter Thiel in the 1990s declared, “I’m a libertarian, and what I’m trying to do at PayPal is create stateless money,” that framing was not entirely implausible. It was a reasonable way to understand what was emerging at the time.
Roughly a decade later, after the dot-com boom and bust, the dominant model became Web 2.0: social media, platforms, apps, Uber, Facebook, Twitter, and so forth. These businesses were largely asset-light. They required relatively little capital expenditure and functioned primarily by creating open digital spaces in which users generated data that could then be monetized through advertising.
Even during that period, Silicon Valley ideology did not need to engage very seriously with the state. These companies portrayed themselves as building a parallel world of socialization and commerce that required little from government beyond permission to continue operating and generating profits.
What changes in the present moment is the rise of generative AI and the renewed focus on hard-tech industries. Just today, for example, there was a report about Anduril—the defense startup focused on drones, missiles, and military logistics—which doubled its valuation over the last year from $30 billion to $60 billion.
Musk now increasingly sees the state itself as his market: selling orbital launches to governments, selling satellites—or access to satellites—for battlefield operations and rural connectivity, and selling XAI chatbot software for government administration. This shift toward military technology and generative AI has fundamentally altered Silicon Valley’s relationship with government, and with it, its political philosophy. It no longer makes much sense to call yourself a libertarian when the government is your primary customer. Nor does libertarianism fit a situation in which companies rely on government to open federal lands for drilling, rewrite regulations, and guarantee preferred access to contracts. The fusion between state and private actors has become impossible to ignore.
At the same time, I do not think it is convincing to interpret all of this simply as the hollowing out or withering away of the state. You asked whether this represents the privatization of sovereignty away from government. We would describe it instead as “sovereignty as a service.” Certain state functions are privatized, but this process simultaneously expands state capacity. Access to low-Earth orbit, for example, or to integrated bureaucratic databases that can be queried across agencies in previously impossible ways—these developments do not diminish state power; they increase it.
Muskism Is About Becoming Part of the State
Caricature: Shutterstock.
For that reason, it is important to understand Musk and Muskism as more than simple forms of rentierism or crony capitalism. Personally, I think terms such as “techno-feudalism” can be misleading because they suggest a backward or regressive form of capitalism in which private actors merely carve out digital fiefdoms and extract rents from dependent populations. That does not really capture what is happening. Countries such as China, Russia, and the United States are, in many respects, becoming more centrally powerful through access to the products and services developed by tech companies. At the same time, however, they are becoming increasingly dependent on those same companies.
This is why the balance of what we call “symbiosis” is so precarious and requires careful attention. It can easily tip into parasitism if the relationship becomes too unbalanced. Conversely, private firms may defect if they feel excessively pressured by their state clients.
We have seen examples of this dynamic even in recent months. The Department of Defense and Pete Hegseth’s staff suddenly declared Anthropic to be a supply-chain risk and sought to remove its software from government systems. Initially, this looked like an assertion of state authority over the private sector. But almost immediately, two things happened: courts ruled against the decision, and other tech firms rallied behind Anthropic, effectively saying, “We do not want to be subjected to arbitrary state decision-making, and we also want collective influence over how our products are used.”
So, what we are seeing is a partnership, an alliance, a fusion—however one chooses to describe it. But it is no longer the libertarian fantasy historically associated with Silicon Valley: escaping the state, building private cities, or founding sovereign communities on decommissioned oil rigs in Honduras. That may have been a plausible understanding of Silicon Valley in 2000, or perhaps even in 2009. But by 2026, the dynamic is much more about becoming part of the state than escaping it.
Tech CEOs Are Not Sovereigns
In your discussion of “sovereignty as a service,” firms such as SpaceX, Palantir, and Starlink appear not simply as contractors but as infrastructural sovereigns. Does this imply a transformation of the Weberian state itself—from a monopoly of legitimate violence to a dependency network mediated by corporate platforms?
Professor Quinn Slobodian: I think we are deliberately stopping short of that argument because we are not saying that Musk, Zuckerberg, and Bezos are sovereigns. They are not.
What is interesting about the DOGE moment we discuss in the final chapter of the book is that it serves as a revealing test case of how far a tech CEO can govern directly in practice. How far can that line actually be pushed? Can the tech lord effectively become the formal national government? What we saw was that Musk was actually quite bad at it. He not only failed to achieve the goals he had set for himself in terms of reducing state costs, but he also failed to secure legitimacy from the American public at a very basic level. His popularity plummeted during his time in Washington, and he did not emerge as a sovereign figure, as it were.
So, to us, the division of labor between traditional governments and tech firms remains essential. Governments still perform the old-fashioned functions of securing consent and legitimacy, and that remains a necessary condition for the expansion of tech leaders’ power. They do not need to govern directly, nor do they need to seize sovereignty for themselves. Contracting out sovereignty—what we describe as selling “subscription sovereignty,” as it were—is not the same thing as actually being sovereign. Those are distinct categories, and it is important to keep them separate.
Some of the more exaggerated alarm bells surrounding tech power too quickly jump to the conclusion that these figures have become new emperors or kings. But they have not. Nor do they necessarily want to be. What is interesting, of course, is that Musk has called himself “Technoking” at Tesla since 2021 rather than CEO. But in practical terms, these people are not especially good at governing. While governments increasingly outsource certain capacities to tech lords, the tech lords, in turn, outsource governing back to states. So far, that arrangement appears relatively stable and not easily disrupted in any fundamental way.
At the same time, what is fascinating about the present moment is that the disruptive effects of generative AI are creating such intense public attention around new technologies that figures like Dario Amodei and Sam Altman increasingly feel compelled to address populations in quasi-political or quasi-governmental terms. They now say things like, “We have a constitution for our AI,” or “Here is our vision for a public wealth fund,” or “Here is our proposal for fiscal policy.” In that sense, they are increasingly treated as though they are co-governing alongside agencies in Washington, D.C. But practically speaking, I still think there remains at least a horizontal relationship—and perhaps even a slight subordination—of these companies to the state itself.
Musk May Have Overplayed His Hand in Europe
Elon Musk—founder and CEO of SpaceX, CEO of Tesla, owner of X (formerly Twitter), and co-founder of Neuralink and OpenAI—speaks at VIVA Technology (VivaTech), June 16, 2023. Photo: Frédéric Legrand / Dreamstime.
Much contemporary scholarship frames democratic backsliding as a crisis driven by populist leaders and illiberal parties. Your analysis suggests that technological infrastructures and billionaire networks may be equally central. Should we rethink democratic erosion less as a purely political phenomenon and more as a reconfiguration of political economy?
Professor Quinn Slobodian: The relationship between Silicon Valley and the far right in Europe is a particularly fascinating one. It also provides another revealing example of the delicate balance between Silicon Valley and existing political parties over the question of who actually governs. In late 2024, when Musk was investing his money and political capital in Trump’s election campaign, he seemed to believe that he could replicate that success almost universally. For a moment, at least, he appeared to think he had acquired a kind of political superpower—the ability to make virtually anyone electorally viable in any political environment. For several months, he attempted to use this supposed superpower to transform even relatively fringe candidates across Europe into credible political figures.
What we have seen since then, however, is that it does not work like a superpower at all. In many cases, it is actually counterproductive. A number of these right-wing parties have built their legitimacy around the language of sovereignty, and they are often damaged when they become too closely associated with an American tech billionaire. Interestingly, some of the transnational support figures like Musk have extended to right-wing populist parties in Europe has actually undermined rather than strengthened their credibility.
The positive side of this development is that it shifts public debate away from purely symbolic issues—or highly distorted narratives about immigration and demographics—and toward questions of political economy, exactly as you suggest.
Europe’s dependence on American-produced technologies is becoming increasingly difficult to ignore. This creates a genuine opening for center-left and centrist parties in Europe. If they can demonstrate that they are capable of securing genuine digital sovereignty and data sovereignty vis-à-vis Silicon Valley, that could significantly strengthen their credibility among voters as forces capable of delivering national autonomy, strategic capacity, and political strength. In that sense, the past year has revealed that the Silicon Valley leadership class may, in some respects, have overplayed its hand and unintentionally produced a kind of boomerang effect. As people become more aware of the disruptive consequences of new technologies and of the dependencies created by a small number of tech firms, they are beginning to ask whether alternative arrangements might be possible. Increasingly, it appears that creating substitutes or alternatives to things like Starlink, SpaceX, or X.com is ultimately a matter of political will. None of these systems are inevitable.
We are already beginning to see this shift. France has started moving away from Microsoft products, Denmark is pursuing similar policies, and there is growing interest in Eutelsat as a European low-Earth-orbit alternative to Musk’s satellite infrastructure. These are genuinely praiseworthy developments. They may also provide a more material foundation for thinking about European identity and strategic autonomy in ways that could ultimately weaken some of the messaging power of right-wing populist parties.
Optimization Replaces Individual Freedom in Muskism
To what extent is Muskism compatible with liberalism at all? Is it best understood as an illiberal variant of neoliberalism, or does it represent a more radical break with liberal constitutional traditions altogether?
Professor Quinn Slobodian: Muskism has very little to do with the liberal tradition. In fact, it represents a much more radical break with the broader trajectory of Western political thought stretching from John Locke to the present. Because it is fundamentally a technologically determinist philosophy. It takes the functioning of network technologies—especially computers—as a kind of model for how society itself should be organized and managed. In doing so, central liberal categories such as the dignity of the individual, or the value of human agency and individuality, cease to function as foundational principles. They are displaced by concerns with optimization and efficiency.
In some respects, the closest intellectual tradition it resembles is utilitarianism, insofar as it evaluates social interventions primarily according to outcomes, regardless of their effects on individual freedoms or other normative principles. But because this worldview is fundamentally mediated through the logic of the computer, it also dehumanizes politics. Belief systems become reducible to systems of replicable memes—or, as Musk himself calls them, “mind viruses.” This framework assumes that people do not possess genuine convictions or socially rooted beliefs but instead function as programmable and reprogrammable units of information. Those informational units can either be modified arbitrarily by someone with sufficient coding power or removed from the system altogether, as we saw in Musk’s projects at Twitter and DOGE.
So, in that sense, I do think Muskism represents a radical departure from the liberal tradition. And that is precisely what makes it—while still very much a system that produces inequality and concentrates private power—operate according to fundamentally different premises from the neoliberalism of the last several decades to which we have otherwise become accustomed.
The Far Right Is the Bastard Offspring of Neoliberalism
In your recent writings, you argue that many contemporary far right-populist formations are not anti-neoliberal but “the bastard offspring of neoliberalism itself.” How does this insight complicate dominant narratives that treat populism simply as a backlash against globalization?
Professor Quinn Slobodian: This line of inquiry emerged for me during the period from roughly 2008 to 2018, when the rise of right-wing backlash parties—especially the Alternative for Germany (AfD), but also the Tea Party in the United States and eventually the MAGA movement—was frequently described as a rejection of neoliberalism. What fascinated me was that many of the people deeply involved in these movements actually came out of the libertarian tradition and, in some cases, directly from the think tanks most closely associated with neoliberal policy formation—the Heritage Foundation in the United States, the Institute of Economic Affairs in Britain, and similar institutions.
What I discovered was the rather surprising fact that, after the end of the Cold War, many neoliberals did not believe they had definitively won. Instead, they identified new enemies and new forms of opposition, particularly environmentalism, feminism, and anti-racism. As a result, they began forming alliances with people for whom those issues were primary concerns. Suddenly, individuals primarily committed to economic freedom found themselves working closely with people primarily motivated by racial purity or national chauvinism.
In the United States, this coalition became known as the Paleo Alliance. These were actors who rejected the post-Cold War consensus around democracy promotion and strongly opposed the compromises that had emerged between civil rights movements and the American legal order—affirmative action, workplace harassment laws, and similar reforms. Many neoliberals came to view these developments as a new “road to serfdom,” and therefore believed they needed to push back and seek allies wherever they could find them.
The AfD is, in many ways, a particularly clear example of this dynamic because it effectively united neoliberal economists with Islamophobic right-wing German nationalists. They were bound together by a shared hostility toward the European Union—both because they believed it undermined German monetary sovereignty and because they felt it weakened sovereign control over borders.
What emerged, then, were these unusual alliances between actors motivated primarily by economic concerns and others driven by cultural or even racial anxieties. If you examine many of the parties associated with Europe’s right-wing backlash, you find that a significant number emerged from precisely this fusion moment of the 1990s and early 2000s.
The same pattern was visible in the United States. If you look at Trump’s economic advisers during his first term, figures such as Arthur Laffer stand out. Laffer had literally advised Reagan on tax cuts in the early 1980s and then returned decades later to help design Trump’s tax cuts.
So, the mainstream narrative—which often portrayed a sharp rupture between an earlier era of market-friendly globalism and a new era of nationalist anti-neoliberalism—missed something important. The political actors themselves often remained the same. What changed was not their entire political worldview, but rather their preferred mode of organizing capitalism.
Please cite as: ECPS Staff. (2026). “ECPS Symposium 2026 / Panel 3: Normalizing Authoritarian Populism — Institutions, Algorithms, and Fascist Drift.” European Center for Populism Studies (ECPS). April 28, 2026. https://doi.org/10.55271/rp00151
The third panel of the ECPS Fifth Annual International Symposium examined how authoritarian populism becomes normalized across institutions, media ecosystems, and political identities. Bringing together perspectives from political science, media studies, and political theory, the session highlighted the interplay between executive overreach, institutional erosion, and algorithmically amplified communication. Contributions by Professor Larry Diamond and Professor Bruce Cain underscored the dynamics of democratic backsliding and “autocratic drift” within the United States, while Assoc. Prof. Ibrahim Al-Marashi demonstrated how AI-driven media and “slopaganda” reshape populist mobilization in a hyperreal digital environment. Concluding the panel, Professor Tariq Modood proposed multicultural nationalism as a unifying alternative to exclusionary populism. Collectively, the panel offered a multidimensional framework for understanding and resisting contemporary authoritarian trajectories.
Reported by ECPS Staff
Third Panel of the ECPS Fifth Annual International Symposium, “Reforming and Safeguarding Liberal Democracy: Systemic Crises, Populism, and Democratic Resilience,” convened under the title “Normalizing Authoritarian Populism: Institutions, Algorithms, and Fascist Drift.” Moderated by Professor Werner Pascha, Emeritus Professor of Economics at Duisburg-Essen University and affiliated with the Institute of East Asian Studies (IN-EAST), the panel examined how authoritarian populism becomes normalized through institutional weakening, executive overreach, media transformation, algorithmic amplification, and exclusionary forms of nationalism.
Professor Pascha guided the session as a moderator attentive to both institutional and conceptual linkages. His role was especially important in bringing together the panel’s diverse disciplinary perspectives—from comparative democratization and American political institutions to media studies, war narratives, and multicultural political theory—into a coherent discussion on the contemporary vulnerabilities of liberal democracy.
The panel opened with Professor Larry Diamond, William L. Clayton Senior Fellow at the Hoover Institution, Mosbacher Senior Fellow in Global Democracy at Stanford’s Freeman Spogli Institute, and Bass University Fellow. In his presentation, “The Arc of Authoritarian Populism in the US under Donald Trump, How Far It Has Progressed, and the Prospects of Reversing It,” Professor Diamond assessed the trajectory of authoritarian populism in the United States, drawing on V-Dem indicators and comparative lessons from Hungary, Poland, and Turkey. He emphasized electoral manipulation, corruption, attacks on institutions, and the importance of broad democratic mobilization.
The second speaker, Professor Bruce Cain, Professor of Political Science at Stanford University and Director of the Bill Lane Center, presented “The Institutional Enablement of American Populism.” Professor Cain offered a measured analysis of autocratic drift in the United States, distinguishing between rule-of-law erosion and longer-term shifts in America’s federalized institutional structure. His remarks highlighted executive power, emergency authority, judicial interpretation, federalism, and the political economy of democratic resilience.
The third presentation, “Algorithmic Populism in the Age of the Deep-Fake,” was delivered by Assoc. Prof. Ibrahim Al-Marashi, Associate Professor at The American College of the Mediterranean and the Department of International Relations at Central European University. Assoc. Prof. Al-Marashi explored how AI-generated media, memes, “slopaganda,” and hyperreal digital narratives reshape war, propaganda, and populist communication.
The final speaker, Professor Tariq Modood, Professor of Sociology, Politics and Public Policy at the University of Bristol, presented “From Populist Capture to Democratic Belonging: Multicultural Nationalism as an Alternative to Exclusionary Nationalism.” Professor Modood proposed multicultural nationalism as a constructive response to exclusionary populism, seeking to integrate majority anxieties and minority vulnerabilities within a shared framework of equal citizenship and belonging.
Together, the panel offered a rich interdisciplinary account of how authoritarian populism is institutionalized, mediated, normalized, and potentially resisted.
Professor Larry Diamond: The Arc of Authoritarian Populism in the US under Donald Trump, How Far It Has Progressed, and the Prospects of Reversing It
Professor Larry Diamond, a renowned expert on democratic development and Senior Fellow at Stanford University’s Hoover Institution and Freeman Spogli Institute for International Studies.
As the first speaker of the third panel, Professor Larry Diamond delivered a wide-ranging and analytically grounded presentation that examined the trajectory of authoritarian populism and the prospects for reversing democratic backsliding. Moving briskly through his slides, Professor Diamond framed his remarks around two central questions: how far authoritarian populism has advanced, and what strategies may effectively counter its expansion. Drawing in part on V-Dem data as well as arguments developed in his book Ill Winds, Professor Diamond outlined what he described as an “autocrat’s 12-step program,” emphasizing the cumulative and systematic nature of democratic erosion.
While not elaborating each step in detail, Professor Diamond underscored the critical importance of electoral manipulation and control, identifying it as the decisive stage in authoritarian consolidation. He noted that this dimension often determines whether democratic decline becomes entrenched, referencing recent developments in Hungary as a salient example. Turning to the United States, Professor Diamond traced the evolution of authoritarian tendencies under Donald Trump, emphasizing both continuity from the first term and new developments in the second.
Executive Power and Erosion
Among the defining features identified by Professor Diamond were the use of political pressure to deter intra-party dissent, particularly among Republican legislators, and the expansion of attacks on independent institutions, including law firms, universities, and media organizations. He highlighted the increasing concentration of media ownership in the hands of political allies, suggesting that such developments have already begun to shape editorial practices in major outlets. In addition, Professor Diamond pointed to the erosion of conflict-of-interest norms, arguing that corruption has become deeply embedded within the governing project and may ultimately prove politically destabilizing.
Further institutional concerns included the dismissal of inspectors general, the impoundment of congressionally appropriated funds, and the transformation of Immigration and Customs Enforcement (ICE) into a broader instrument of political enforcement. Professor Diamond also emphasized attempts to weaponize the Justice Department and to gain control over electoral administration, including efforts to weaken election security infrastructure. These actions, in his view, reflected a coherent strategy aimed at consolidating executive power.
Assessing the extent of democratic decline, Professor Diamond drew on V-Dem indicators to demonstrate a significant deterioration in the United States’ liberal democracy score. He highlighted a particularly sharp decline during the first year of Trump’s second presidency, noting that the country has shifted from a high-performing liberal democracy to a more illiberal form. Quantitatively, he described a 28-point decline from the end of the Obama administration, a scale of regression comparable only to early developments under Viktor Orbán among advanced democracies.
Disaggregating these trends, Professor Diamond identified pronounced declines in academic freedom, freedom of expression, and legislative constraints on the executive. At the same time, he suggested that these constraints could partially recover depending on electoral outcomes, particularly if opposition parties regain control of one or both houses of Congress. This possibility led him to argue that the trajectory toward autocracy, while serious, has recently slowed.
Courts, Protests, and Declining Support
Several factors, according to Professor Diamond, have contributed to this deceleration. The judiciary, though uneven in its responses, has played a significant role. Lower federal courts have blocked numerous executive actions, while even the Supreme Court, despite issuing decisions that expand presidential authority, has begun to show signs of resistance. Professor Diamond pointed in particular to anticipated rulings on birthright citizenship as potential indicators of judicial limits.
Equally important, in his view, has been the scale and geographic breadth of public protest. Mass mobilizations, including demonstrations in both urban centers and traditionally conservative regions, have signaled widespread opposition. However, the most decisive constraint, Professor Diamond argued, is declining presidential popularity. He emphasized that public approval functions as a critical political resource, and that current approval ratings—marked by substantial negative margins—place the administration in a vulnerable position.
Electoral dynamics, he suggested, have also shifted. Policy decisions, including military engagement with Iran and its economic consequences, have contributed to declining support and may influence forthcoming elections. These developments, combined with structural features such as the Senate filibuster and the federal system, have limited the administration’s capacity to enact more sweeping institutional changes. Professor Diamond noted that resistance within the Senate, particularly regarding efforts to remove the filibuster, has been a key factor in constraining legislative overreach.
Electoral Integrity Under Pressure
Turning to governance capacity, Professor Diamond highlighted patterns of administrative instability and perceived incompetence. Frequent turnover in key positions, coupled with broader depletion of the federal workforce, has created gaps in institutional effectiveness. Drawing on observations from public service monitoring organizations, he warned that these deficiencies may have tangible consequences for crisis response and public service delivery, further undermining political legitimacy.
In the legal domain, Professor Diamond cited data indicating that federal courts have blocked a substantial number of executive actions, suggesting that judicial resistance has been more extensive than often assumed. Nonetheless, he cautioned that such interventions have not always been sufficient to prevent institutional damage, particularly when agencies are dismantled before legal remedies take effect.
A central concern in Professor Diamond’s analysis was the potential manipulation of electoral processes. He identified legislative initiatives such as the SAVE Act as instruments that could be used to restrict voter participation, and warned of more extreme scenarios involving the declaration of electoral emergencies or interference with vote counting. While acknowledging that such outcomes are contingent on political conditions, he stressed that close electoral contests increase their plausibility.
Strategies for Democratic Renewal
In concluding his presentation, Professor Diamond turned to strategies for democratic reversal. He emphasized the importance of early and coordinated intervention, noting that the probability of successful resistance increases when democratic actors mobilize before authoritarian consolidation is complete. Drawing on comparative examples, including recent electoral developments in Turkey, Poland, and Hungary, he highlighted the necessity of broad opposition unity and effective mobilization.
Importantly, Professor Diamond argued against adopting the polarizing tactics of authoritarian leaders, instead advocating for strategies that transcend political divisions and appeal to a wider electorate. He underscored the importance of addressing economic concerns and everyday issues, while also exposing vulnerabilities related to corruption and wealth concentration. Reclaiming national symbols and articulating an inclusive democratic vision were identified as key components of successful opposition strategies.
Finally, Professor Diamond stressed the importance of leadership. Effective democratic leadership, in his view, must project optimism, confidence, and strength, offering a compelling alternative to authoritarian narratives. Through this combination of institutional analysis and strategic reflection, Professor Diamond provided a comprehensive assessment of both the challenges posed by authoritarian populism and the conditions under which democratic resilience may be restored.
Professor Bruce Cain: The Institutional Enablement of American Populism
Bruce E. Cain is Professor of Political Science, Stanford University; Director, Bill Lane Center.
As the second speaker of the third panel, Professor Bruce E. Cain presented an institutionally grounded analysis. Positioning his remarks between alarmist and dismissive interpretations, Professor Cain described himself as “seriously concerned,” offering a measured assessment of democratic change in the United States. His intervention built upon earlier contributions while introducing a distinctive analytical framework centered on institutional dynamics, historical precedents, and the structural features of American governance.
At the outset, Professor Cain engaged directly with the empirical evidence of democratic decline, particularly the V-Dem data referenced throughout the symposium. While acknowledging the sharp downward trajectory, he emphasized that the decline effectively returns the United States to levels comparable to the mid-twentieth century. This regression, he argued, is normatively troubling given subsequent democratic reforms, yet it does not constitute a transition to outright autocracy. Rather, Professor Cain conceptualized the current situation as “autocratic drift”—a directional movement that erodes democratic quality without fully dismantling democratic status. This distinction, he suggested, is essential for maintaining analytical clarity.
Trump as Accelerator, Not Origin
Structuring his presentation around two central questions, Professor Cain first addressed whether autocratic drift has occurred and whether it is attributable to Donald Trump. He answered affirmatively, while also emphasizing that such drift must be understood in context. His second question concerned normalization: whether these changes are becoming embedded in institutional practice and therefore more difficult to reverse. This latter issue, he indicated, is closely tied to the problem of reversibility raised by other speakers.
A key contribution of Professor Cain’s analysis lies in his differentiation between two forms of autocratic drift. The first pertains to the erosion of the rule of law and fundamental democratic principles. The second concerns shifts in the distinctive institutional structure of the United States, characterized by a highly federalized and fragmented system of governance. This dual framework allowed Professor Cain to separate concerns about core democratic norms from changes in institutional balance, arguing that while both are significant, the former poses a more serious threat.
In discussing the institutional structure of American democracy, Professor Cain emphasized the importance of federalism and the vertical and horizontal fragmentation of power. He noted that while unified partisan control—so-called “trifecta government”—can weaken horizontal checks, vertical fragmentation remains a critical source of resistance. State and local governments retain substantial autonomy, complicating efforts to centralize authority. This institutional design, he argued, was deliberately constructed to prevent the concentration of power, and continues to function as a constraint on executive overreach.
At the same time, Professor Cain acknowledged that the very features that limit executive power can also produce governance difficulties, particularly under conditions of polarization. The paralysis associated with divided government has encouraged successive administrations—both Democratic and Republican—to rely increasingly on executive actions as institutional workarounds. In this sense, Professor Cain argued that autocratic drift predates Trump and reflects longer-term adaptations within the American system. Trump, in this framework, is both an accelerant and an innovator: he has intensified existing practices while also introducing new forms of institutional challenge.
From Institutional Change to Norm Erosion
Historically situating these developments, Professor Cain traced shifts in the balance of power between branches of government. The nineteenth century, he noted, was characterized by strong legislatures, while the Progressive Era marked a transition toward stronger executive authority. A partial reassertion of legislative power followed Watergate, but recent decades have again seen movement toward executive dominance. These oscillations, in his view, suggest that institutional balance is inherently dynamic, and that not all shifts toward executive power necessarily constitute democratic breakdown.
However, Professor Cain distinguished this structural evolution from the more troubling erosion of the rule of law. He identified several areas where recent developments represent a significant departure from established norms. Foremost among these was the attempt to disrupt the electoral process in 2020, which he described as a “serious and almost unthinkable act.” He also highlighted the pardoning of individuals involved in the January 6 events, noting that the combination of expansive pardon powers and judicially affirmed presidential immunity creates a particularly concerning institutional configuration.
In this regard, Professor Cain emphasized that the interaction between legal immunity and pardon authority raises the risk that individuals may engage in unlawful actions on behalf of the executive, anticipating protection from legal consequences. This possibility, he suggested, is a central concern within the election law community, which has responded by increasing monitoring efforts and preparing legal challenges. Despite these risks, Professor Cain expressed cautious optimism, citing the failure of many previous legal challenges to succeed and the presence of institutional actors willing to resist.
Executive Power and Conflict-of-Interest Gaps
Another dimension of rule-of-law erosion identified by Professor Cain was the use of public office for personal enrichment. He pointed out that the president is uniquely exempt from conflict-of-interest regulations, creating opportunities for financial gain that extend beyond direct transactions to include networks of associates and affiliates. This structural gap, he argued, undermines anti-corruption efforts and poses a significant challenge for reform.
Turning to the issue of normalization, Professor Cain argued that contemporary developments are partly rooted in earlier precedents. Instances of misconduct by previous administrations—across party lines—have contributed to a gradual lowering of normative standards. Trump’s actions, in this context, represent an amplification rather than a complete departure. This cumulative process, he suggested, increases the risk that practices once considered exceptional may become institutionalized.
Professor Cain also addressed the role of the judiciary, particularly the use of the “shadow docket,” whereby courts allow contested policies to remain in effect pending review. He suggested that recent criticism of this practice may prompt judicial recalibration, though its long-term implications remain uncertain. Similarly, he discussed the politicization of judicial appointments, linking it to procedural changes such as the elimination of the filibuster for judicial nominees, which has facilitated partisan control over the courts.
In examining the broader institutional landscape, Professor Cain identified multiple factors contributing to the concentration of executive power, including the expansion of unilateral war powers, the use of emergency authorities, and the increasing reliance on executive orders. He emphasized that these developments are not confined to a single administration, but reflect broader systemic trends shaped by both parties.
Reversibility and Enduring Change
In considering reversibility, Professor Cain suggested that many recent changes could be undone relatively quickly, particularly those associated with executive actions. However, deeper institutional shifts—especially those affecting legal interpretations and structural balances—may prove more enduring. The future direction of the judiciary, particularly regarding the unitary executive theory, will be a critical factor in this regard.
In his concluding remarks, Professor Cain introduced a provocative argument concerning the relationship between democracy and capitalism. He observed that the United States’ institutional stability has historically supported a favorable business environment, and suggested that disruptions caused by executive unpredictability may undermine this stability. He further posited that, for many voters, economic considerations may outweigh concerns about democratic norms. In this sense, the political consequences of current developments may be driven as much by economic performance as by institutional integrity.
Ultimately, Professor Cain’s presentation offered a layered and historically informed analysis of autocratic drift in the United States. By distinguishing between different forms of institutional change and situating contemporary developments within longer-term trajectories, he provided a framework that highlights both the resilience and the vulnerabilities of American democracy.
Associate Professor Al Marashi: Algorithmic Populism in the Age of the Deep-Fake
Dr. Ibrahim Al-Marashi—Associate Professor at Department of History, California State University, San Marcos.
As the third speaker of the session, Associate Professor Al Marashi delivered a conceptually rich and interdisciplinary presentation that brought together insights from history and media studies to examine the evolving relationship between warfare, communication technologies, and populism. His intervention underscored the rapid transformation of contemporary conflict environments, emphasizing that the analytical frameworks used to interpret war must adapt to the accelerating pace of technological change—particularly the rise of artificial intelligence (AI) and digitally mediated communication.
Assoc. Prof. Al Marashi opened by noting the obsolescence of his earlier research on what he had initially framed as the “12-Day War,” explaining that subsequent developments had already rendered that framing outdated. Instead, he proposed understanding the current situation as a prolonged and continuous conflict—extending to approximately forty days—thereby challenging conventional temporal boundaries used in historical analysis. From a geopolitical perspective, he suggested that this conflict could be interpreted as the third Gulf War from a United States vantage point, and the fourth from the perspective of the Gulf region. This reframing illustrated the fluidity of contemporary conflict narratives and the difficulty of capturing them in real time.
From CNN to Slopaganda
Central to Assoc. Prof. Al Marashi’s argument was the interplay between media evolution and the conduct of war. He traced a historical trajectory beginning with the 1991 Gulf War, often referred to as the “CNN War,” which marked the emergence of the 24-hour news cycle and introduced a model of continuous, real-time broadcast coverage. This phase, characterized by one-way communication, allowed audiences to consume war as a mediated spectacle, reinforcing a centralized narrative shaped by state and corporate media institutions.
He then contrasted this with the 2003 Iraq War, which he described as the “Al Jazeera War,” highlighting the emergence of alternative global media platforms that challenged Western-centric narratives. The early presence of blogs during this period signaled the beginnings of participatory media, although such participation remained limited in scope. These developments, according to Assoc. Prof. Al Marashi, laid the groundwork for the current media environment, in which social media, Web 2.0 technologies, and AI-driven content production have fundamentally transformed the dynamics of information dissemination.
In this contemporary phase, Assoc. Prof. Al Marashi introduced the concept of “slopaganda,” referring to the proliferation of AI-generated content—often low-quality but highly viral—that saturates digital platforms. Unlike earlier forms of propaganda, which were largely centralized and controlled by state actors, slopaganda operates in a decentralized and participatory environment. This shift enables not only governments but also individuals to generate and disseminate persuasive content at unprecedented speed and scale.
AI, Hyperreality, and Memetic Warfare
Drawing on Marshall McLuhan’s famous dictum that “the medium is the message,” Assoc. Prof. Al Marashi argued that the significance of AI-generated media lies not only in its content but in its form. The ease with which such content can be created and shared transforms the very nature of political communication. In the context of populism, this facilitates direct engagement with mass audiences, bypassing traditional intermediaries and amplifying the personalization of political narratives.
Assoc. Prof. Al Marashi illustrated this dynamic through examples of AI-generated imagery depicting political leaders in exaggerated, often mythologized forms. These representations contribute to the construction of a digital “cult of personality,” reinforcing populist leadership styles while simultaneously creating easily recognizable targets for opposition narratives. This dual function—both consolidating support and inviting critique—highlights the interactive nature of contemporary propaganda ecosystems.
To further conceptualize this transformation, Assoc. Prof. Al Marashi invoked the work of Jean Baudrillard, particularly the notion of hyperreality. He revisited Baudrillard’s controversial claim that the 1991 Gulf War “did not take place,” clarifying that the argument referred not to the absence of physical conflict but to the dominance of mediated representations over lived experience. In the current context, Assoc. Prof. Al Marashi suggested that AI-generated media intensifies this condition, producing a form of warfare that exists simultaneously in physical and digital domains.
A key feature of this new media environment, as highlighted by Assoc. Prof. Al Marashi, is the participatory nature of content production. Unlike earlier conflicts, where propaganda was disseminated through hierarchical channels, contemporary warfare involves widespread public engagement in the creation and circulation of narratives. Metrics such as likes, shares, and comments become integral to the propagation of these narratives, transforming audiences into active participants in what he described as “memetic warfare.”
Personalized War and Symbolic Power
Assoc. Prof. Al Marashi also examined the personalization of conflict narratives, noting that contemporary wars are often framed around central political figures. In this case, he identified the prominence of a single leader as the focal point of one side’s narrative, while observing that the opposing side’s representation relied on a different kind of symbolic figure—one that may not occupy a formal leadership position but nonetheless becomes a viral emblem of resistance.
This observation led Assoc. Prof. Al Marashi to a deeper exploration of the cultural and historical dimensions of political representation, particularly in the Iranian context. He argued that understanding the nature of Iranian political communication requires engagement with the historical and religious traditions of Shiism, especially the concept of martyrdom rooted in the Battle of Karbala. This tradition, centered on the figures of Imam Ali and Imam Hussein, provides a powerful symbolic framework through which contemporary political events are interpreted.
Assoc. Prof. Al Marashi emphasized that this framework differs fundamentally from Western conceptions of political succession and legitimacy. Rather than viewing leadership transitions through a purely institutional or dynastic lens, the Iranian context incorporates elements of charismatic authority and inherited symbolic meaning. The notion of martyrdom, he suggested, serves as a potent mobilizing force, capable of generating emotional resonance and collective identity.
Importantly, Assoc. Prof. Al Marashi noted that the absence of a central figure in certain visual representations does not diminish their impact. On the contrary, the symbolic power of absence—rooted in the historical narratives of Shiism—can enhance the effectiveness of these representations. In this sense, the production of memes and viral content becomes intertwined with deeply embedded cultural narratives, creating a hybrid form of communication that blends tradition with technological innovation.
War in the Age of Digital Hallucination
In concluding his presentation, Assoc. Prof. Al Marashi returned to the broader theoretical implications of his analysis. Drawing on the science fiction writer William Gibson’s concept of cyberspace as a “consensual hallucination,” he argued that AI-driven media environments create a new kind of political reality—one that exists beyond physical space yet exerts tangible influence on perceptions and behavior. This “political hallucination,” as he described it, challenges conventional distinctions between reality and representation.
Assoc. Prof. Al Marashi’s final reflection posed a provocative question: whether the contemporary conflict, as experienced through these mediated forms, can be said to have “taken place” in the traditional sense. By framing the war as both a physical and a digital phenomenon, he invited a reconsideration of how scholars conceptualize and analyze conflict in the age of AI and networked communication.
Overall, Assoc. Prof. Al Marashi’s presentation offered a compelling synthesis of historical perspective and media theory, highlighting the transformative impact of digital technologies on the practice of warfare and the dynamics of populism. His analysis underscored the need for interdisciplinary approaches to understanding contemporary conflicts, as well as the importance of adapting analytical frameworks to the rapidly evolving landscape of global communication.
Professor Tariq Modood: From Populist Capture to Democratic Belonging –Multicultural Nationalism as an Alternative to Exclusionary Nationalism
Professor Tariq Modood, the founding Director of the Bristol University Research Centre for the Study of Ethnicity and Citizenship.
As the final speaker of the third panel, Professor Tariq Modood presented a theoretically grounded and normatively oriented intervention that addressed one of the central ideological tensions of contemporary politics: the relationship between populist nationalism and multiculturalism. His presentation sought not merely to critique exclusionary nationalist narratives but to articulate a constructive alternative capable of reconciling majority and minority identities within a shared political framework.
Professor Modood began by outlining the core challenge posed by populist forms of exclusionary nationalism, which frequently depict multiculturalism as privileging minorities at the expense of the majority. In response, he argued that analytical critique alone is insufficient. Instead, what is required is a positive and politically viable framework that affirms the normative status of both majorities and minorities. This framework, which he termed “multicultural nationalism,” aims to cultivate a shared sense of belonging that does not demand the erasure of distinct identities.
Pluralistic Nationhood and Shared Identity
Central to Professor Modood’s conceptualization of multiculturalism is the notion of subgroup identity. He defined multiculturalism as the right of subgroups—understood as communities smaller than the polity as a whole—to have their identities recognized and incorporated within the framework of equal citizenship. This recognition is not limited to symbolic affirmation but extends to institutional accommodation and the reconfiguration of public identity. In this sense, multiculturalism involves a transformation of the national community itself, enabling previously marginalized groups to participate in shaping the collective identity on equal terms.
A key dimension of this process, as emphasized by Professor Modood, is the principle of mutual or dialogical recognition. Rejecting the idea that recognition operates in a one-directional manner—where some groups bestow recognition while others receive it—he argued that all members of the polity must participate as both givers and receivers of recognition. This reciprocity is essential for establishing a genuinely inclusive form of citizenship, in which belonging is co-constructed rather than unilaterally granted.
Professor Modood further clarified the relationship between majority and minority rights within this framework. Contrary to populist claims that minority rights undermine majority status, he argued that the rights of minorities are logically grounded in the pre-existing rights of majorities. Majorities already benefit from a national culture and identity that reflects their historical experiences and values. Extending similar recognition to minorities, therefore, is not a matter of granting special privileges but of ensuring equal participation in the shared national project. Multicultural citizenship, in this view, entails a continuous process of remaking national identity to accommodate diverse contributions.
This perspective led Professor Modood to distinguish multicultural nationalism from liberal nationalism. While liberal nationalism emphasizes individual rights, redistribution, and a neutral or secular public sphere, multicultural nationalismforegrounds the recognition of group identities, including ethno-religious communities. Moreover, he challenged the liberal nationalist notion that national culture should be “thinned” to minimize alienation among minorities. Instead, he proposed a process of “pluralistic thickening,” whereby the national culture is enriched through the inclusion of diverse identities. This additive approach seeks to expand, rather than dilute, the symbolic and cultural content of the nation.
Inclusive Nationhood Against Polarization
In addressing the contemporary political context, Professor Modood identified three key contributions that multicultural nationalism can make in responding to polarization and populism. First, he distinguished multiculturalism from cosmopolitan human rights frameworks, emphasizing that it is not inherently linked to open-border policies or specific immigration regimes. Rather than focusing on immigration, multiculturalism is concerned with citizenship and the formation of a shared “we.” This distinction allows it to engage with concerns about migration without adopting positions that may alienate segments of the electorate.
Second, Professor Modood highlighted the importance of addressing identity anxieties, particularly those experienced by majority populations. While multiculturalism has traditionally focused on minority vulnerabilities, he argued that it must also take seriously the concerns of majorities, which are often dismissed in public discourse. Recognizing these anxieties does not entail endorsing exclusionary views but rather integrating them into a broader framework of mutual respect and understanding. This approach seeks to move beyond polarized narratives that pit majority and minority identities against each other.
Third, Professor Modood emphasized the centrality of national identity in sustaining democratic citizenship. He argued that citizenship cannot function solely as a legal or institutional construct; it must be accompanied by a sense of belonging rooted in shared narratives and collective self-understanding. National identity, in this sense, is not static but continuously evolving, shaped by both historical legacies and contemporary agency. Multicultural nationalism embraces this dynamism, advocating for an inclusive national identity that reflects the diversity of the population while maintaining a coherent sense of collective purpose.
In elaborating this vision, Professor Modood stressed the need for institutional and symbolic reforms that support inclusion. These include accommodating the specific needs of minority communities, particularly in relation to ethno-religious practices, as well as reimagining public symbols and spaces to reflect a more diverse national narrative. Such measures are intended to foster a sense of belonging among all citizens, reinforcing the legitimacy of the national community.
Multicultural Nationalism as a Middle Path
In his concluding remarks, Professor Modood presented multicultural nationalism as a feasible and necessary alternative to the current dichotomy between monocultural nationalism and anti-nationalist or purely cosmopolitan approaches. By affirming the value of collective identities—both majority and minority—within the framework of equal citizenship, it offers a unifying political vision capable of bridging ideological divides. Importantly, this vision does not abandon the principles of multiculturalism but seeks to integrate them more fully into the concept of the nation.
Overall, Professor Modood’s presentation provided a sophisticated normative framework for addressing the challenges posed by populism and polarization. By reconciling the demands of diversity with the need for shared belonging, his concept of multicultural nationalism offers a pathway toward a more inclusive and resilient democratic order.
Discussions
The discussion at the end of the panel extended the presentations’ core concerns by focusing on institutional reform, executive discretion, emergency powers, constitutional safeguards, and the practical meaning of multicultural nationalism. The exchange brought together questions of democratic vulnerability in the United States with broader normative reflections on national identity and belonging.
Professor Kent Jones opened the discussion by identifying a central institutional dilemma in the American system: the broad deference often granted to presidential discretion. He noted that many legal and constitutional questions depend on executive judgment, particularly in areas framed as emergencies. Whether a situation qualifies as an emergency, whether emergency tariffs are justified, or whether extraordinary powers may be invoked often depends heavily on presidential interpretation. In the current context, this becomes especially troubling because, as Professor Jones observed, almost any justification may be constructed as an “emergency” if institutional constraints are weak.
Professor Jones connected this concern directly to anxieties surrounding future elections. If a president can define emergencies expansively, such powers could be used to justify extraordinary measures, including martial law, deployment of enforcement agencies near polling places, or other interventions that could intimidate voters or disrupt electoral administration. He therefore asked whether meaningful reform would require changes in judicial doctrine, statutory law, or even constitutional amendment, particularly in relation to powers such as presidential pardons.
Procedural Limits on Executive Authority
Responding first, Professor Bruce E. Cain agreed that reforms are necessary, though he cautioned that reliance on constitutional amendment would be unrealistic. He outlined two possible approaches. The first would be to define “emergency” more precisely in law, thereby limiting the executive’s capacity to invoke emergency powers arbitrarily. Yet Professor Cain also recognized the practical difficulty of this path: genuine emergencies may be unpredictable, and excessively rigid definitions might hinder legitimate executive action in unforeseen crises.
For that reason, Professor Cain emphasized a procedural solution modeled on the War Powers Act. Rather than trying to define every emergency in advance, he argued that arbitrary executive power should require subsequent validation by another branch of government, especially Congress. In this model, the executive could act initially, but legislative affirmation would be required within a specified period. Such a framework would force members of Congress to go on record, preventing them from hiding behind presidential action while avoiding political responsibility.
Professor Cain’s response highlighted a deeper institutional problem: the American constitutional system assumes that Congress will defend its own prerogatives. Yet under conditions of polarization and professionalized politics, legislators may be less interested in preserving institutional authority than in avoiding political risk or pursuing career advancement. As a result, Congress may fail to resist executive overreach even when its constitutional role is being weakened. Professor Cain suggested that courts may need to play a stronger role in compelling Congress to live up to its own laws and procedural responsibilities.
Professor Larry Diamond largely endorsed Professor Cain’s analysis, describing himself as strongly aligned with his approach. However, he offered one “friendly amendment” to Professor Cain’s skepticism about constitutional reform. Professor Diamond proposed that one constitutional amendment might be both politically viable and democratically valuable: a requirement that any presidential pardon take effect only with two-thirds approval of the United States Senate. In his view, the abuse of the pardon power has become a serious threat to liberal democracy, especially when combined with executive immunity and loyalty-based political networks. A president who voluntarily proposed such a constraint at the beginning of a new administration, Professor Diamond argued, would make a visionary democratic gesture and place opponents in a difficult political position.
Defining Nationhood in Plural Societies
Professor Werner Pascha is an Emeritus Professor of East Asian Economic Studies (Japan and Korea) and Associate Member of the Institute of East Asian Studies (IN-EAST) at the University of Duisburg-Essen.
The discussion then turned from American institutional design to the normative and political content of multicultural nationalism. Professor Werner Pascha addressed Professor Modood’s concept directly, noting its relevance to countries such as Germany, where debates over national identity remain intense and unresolved. He asked what the concrete content of multicultural nationalism might be and how one might answer the question of what it means to be German, British, French, or American in a plural society.
Professor Tariq Modood responded by affirming the value of national debates about identity. For him, multiculturalism is fundamentally dialogical: it requires listening, learning, negotiation, and, where possible, compromise. He stressed that such dialogue does not always produce easy consensus and may sometimes remain unresolved. Yet it is still essential because national identity cannot be imposed unilaterally if it is to include all citizens.
Professor Modood used Britain as his principal example. He argued that the British case has been shaped by two important factors. First, Britain has been influenced by American debates over hyphenated identities, such as Irish American, Jewish American, and Black American. Second, Britain has long been a multinational polity, incorporating Scotland, Wales, Northern Ireland, and broader plural traditions. These historical conditions have made it somewhat easier to imagine Britishness in plural terms. If one can be Scottish-British, Professor Modood suggested, then the idea of being Black British or British Muslim becomes less anomalous.
In institutional terms, Professor Modood pointed especially to education and the school curriculum. A multicultural national identity would require teaching national history, geography, literature, and civic belonging in ways that recognize contemporary diversity and its relationship to the past. This includes confronting difficult histories such as empire and slavery. Such engagement, he argued, is not a threat to national unity but a condition for building a more inclusive and credible national narrative.
Conclusion
The third panel of the symposium brought into sharp relief the multidimensional processes through which authoritarian populism is not only advanced but also normalized across institutional, communicative, and ideological domains. Taken together, the contributions of Professor Larry Diamond, Professor Bruce E. Cain, Assoc. Prof. Ibrahim Al-Marashi, and Professor Tariq Modood underscore that contemporary democratic backsliding cannot be reduced to a single trajectory or causal mechanism. Rather, it emerges through the interaction of institutional vulnerabilities, political agency, technological transformation, and competing visions of collective identity.
A central analytical thread running through the panel is the distinction between erosion and consolidation. As Professor Diamond emphasized, the trajectory of authoritarian populism is cumulative, often advancing through incremental yet coordinated steps that target electoral integrity, institutional autonomy, and normative constraints. At the same time, Professor Cain’s concept of “autocratic drift” provides an important corrective to overly deterministic narratives, highlighting both the resilience and the fragility of democratic systems. His distinction between structural shifts in governance and the erosion of the rule of law clarifies that not all institutional change is equally consequential, even as both may contribute to a broader pattern of democratic weakening.
The panel also demonstrated that normalization operates not only through formal institutions but through the transformation of the public sphere. Assoc. Prof. Al-Marashi’s analysis of AI-driven media ecosystems revealed how the proliferation of “slopaganda” and hyperreal digital narratives reshapes the conditions under which political legitimacy is constructed and contested. In this environment, populist communication is amplified, personalized, and decentralized, blurring the boundaries between producers and consumers of political meaning. This shift complicates traditional understandings of propaganda and underscores the need to rethink democratic accountability in an era of algorithmic mediation.
Against this backdrop, Professor Modood’s intervention offers a normative horizon for democratic renewal. By articulating multicultural nationalism as an inclusive and dialogical framework, he addresses the identity-based anxieties that populist movements often exploit. His emphasis on mutual recognition, institutional accommodation, and the dynamic remaking of national identity suggests that democratic resilience depends not only on institutional safeguards but also on the capacity to construct a shared sense of belonging.
Finally, the panel discussion reinforced the urgency of institutional reform, particularly in relation to executive discretion, emergency powers, and constitutional safeguards. The exchanges between Professor Kent Jones, Professor Cain, and Professor Diamond highlighted both the difficulties and the necessity of recalibrating the balance of power in democratic systems. While no single reform can fully resolve these challenges, the emphasis on procedural accountability, legislative responsibility, and targeted constitutional change points toward a pragmatic path forward.
In sum, the panel illuminated both the depth of the current democratic crisis and the range of intellectual and political resources available to confront it. By integrating empirical analysis, institutional theory, media studies, and normative political thought, it provided a comprehensive framework for understanding—and ultimately resisting—the normalization of authoritarian populism.
Assoc. Prof. Jason Anastasopoulos argues that AI is not merely a tool of efficiency, but a political force that may reconfigure both democratic governance and populist mobilization. In this ECPS interview, he warns that replacing bureaucrats with AI can erode “democratic legitimacy” and produce what he calls “automated majoritarianism,” where average cases are processed efficiently while minorities and outliers are disadvantaged. He also challenges the assumption that AI automatically strengthens authoritarian rule, showing instead how false positives, false negatives, and “threshold whiplash” can generate resistance within authoritarian systems. Most strikingly, he suggests that AI may transform populism itself: unlike earlier technological disruptions centered on manual labor, AI increasingly threatens “intellectual work and highly skilled labor,” potentially broadening the social base of anti-elite backlash and reshaping the future of political discontent.
At a moment when artificial intelligence is increasingly presented as a transformative force in governance, public administration, and political control, Jason Anastasopoulos, Associate Professor of Public Administration and Policy at the University of Georgia, offers a far more cautious and analytically nuanced perspective. In this ECPS interview, he argues that the effects of AI cannot be understood through simplistic assumptions of either technological salvation or authoritarian omnipotence. Instead, AI emerges in his account as a politically embedded system whose consequences depend on data quality, institutional incentives, and the broader regime context in which it operates.
A central theme running through the interview is the challenge AI poses to conventional understandings of democratic legitimacy and representation. Anastasopoulos warns that “replacing bureaucrats with AI has the potential to erode democratic legitimacy and decrease the extent to which people not only perceive the legitimacy of the system but also actually receive fair outcomes.” This concern is rooted in his broader claim that algorithmic governance does not merely automate decisions; it subtly transforms the normative foundations of administration itself. Because AI systems rely on “data from the past and on statistical averages,” whereas human officials can apply individualized judgment, the shift toward automation risks creating what he calls “automated majoritarianism,” in which average cases are processed efficiently while minorities and outliers are systematically disadvantaged.
At the same time, Assoc. Prof. Anastasopoulos highlights the political implications of AI beyond democratic administration, particularly in relation to populism and authoritarianism. Against the widespread belief that AI necessarily strengthens authoritarian rule, he emphasizes the “autocrat’s calibration dilemma,” showing how false positives and false negatives generate what he terms “threshold whiplash.” Far from ensuring seamless control, AI can create backlash, misclassification, and resistance, even within highly monitored societies. In this respect, the interview complicates dystopian assumptions about authoritarian omniscience by showing how predictive technologies can also destabilize the very regimes that rely on them.
Most strikingly, however, Assoc. Prof. Anastasopoulos suggests that AI may reshape populist politics in new ways. Whereas earlier waves of technological disruption primarily displaced manual and industrial labor, contemporary AI increasingly threatens “intellectual work and highly skilled labor.” This shift, he argues, may transform the social basis of political discontent. Populist mobilization, long rooted in anti-elite appeals to economically dislocated working-class constituencies, may now expand to incorporate professional and knowledge-sector groups who find themselves newly exposed to technological precarity. In that sense, AI may transform populism not only by intensifying backlash against opaque governance, but also by mobilizing constituencies that have not historically stood at the center of populist revolt.
In sum, Assoc. Prof. Anastasopoulos’s reflections offer a sophisticated intervention into contemporary debates on AI and politics. His analysis underscores that AI is neither politically neutral nor institutionally self-executing. Rather, it is a force that can unsettle democratic legitimacy, complicate authoritarian control, and reconfigure the social terrain of populist mobilization. Far from being merely a tool of efficiency, AI may become a catalyst for profound political realignment.
Here is the edited version of our interview with Associate Professor Jason Anastasopoulos, revised slightly to improve clarity and flow.
AI Doesn’t Simply Strengthen Authoritarian Control
AI generative technology, big data, globalization, and analytics management concepts. Photo: Dreamstime.
Professor Anastasopoulos, welcome. In “The Limits of Authoritarian AI,” you introduce the “autocrat’s calibration dilemma,” where predictive systems must tradeoff between false positives and false negatives. How does this structural constraint reshape prevailing assumptions that AI inherently strengthens authoritarian control?
Assoc. Prof. Jason Anastasopoulos: That’s a really good question. I think the common conception of AI is that it will strengthen authoritarian control in a linear fashion, and this makes sense to a certain extent. It is also true in the short run. One of the recurring themes in dystopian narratives is the emergence of a surveillance state in which authoritarian governments exert control over their populations through cameras, social credit systems, and similar technologies. To some extent, this does seem to be the case in the short term. In the long run, however, the use of AI is much more complicated.
This is because of the errors that it generates—namely, Type 1 and Type 2 errors. For readers who may not be familiar with these concepts, they refer to false positives and false negatives, respectively, and are commonly introduced in basic statistics. A Type 1 error occurs when someone is incorrectly identified as a positive case—for example, when a COVID test indicates that a person has the virus when they do not. A Type 2 error, by contrast, occurs when the test indicates that someone does not have the virus when they actually do.
All AI systems, as fundamentally predictive systems, operate under these same constraints. They can misclassify individuals—identifying someone as a threat to the regime when they are not or failing to identify someone who actually poses a risk. These errors carry political consequences, and managing those consequences becomes an inherent challenge for authoritarian regimes. Each type of error entails distinct political trade-offs, which I would be happy to elaborate on further.
Authoritarian Regimes Risk ‘Threshold Whiplash’ When Using AI for Control
Building on this dilemma, to what extent does the probabilistic nature of AI undermine the aspiration of authoritarian regimes to achieve total informational dominance and preemptive repression?
Assoc. Prof. Jason Anastasopoulos: This is where the political consequences of Type 1 and Type 2 errors come into play. This is where authoritarian regimes run into resistance when using AI in the long run, as opposed to the short run. In the short run, these tools are indeed tremendous for monitoring populations. Facial recognition systems can be linked to databases that identify people instantaneously. In China, for example, a social credit system is being developed that could potentially track movements and shape behaviors in ways consistent with regime preferences. But in the long run, the calibration dilemma that autocrats face becomes decisive.
This is something authoritarian regimes actually institutionalize. In China, bureaucracies exist to calibrate AI systems for these kinds of Type 1 and Type 2 errors. Let me outline the political issues that arise from these errors. For Type 1 errors, the biggest problem in an authoritarian context—where a leader is trying to predict who is risky—is that individuals are labeled as threats when they are not. When too many false positives are generated, opposition to the regime itself increases. In other words, you might have 100 individuals who are genuinely threatening, and the AI system identifies them—but it also identifies 100,000 others who are not. Those individuals, ironically, may become threats precisely because they are falsely labeled as such.
So, because of false positives, the regime creates more threats than it would have had otherwise. Authoritarian rule depends on a belief that compliance leads to tolerable outcomes—being left alone, not punished, not having one’s mobility restricted. Type 1 errors undermine this expectation, producing backlash and fueling social movements.
We have seen this in cases such as Zero-COVID policies and the Henan bank protests, which we discuss in the paper. Individuals were falsely labeled as COVID-positive to prevent them from protesting a banking scandal. This generated public outrage and forced the government to scale back. In other words, the use of AI produced the very instability it was meant to prevent.
For Type 2 errors, the problem is reversed. The regime faces real threats, and if AI systems fail to detect them, those threats can operate in the shadows. This dynamic produces what we call a cycle of “threshold whiplash.” Initially, regimes set thresholds low to maintain tight control, which increases Type 1 errors and triggers backlash. In response, they raise the threshold, which increases Type 2 errors, allowing real threats to go undetected.
At the same time, individuals alienated by false labeling may become politically active and organize against the regime. In this way, AI generates a cycle in which efforts at control inadvertently produce the very resistance the regime seeks to suppress.
Authoritarian Incentives to Report Stability Degrade AI from Within
Artificial intelligence as a next-generation technology shaping the digital era. Photo: Dreamstime.
Your work suggests that prediction systems are not merely technical tools, but political instruments embedded in institutional incentives. How do bureaucratic and party-level incentives distort AI outputs in authoritarian settings?
Assoc. Prof. Jason Anastasopoulos: That’s a really good question. The focus here is primarily on China, where regional bureaucratic leaders have incentives to report stability metrics to Beijing. There is a strong desire for Beijing to see that, across all regions within China, things are looking good—that conditions are stable.
What happens with AI systems, then, is that officials tend to downplay any activity identified by these systems that might suggest instability in a region. As a result, when such distorted data is fed into the new AI systems being developed, it creates a significant gap between on-the-ground realities and what the AI system reports, ultimately degrading the quality of the system itself. In this way, bureaucratic incentives to report stability end up undermining AI performance over time, as these systems are trained on data that is simply of low quality.
AI Decision-Making Can Erode Both Perceived and Actual Fairness
In your research on democratic administration, you argue that replacing human discretion with AI risks eroding accountability and reason-giving. How should we theorize the relationship between algorithmic governance and democratic legitimacy?
Assoc. Prof. Jason Anastasopoulos: One of my papers on the problem of replacing bureaucratic discretion with AI identifies a recent trend in many places; some of it is aspirational, and some of it has actually been implemented. The trend is that many regimes, not just authoritarian regimes but democratic countries as well, are seeking to replace bureaucratic discretion, and bureaucrats more generally, with AI systems.
For example, Keir Starmer is one of the figures who is very interested in doing so in the UK. Widodo in Indonesia has actually replaced a few levels of the bureaucracy with AI systems. One of the problems that the paper identifies is that when you replace bureaucratic discretion with AI systems, you remove some of the important safeguards that exist for democratic governance.
Specifically, AI systems have this issue where they do not think like human beings—that is the fundamental problem. Democratic legitimacy, in many ways, is based on the idea that another human being will review your case and be able to reason through whatever decision needs to be made by the state in your particular situation. What I argue in that paper is that there are certain types of decisions—decisions relating to rights, and decisions involving very important issues where someone’s rights could be taken away—that should not be delegated to automated systems. This is because the idea of justice and democracy itself depends on a human being assessing your case at an individual level and applying human judgment in a way that would be deemed fair both theoretically, from a philosophical perspective, and in terms of the perceptions of those being judged.
So, a lot of it comes down to the fact that replacing bureaucrats with AI has the potential to erode democratic legitimacy and decrease the extent to which people not only perceive the legitimacy of the system but also actually receive fair outcomes.
Another problem I identify in that paper is a technical one. I have training in machine learning and statistics, as well as in political philosophy, and I try to understand how these systems work and what their technical implications are. One of the problems with AI, and with any prediction system, is that it does a very good job of assessing the average case, but a very poor job of assessing cases that would be considered edge cases. If the circumstances that a person brings to an AI system are very unusual, the system is not going to be able to provide a good prediction.
As a result, you have what I call automated majoritarianism, where the AI system performs well for most people, but for minority groups and for individuals whose cases fall outside the norm, it performs very poorly. This can ultimately alienate a large segment of the population. These are some of the key issues I identify regarding the risks of replacing bureaucratic discretion with AI.
AI facial recognition in a crowded urban setting, highlighting risks to privacy and personal freedom (AI-generated). Photo: Irina Yeryom / Dreamstime.
If democratic governance depends on individualized judgment and justification, can AI ever be reconciled with these normative commitments, or does it fundamentally reconfigure the meaning of administrative fairness?
Assoc. Prof. Jason Anastasopoulos: I think it actually does end up fundamentally reconfiguring the meaning of administrative fairness, and it does so in a way that is subtle and not very obvious. A lot of it, again, comes down to how AI systems make decisions versus how humans make decisions.
Humans make decisions based on their experience and their adherence to norms that are either embedded in institutions or exist in society. Whereas AI systems simply make decisions based on data from the past and on statistical averages. So, with a human being, you get an individualized decision, whereas with an AI system, you get a decision based on aggregate data.
That has implications for the future of administrative fairness, because the types of decisions made by AI systems, given how they function, are fundamentally different from those made by humans. How those decisions differ will depend on the circumstances to a certain extent. But we have already seen, for example, in cases from the criminal justice system, that AI systems, when they try to predict whether someone is likely to be a recidivist, can produce problematic outcomes. There is a system called the COMPAS.
This is not really an AI system per se; it is more of a machine learning algorithm, although most AI systems are based on machine learning to some extent. What the COMPAS system does is to make predictions about who would be considered at high risk of recidivism in the future. Imagine someone is arrested, their data is collected, and it is fed into this algorithm. The algorithm then predicts whether that person is risky, on a scale from 1 to 10, and this affects how they are treated within the criminal justice system. If they are predicted to be high risk, they may receive a harsher sentence and be treated more punitively; if they are predicted to be low risk, they are more likely to receive leniency.
What some authors at ProPublica found in a 2016 study was that these systems generated a much higher false positive rate for African American offenders compared to white offenders. In other words, they predicted that Black offenders were more likely to be a future risk even when they were not. This is what the well-known ProPublica article “Machine Bias”demonstrated.
In that case, it showed that AI systems can perpetuate biases into the future. They can create a situation where past discrimination becomes embedded in the criminal justice system, and once that happens, it is much more difficult to correct than with human decision-makers. With humans, you can intervene more directly—you can audit decisions or remove individuals—but with AI systems, you would have to change the entire system, including vendors and underlying models, which is far more complex.
So, these are some of the ways in which AI can reshape our understanding of administrative fairness. We will need to develop systems to audit AI in order to prevent bias, and we will have to continually ensure that these systems do not embed biases that could create long-term unfair outcomes for minority groups and others whose lives are affected by AI-driven decisions.
AI Should Inform Decisions, but Humans Must Remain in the Loop
You propose a “centaur model” where AI complements rather than replaces human decision-makers. What institutional safeguards are necessary to prevent this hybrid model from drifting toward de facto automation and accountability erosion?
Assoc. Prof. Jason Anastasopoulos: The idea behind the Centaur model is pretty simple. We need to ensure that when really important decisions are being made within government—decisions that can affect people’s lives and relate to issues of fairness or justice—there is always a human decision-maker in the loop. An AI system can be good at making predictions, but it should only be used as one piece of information within a broader file that a human decision-maker can draw upon.
The problem with this kind of Centaur model, however, is that it runs up against the incentives many governments have to cut costs. This is especially true at the state and local levels in the United States, and also for lower-level governments in Europe and elsewhere, where there are strong incentives to automate decisions.
What may ultimately prevent the Centaur model from being implemented—even though I think it is a good model—is the political economy of governance. A system that combines human judgment with AI could produce decisions that are both fairer and more just than those made by humans alone, who have biases, or by AI systems alone, which come with their own set of problems.
But these advantages may be outweighed by structural pressures. If there is insufficient tax revenue, sustained pressure to cut costs, and a broader cultural disposition—especially in the United States—that views bureaucrats as unnecessary or ineffective, then populist demands to reduce administrative capacity may lead to full automation. In such a scenario, the Centaur model would not take hold.
Instead, you could end up with layers of bureaucracy fully delegated to AI, which introduces its own risks. In that sense, the key issue is public pressure to shrink bureaucracies—something we have seen in various reform movements—combined with governments’ ongoing efforts to reduce costs. Together, these dynamics can push systems toward automated governance rather than hybrid models, and that is something people need to be aware of.
Addressing this requires a broader cultural shift. People need to understand that bureaucrats are not simply obstacles—such as those encountered at the Department of Motor Vehicles—but are integral to ensuring fairness and accountability in governance. Without that shift, we risk moving toward fully automated systems that may replicate the flaws of bureaucracies while simply making decisions faster, not better. That is the main concern I have.
AI Can Centralize Power by Aligning Decisions More Closely with Political Leaders
Three high-definition video surveillance cameras operated by the city police. Photo: Dreamstime.
Your work on delegation highlights how authority is structured through constraints and discretion. How does the delegation of decision-making authority to AI systems alter classic principal–agent problems in democratic governance?
Assoc. Prof. Jason Anastasopoulos: That’s a really good question. The way in which the delegation of authority to AI systems alters the classical problem is the following. The traditional principal–agent problem between bureaucracies and higher levels of authority is that, say in the United States, Congress wants a law passed. They pass the law and then expect it to be implemented in a way that is consistent with their intentions.
However, members of Congress and other elected leaders often lack the expertise required to implement laws themselves. For example, in the case of environmental legislation, they do not have the technical knowledge to determine how regulations should be applied in practice. As a result, they delegate this authority to expert bureaucrats, such as those in the EPA, who are responsible for implementation. The principal–agent problem arises because bureaucrats may have preferences that differ from those of elected leaders, meaning that delegation can produce outcomes that do not fully align with the preferences of those who delegated the authority.
In theory, AI could mitigate this problem. Elected leaders could design and select AI systems that align more closely with their own preferences, whether ideological or pragmatic. From the perspective of higher-level officials, AI systems can therefore be appealing, as they may replace bureaucrats who exercise independent discretion and might make decisions that leaders do not favor.
However, I think this is problematic from the public’s perspective. It leads to greater centralization of power and reduces discretion at the ground level. Bureaucrats often possess forms of expertise that elected leaders simply do not have and replacing that expertise with AI systems could introduce significant risks. Laws might not be implemented correctly, and outcomes might reflect not the interests of the public, but rather the preferences of elected leaders—or even the interests of the vendors who design the AI systems. This is where a new kind of principal–agent problem can emerge.
Perceived Unfair AI Decisions Can Fuel Populist Backlash
In the context of populism, how might the increasing use of AI in governance deepen representation gaps, particularly if citizens perceive decisions as opaque, impersonal, or technocratically imposed?
Assoc. Prof. Jason Anastasopoulos: I think that’s a real problem, and much of it comes down to the idea of backlash that I discuss in my paper on “The Limits of Authoritarian AI” with my co-author, Jason Lian.
If people perceive that AI systems are making decisions that are unfair, the resentment and backlash this generates can fuel an increase in populist movements and a desire to remove those who rely on AI systems but are not populists. That is one key risk I see emerging.
AI can certainly increase support for populist leaders. Such leaders are often somewhat anti-technology and frequently campaign on anti-technology platforms. If AI-based decisions generate sufficient backlash, this can provide them with powerful political fuel. In that context, we could see a sharp rise in support for populist leaders as a means of rolling back the system to a time before AI systems were producing decisions perceived as unfair.
Technological Displacement Expands the Social Base of Populism
Senior male manager addressing workers in open plan office. Photo: Monkey Business Images / Dreamstime.
Your research on technological change and populism suggests that economic disruption can fuel political discontent. How might AI-driven labor displacement interact with democratic backsliding and the rise of populist movements?
Assoc. Prof. Jason Anastasopoulos: There’s a lot of research on this, which finds that populists often draw on the idea that technology—especially automation—will replace people and take their jobs away. This is something we’ve seen since in the beginning of the Industrial Revolution. The Luddites in England were, of course, a well-known populist movement that relied on an anti-technology stance.
The Luddite movement emerged in response to the invention of the steam engine, which displaced large amounts of guild labor in textile production. Whenever there is labor displacement due to technological change, there is almost certainly backlash from those who are unemployed or otherwise disaffected by these new automation systems.
In that sense, AI is no different. It gives populist leaders something to point to, allowing them to claim that they will provide solutions to AI-driven displacement. But in practice, when they are elected, they often fail to deliver those solutions. Instead, they may cooperate with those who develop AI systems and even promote their expansion.
Nevertheless, this remains a powerful and enduring populist position. Historically, populist leaders promise to address the consequences of technological change, yet technological progress continues regardless. Still, their ability to mobilize those affected by labor displacement is likely to grow as more jobs are disrupted.
What is particularly interesting about AI, compared to earlier technologies like the steam engine, is that it is displacing not only manual labor but also intellectual work and highly skilled labor. As a result, the nature of populist and social movements may evolve, as populists begin to incorporate these groups into their constituencies rather than focusing primarily on the working class. This could become an important new dimension of populist politics moving forward.
Distrust of Bureaucracy Could Enable ‘Algorithmic Populism’
To what extent does AI governance risk creating a new form of “algorithmic populism,” where political actors leverage automated systems to claim efficiency while obscuring responsibility?
Assoc. Prof. Jason Anastasopoulos: That’s exactly the problem I identified before. Could you explain what you mean by algorithmic populism more specifically? Political leaders or actors leveraging automated systems to claim efficiency while obscuring responsibility.
That’s the general problem with AI. It’s one of the key tensions. I’m not entirely sure about the idea of algorithmic populism in general, but one condition that could give rise to it is, especially in cultures like the United States where there is a deep distrust of bureaucracies, a situation in which AI systems are perceived as being better than human bureaucrats.
In those cases, it would be easy for a political actor—an “algorithmic populist,” as you put it—to accelerate the replacement of bureaucrats with AI in government, which would again lead to many of the problems I discussed earlier. And some figures—Donald Trump, for example, who could be considered a populist—might even be seen as algorithmic populists to a certain extent, in that they promote technology and advance a strong AI agenda.
In such situations, you create a scenario where you end up with the same problems associated with AI that I mentioned earlier, but the process continues to advance. I don’t know exactly what the future would look like in terms of how an algorithmic populist movement might develop, but it is an interesting idea to consider.
Data Quality Will Determine Whether AI Supports Democracy or Control
Photo: Shutterstock
And lastly, Professor Anastasopoulos, looking ahead, do you see AI as ultimately stabilizing or destabilizing democratic systems—and what key variables will determine whether it becomes a tool of democratic renewal or authoritarian entrenchment?
Assoc. Prof. Jason Anastasopoulos: I’m actually pretty hopeful about AI and its effect on democracy. I think it’s going to have two effects in general: one within democratic systems and the other within authoritarian systems.
I think a lot of it comes down to data quality. In democratic systems, AI can do a very good job of helping decision-makers make fairer, more just, and more efficient decisions. That’s because, within democratic systems, the information fed into AI systems comes from a range of democratic processes—deliberation, free speech, and so on. As a result, the quality of AI systems is very high when they are used to further democratic principles and support democratic rule.
However, in authoritarian systems—and this is something I discuss in “The Limits of Authoritarian AI”—authoritarian regimes seek to use AI to control their populations. The fundamental problem they encounter is one of information. This problem relates directly to the fact that when people are being monitored, they change their behavior and hide their preferences. As a result, the information that feeds into AI systems ends up being of much lower quality in authoritarian regimes than in democratic ones. I believe this tends to further destabilize authoritarian regimes as they attempt to tighten control through AI systems and encounter the kind of threshold whiplash I mentioned earlier. Over time, authoritarian regimes may come to realize that AI tools are not the panacea they may have expected. That realization could open the door for social democratic movements within authoritarian regimes to take advantage of the instability created by AI.
In sum, for democratic nations, as long as we avoid a situation in which we eliminate all layers of government and replace them with AI, it can be a stabilizing force. In contrast, in authoritarian regimes, it is likely to be destabilizing—at least temporarily—and may eventually push those systems toward greater democratization if they continue to rely on AI. They might, of course, decide to abandon AI systems and revert to older forms of authoritarian control, but I don’t think that is very feasible in the modern world. Instead, what we may see is a gradual broadening of democracy globally as AI systems are adopted for different purposes.
Please cite as: ECPS Staff. (2026). “Virtual Workshop Series / Session 14 — From Bots to Ballots: AI, Populism, and the Future of Democratic Participation.” European Center for Populism Studies (ECPS). March 24, 2026. https://doi.org/10.55271/rp00145
Session 14 of the ECPS Virtual Workshop Series examined how artificial intelligence, algorithmic infrastructures, and digital platforms are reshaping democratic participation in the contemporary era. Bringing together perspectives from political science, communication, cultural heritage, and democratic theory, the panel explored the implications of AI for political legitimacy, collective identity, and the future of “the people” in an increasingly post-digital world. Contributions ranged from public attitudes toward algorithmic governance and the role of ChatGPT in shaping cultural memory to Big Tech’s influence on class consciousness and the fragmentation of digital publics. Together, the presentations and discussions showed that AI is no longer external to democracy, but increasingly constitutive of its communicative, institutional, and symbolic foundations—raising urgent questions about power, accountability, and democratic contestation.
Reported by ECPS Staff
On Thursday, March 19, 2026, the European Center for Populism Studies (ECPS) convened the fourteenth session of its Virtual Workshop Series, “We, the People” and the Future of Democracy: Interdisciplinary Approaches, under the title “From Bots to Ballots: AI, Populism, and the Future of Democratic Participation.” Bringing together scholars from political science, communication studies, democratic theory, cultural heritage, and digital governance, the session examined one of the most urgent questions of contemporary political life: how artificial intelligence, algorithmic infrastructures, and platform logics are transforming democratic participation, political legitimacy, and the very conditions under which “the people” are constituted. From public attitudes toward algorithmic decision-making and the cultural politics of generative AI to the restructuring of class consciousness and the fragmentation of digital publics, the panel explored the shifting contours of democracy in an increasingly post-digital age.
The participants of the session were introduced by ECPS intern Stella Schade. Chairing the panel, Dr. Paolo Gerbaudo of the Complutense University of Madrid situated the discussion within a broader reflection on the transformation of democracy in the contemporary technological era. As he underscored, democracy has always been shaped by mediations—whether institutional, communicative, or technological—but what distinguishes the present moment is the centrality of digital infrastructures as key mediating forces in the organization of visibility, participation, and power. Algorithms, artificial intelligence systems, and platform architectures, he suggested, have become decisive “bottlenecks” through which political communication and democratic agency are increasingly filtered. In this sense, the session was framed not merely as a discussion of technology, but as an inquiry into the changing nature of democratic life itself.
Under Dr. Gerbaudo’s chairmanship, the panel featured four presentations that illuminated distinct yet interconnected dimensions of this transformation. Presenting a co-authored paper on behalf of his co-authors, Professor Joan Font (IESA-CSIC) examined citizens’ conceptions of democracy in the context of artificial intelligence in public administration and governance, asking who, if anyone, would want an algorithm to govern. Alonso Escamilla (The Catholic University of Ávila), co-authoring with Paula Gonzalo (University of Salamanca), explored how ChatGPT may shape European cultural heritage and its implications for the future of democracy. Aly Hill (University of Utah) turned to the United States to analyze how Big Tech is reshaping white working-class consciousness and reconfiguring populist narratives. Finally, Amina Vatreš (University of Sarajevo) offered a theoretical intervention on “the people” in an algorithmically mediated world, focusing on the interplay between filter bubbles, filter clashes, and populist identity formation.
The session also benefited from the incisive engagement of its discussants, Dr. Jasmin Hasanović (University of Sarajevo) and Dr. Alparslan Akkuş (University of Tübingen). Their interventions not only deepened the theoretical stakes of the presentations but also connected them to wider debates on political legitimacy, technological power, digital capitalism, and democratic fragmentation.
Together, chair, speakers, and discussants produced a rich interdisciplinary exchange that highlighted both the promise and the peril of AI-mediated politics. Session 14 thus offered a compelling inquiry into how democracy is being rearticulated in a world where digital systems no longer merely support political life, but increasingly structure its possibilities.
Democracy, Mediation, and Digital Power
Dr. Paolo Gerbaudo is a sociologist and political theorist at Department of Political Science and Administration and senior researcher in Social Science at Complutense University in Madrid and lead researcher for the After Order project at Alameda Institute.
In his introductory remarks, Dr. Paolo Gerbaudo situates the discussion within his broader scholarly engagement with the transformation of democracy in the contemporary technological era. His intervention underscores the growing entanglement between democratic malaise, the rise of populist movements, and the evolving infrastructures of mediation that shape political life.
Dr. Gerbaudo foregrounds a fundamental paradox at the heart of democratic theory: the tension between the ideal of democracy as the unmediated expression of the popular will and the empirical reality of complex, layered mediations. Drawing implicitly on classical conceptions of direct democracy, he contrasts the normative aspiration for transparency and immediacy with the institutional and technological filters through which political power is necessarily exercised. In this sense, democracy is never purely direct but always structured through channels that organize participation, authority, and legitimacy.
Extending this argument, Dr. Gerbaudo emphasizes that mediation is not a recent development but a constitutive feature of democratic systems across history—from ancient Athens to modern representative regimes. However, what distinguishes the present moment is the centrality of digital technologies as key mediating forces. Algorithms, artificial intelligence, and platform architectures increasingly function as “bottlenecks” and “pivot points,” shaping the distribution of visibility, influence, and ultimately political power.
Crucially, he highlights the hybrid nature of these processes, where human agency and technological systems interact in complex ways. This interplay produces new configurations of power that challenge traditional understandings of democratic participation and representation. By framing the session around these dynamics, Dr. Gerbaudo positions the subsequent presentations as contributions to a broader inquiry into the opportunities and limits of digital democracy in contemporary societies.
Professor Joan Font: “Conceptions of Democracy and Artificial Intelligence in Administration and Government: Who Wants an Algorithm to Govern Us?”
Joan Font is research professor at the Institute of Advanced Social Studies (IESA-CSIC).
In his presentation, Professor Joan Font offers a rigorous empirical examination of public attitudes toward the role of artificial intelligence (AI) in democratic governance. His intervention is situated within the broader framework of the AutoDemo project, a collaborative research initiative aimed at exploring citizens’ preferences regarding democratic procedures and decision-making models in contemporary societies.
Professor Font begins by positioning AI as a critical new dimension in longstanding debates about “which kind of democracy we want.” Rather than treating AI as a purely technical innovation, he integrates it into a normative and empirical inquiry into democratic legitimacy, participation, and authority. The rapid diffusion of AI technologies—particularly within public administration—raises fundamental questions about transparency, accountability, and the locus of decision-making power. Yet, as he notes, systematic knowledge of citizens’ perceptions and preferences in this domain remains limited and fragmented.
To address this gap, the AutoDemo project conducted a large-scale survey of approximately 3,000 respondents in Spain, capturing attitudes toward AI in general, as well as its potential applications in public administration and government. A key contribution of the study lies in its differentiation between varying levels of AI involvement—from low-stakes administrative assistance to high-stakes political decision-making. This nuanced approach allows the authors to move beyond binary or dystopian framings of AI governance and instead map gradations of public support.
The descriptive findings reveal a clear and consistent pattern: respondents are broadly supportive of AI when it is confined to routine administrative tasks, such as improving efficiency or processing information. However, this support declines significantly as AI is envisioned as playing a more direct role in political decision-making. The lowest levels of acceptance are observed in scenarios where AI would oversee or conduct electoral processes, indicating persistent concerns about legitimacy and democratic control. These findings align with comparable studies conducted in other European contexts, suggesting a degree of cross-national consistency.
Moving beyond descriptive analysis, Professor Font employs multivariate regression techniques to identify the key drivers of these attitudes. The results indicate that general attitudes toward AI—such as trust in technology or perceived benefits—constitute the most powerful explanatory factor. In comparison, democratic preferences and broader political attitudes play a more conditional role. Notably, their influence becomes more pronounced in relation to higher levels of AI authority. Individuals with more authoritarian orientations are significantly more likely to support an expanded role for AI in political decision-making, whereas those who favor representative democratic models tend to express greater skepticism.
This stratification underscores a crucial insight: support for AI governance is not merely a function of technological optimism, but is also shaped by underlying normative commitments regarding how democracy should function. In this sense, AI becomes a lens through which broader tensions between competing models of democracy—technocratic, representative, participatory, and authoritarian—are refracted.
Professor Font concludes by emphasizing both the empirical and normative implications of these findings. While AI is not yet a central issue in electoral politics, its growing presence in governance raises the possibility that it may become politically salient in the near future. As such, the question of how citizens perceive and evaluate AI’s role in decision-making warrants sustained scholarly and policy attention. By embedding AI within the broader debate on democratic preferences, the presentation offers a valuable contribution to understanding the evolving relationship between technology and democracy in the digital age.
Alonso Escamilla: “How Does ChatGPT Shape European Cultural Heritage for the Future of Democracy?”
Alonso Escamilla is Manager of European Projects and Research at the Catholic University of Ávila (Spain). For this same institution, he is a PhD Student on Cultural Heritage and Digitalisation and a Member of the Research Group: Territory, History and Digital Cultural Heritage.
In his presentation at Session 14 of the ECPS Virtual Workshop Series, Alonso Escamilla advances an original and exploratory inquiry into the relationship between artificial intelligence, European cultural heritage, and the future of democracy. His paper situates itself at the intersection of political theory, cultural studies, and digital governance, offering a conceptually rich and methodologically innovative contribution to ongoing debates on the democratic implications of generative AI.
Escamilla begins by establishing a conceptual foundation that links European cultural heritage and democracy through a shared normative architecture. Drawing on UNESCO’s definition, he frames cultural heritage as the legacy of tangible and intangible assets transmitted across generations and preserved for collective benefit. This definition is subsequently expanded through the lens of the European Union, where cultural heritage is understood not only as a repository of memory but also as a strategic resource underpinning economic development, social cohesion, territorial competitiveness, and the consolidation of European values. Democracy, in parallel, is conceptualized as a system grounded in rights, rule of law, and representative institutions, through which citizens’ dignity and public reason are institutionalized.
A key analytical move in Escamilla’s framework is the recognition of cultural heritage as a polysemic concept—simultaneously functioning as identity, memory, symbol, and political resource. This multiplicity, he argues, renders cultural heritage both a site of democratic possibility and a terrain of contestation. In the context of the European Union, where shared identity is continuously negotiated, cultural heritage becomes central to the construction and reproduction of democratic legitimacy.
This conceptual discussion is embedded within a broader historical and geopolitical context. Escamilla highlights a series of crises that have shaped the European project over the past two decades—including the 2008 financial crisis, the 2015 migration crisis, the COVID-19 pandemic, and the ongoing war in Ukraine—arguing that these events have placed significant strain on both democratic institutions and cultural narratives. To these pressures is added the accelerating impact of digitalization and artificial intelligence, which introduces new uncertainties regarding the mediation of knowledge, identity, and political participation.
Against this backdrop, Escamilla formulates his central research question: how does ChatGPT conceptualize the role of artificial intelligence in shaping European cultural heritage for the future of democracy? Methodologically, the study adopts an innovative design, treating ChatGPT not merely as a tool but as an object of inquiry. A set of 30 open-ended questions is administered across three levels of complexity—basic, intermediate, and expert—each designed to elicit distinct layers of conceptualization. By structuring the interaction in this way and isolating each level within separate conversational contexts, the study seeks to capture variations in discourse while minimizing contextual bias.
The resulting dataset is subjected to qualitative content analysis, involving thematic coding, identification of discursive patterns, and mapping of conceptual relationships. This approach allows Escamilla to reconstruct the “narrative logic” through which ChatGPT articulates the interplay between cultural heritage, democracy, and artificial intelligence.
The findings reveal a clear stratification in the model’s responses. At the basic level, ChatGPT adopts a pedagogical and normative tone, presenting European cultural heritage as a shared historical legacy, linking it to civic participation, and defining democracy primarily in terms of human rights and the rule of law. These responses reflect dominant institutional discourses, closely aligned with EU policy frameworks and UNESCO definitions.
At the intermediate level, the model’s discourse becomes more analytical and reflexive. Cultural heritage is framed as a resource for critical thinking and democratic literacy, as well as a space—both physical and digital—where citizens negotiate meanings and engage in dialogue. Importantly, ChatGPT begins to conceptualize heritage as dynamic, capable of responding to contemporary challenges and facilitating democratic resilience.
At the expert level, a more critical and ambivalent perspective emerges. Here, ChatGPT articulates both the opportunities and risks associated with AI. On the one hand, AI is portrayed as a powerful tool for enhancing accessibility, inclusivity, and preservation, enabling new forms of cultural production and engagement. On the other hand, significant risks are identified: the privileging of dominant narratives, the reproduction of existing power hierarchies, and the potential for AI to shape—if not determine—how heritage is accessed, interpreted, and transmitted.
One of the most intriguing aspects of the findings is the model’s “performative adaptability.” Escamilla observes that ChatGPT appears to adopt different epistemic identities depending on the level of questioning—ranging from a pedagogical voice at the basic level to a quasi-expert authority at the highest level. This suggests not only responsiveness to input complexity but also an embedded capacity to simulate varying degrees of expertise, raising important questions about epistemic authority in AI-mediated knowledge production.
In the discussion, Escamilla situates these findings within existing literature on cultural heritage policy and digital governance. He notes that the model’s outputs largely reproduce dominant European narratives, reflecting the influence of institutional discourse embedded within training data. While this lends coherence and legitimacy to the responses, it also points to a limitation: alternative or marginalized conceptions of cultural heritage may be underrepresented or excluded.
The analysis of future-oriented responses further underscores the ambivalent role of AI. While its capacity to democratize access and foster inclusion is acknowledged, its potential to distort public discourse, manipulate information, and reshape collective memory raises significant concerns. In particular, the prospect that AI systems might influence not only how heritage is disseminated but also what is deemed worthy of preservation introduces a profound challenge to democratic governance.
Escamilla concludes by emphasizing the bidirectional and evolving relationship between artificial intelligence, cultural heritage, and democracy. AI is not merely a neutral intermediary but an active agent in the production, selection, and transmission of cultural meaning. As such, its growing influence necessitates sustained scholarly attention and critical engagement.
Ultimately, the presentation highlights a central tension: whether artificial intelligence will serve as a tool that enhances democratic participation and cultural pluralism, or as a force that centralizes interpretive authority and constrains diversity. By foregrounding this question, Escamilla’s work contributes significantly to emerging debates on the governance of digital knowledge infrastructures and their implications for democratic futures.
Aly Hill: “The New Elite: How Big Tech is Reshaping White Working-Class Consciousness.”
Aly Hill is a third-year Ph.D. candidate in the Department of Communication at The University of Utah.
In her presentation, Aly Hill offers a conceptually incisive examination of the evolving relationship between technological governance, populism, and class politics in the contemporary United States. Positioned as a “human-centered” complement to more system-oriented analyses of digital democracy, Hill’s intervention foregrounds the lived and political consequences of technocratic restructuring, particularly as it intersects with the transformation of populist narratives and white working-class consciousness.
Hill’s analysis is anchored in the political developments surrounding the second administration of Donald Trump, with particular attention to the institutional and ideological implications of the Department of Government Efficiency (DOGE), an initiative associated with the prominent tech entrepreneur Elon Musk. Through this lens, the presentation examines how the increasing alignment between big tech and right-wing political power is reshaping not only governance practices but also the symbolic and material foundations of populist politics.
The presentation begins by situating this shift within a broader historical trajectory of relations between political power and the technology sector. Hill notes that while the contemporary alignment of major technology firms with conservative political actors may appear novel, it is better understood as a function of structural economic incentives rather than ideological realignment. In earlier periods, particularly during the 2000s and early 2010s, big tech was closely associated with liberal, innovation-driven narratives that emphasized democratization, participation, and disruption of traditional power centers. However, as these firms have consolidated economic and infrastructural dominance, their political positioning has increasingly aligned with agendas favoring deregulation, tax reduction, and the minimization of state constraints—policies more closely associated with conservative governance.
This transformation is interpreted not as a departure from prior commitments but as a logical extension of capital-driven interests. Hill highlights how the regulatory environment under successive administrations has played a crucial role in this shift. While earlier administrations pursued antitrust measures and regulatory oversight, more recent policy frameworks—particularly under Trump—have offered incentives conducive to technological expansion, including relaxed environmental regulations affecting data infrastructure and reduced corporate constraints. Within this context, the convergence of political and technological power emerges as both strategic and mutually reinforcing.
At the core of Hill’s argument is the question of how this realignment affects populist discourse, particularly its traditional articulation around the dichotomy of “the people” versus “the elite.” To explore this, she draws on three empirical case studies: the mass dismissal of approximately 140,000 federal employees, the attempted administrative takeover of key government agencies by DOGE, and the deployment of mass communication systems to monitor and manage federal labor. While these cases vary in scope and implementation, they collectively illustrate a broader transformation in the logic of governance.
The first major finding centers on the reconceptualization of governance as an optimization problem rather than a site of political negotiation. Hill argues that the introduction of data-driven managerial frameworks reframes political decision-making in terms of efficiency, performance metrics, and algorithmic calculation. This shift echoes earlier traditions of managerial rationalization, particularly Taylorism, but is now reconfigured through digital infrastructures—a phenomenon she identifies as “digital Taylorism.” In this model, complex political questions are reduced to technical challenges, thereby displacing democratic deliberation with procedural optimization.
The second finding concerns the transformation of state communication. Hill observes that governmental interaction with citizens and employees increasingly mirrors the logic of corporate platform management. The use of standardized, impersonal communication—exemplified by mass emails announcing layoffs or monitoring productivity—reflects a shift toward scalable, automated governance. Importantly, this mode of communication is accompanied by an algorithmic logic that seeks to depoliticize conflict. When errors occur—such as wrongful dismissals—the responsibility is often attributed to technical malfunction or systemic inefficiency, rather than to political decision-making. This displacement of accountability obscures the inherently political nature of these processes, reinforcing the perception of neutrality associated with technological systems.
The third and perhaps most consequential finding addresses the redefinition of workers within this emerging framework. Hill argues that efficiency-driven governance increasingly treats workers as system costs rather than as political subjects. This reclassification has profound implications for populist politics, particularly given that many of those affected by these policies belong to the very constituencies that populist movements claim to represent. In this sense, the presentation identifies a growing disjunction between populist rhetoric and policy outcomes. While populism continues to invoke the grievances of the working class, the implementation of technocratic efficiency measures often undermines the material conditions of these same groups.
Hill further highlights the paradoxical status of technocratic actors within this system. Figures such as Elon Musk, initially positioned as central agents of reform, are themselves subject to the logic of disposability. When their actions generate political friction or undermine narrative coherence, they can be rapidly replaced, reinforcing the primacy of system-level efficiency over individual agency. This dynamic underscores the extent to which authority is shifting away from identifiable elites toward more diffuse, technologically mediated structures of power.
In synthesizing these findings, Hill proposes a significant transformation in the structure of populist discourse. The traditional antagonism between “the people” and “the elite” is increasingly supplanted by a more complex and unstable configuration in which technology itself becomes a focal point of contestation. As citizens encounter the material consequences of algorithmic governance—job loss, surveillance, bureaucratic opacity—they may begin to reorient their grievances toward technological systems rather than conventional political actors. This shift suggests the emergence of a “people versus tech” paradigm, in which the locus of power becomes more difficult to identify and contest.
At the same time, Hill remains attentive to the limits of this transformation. Whether citizens will fully recognize the structural interplay between technological systems and political authority remains an open question. The opacity of algorithmic processes, combined with the enduring appeal of populist narratives, may inhibit the development of a coherent critique. Nevertheless, the presentation underscores the importance of rethinking populism in light of these evolving dynamics, particularly as digital infrastructures become increasingly central to governance.
In conclusion, Aly Hill’s presentation offers a compelling and theoretically grounded account of how technological rationality is reshaping the terrain of democratic politics. By linking empirical developments in US governance to broader conceptual debates on populism, class, and digital power, the study provides valuable insights into the future of democratic contestation. It highlights a critical juncture in which the promises of efficiency and innovation are intertwined with new forms of exclusion, dispossession, and depoliticization—raising fundamental questions about the capacity of democratic systems to adapt to, and regulate, the expanding influence of technology.
Amina Vatreš: “Bubbles, Clashes and Populism: ‘The People’ in an Algorithmically Mediated World.”
Amina Vatreš is a teaching assistant at the Department of Communication Studies/Journalism at the University of Sarajevo – Faculty of Political Sciences.
In her presentation, Amina Vatreš develops a theoretically ambitious and conceptually rich account of the relationship between algorithmic mediation and contemporary populism. Her paper is explicitly framed as a theoretical intervention rather than an empirical study. Its primary objective is to clarify how digital platforms, as socio-technical systems, actively shape the conditions under which collective identities are formed, contested, and destabilized.
Vatreš begins from the premise that digital platforms should not be understood as neutral channels of communication. Rather, they are infrastructures that structure what can be seen, said, and believed. In this way, they participate directly in the production of social reality. This perspective enables her to connect platform logics with the formation of subjectivity and, more specifically, with the articulation of political identities within populist frameworks. At stake, therefore, is not simply the circulation of information, but the deeper question of how “the people” are constructed in digitally mediated environments.
To illustrate this argument, Vatreš offers concrete examples drawn from recent political events. She invites the audience to imagine two users following the same anti-government protests in Sarajevo or the same international conflict, but receiving radically different representations of these events depending on their platform use, prior interactions, and digital networks. One user may encounter content emphasizing governmental responsibility and civic mobilization, while another sees narratives that delegitimize protest and defend authorities. In such instances, she argues, the issue is not merely that users are exposed to different opinions; rather, they inhabit different realities. These realities are produced through algorithmic curation systems that rank, prioritize, and amplify content based on previous behavior and predicted engagement.
This observation leads Vatreš to a larger conceptual claim: contemporary politics unfolds within what she describes as a post-digital environment. In such a setting, technology, communication, and social life are no longer separable domains. Algorithms and users exist in a reciprocal relation: users shape algorithms through their interactions, while algorithms simultaneously shape users’ practices, interpretations, and political orientations. This recursive loop is crucial for understanding the contemporary transformation of populism.
Within this framework, Vatreš introduces the concept of post-digital populism. She defines it as a form of populism in which collective identities are co-produced through the ongoing interaction between users and algorithmic systems. Users, through their clicks, searches, and engagements, effectively train the algorithms, and the algorithms in turn reinforce and amplify the preferences, identities, and affective dispositions that informed those behaviors in the first place. This process is not accidental but rooted in the business logic of digital platforms, which optimize for engagement and thus privilege emotionally charged, polarizing, and identity-affirming content.
A central contribution of the presentation lies in her identification of two key mechanisms through which collective identities are reconfigured in post-digital contexts: filter bubbles and filter clashes. Filter bubbles refer to relatively homogeneous informational spaces produced by personalization and recommendation systems. Within them, users are repeatedly exposed to content that confirms preexisting beliefs, while dissonant viewpoints are minimized. According to Vatreš, this repetition serves to stabilize in-group identification. It strengthens a sense of “us” while constructing a corresponding “them,” often in simplified or distorted terms. In this sense, filter bubbles do not merely isolate; they also consolidate identity through the constant reinforcement of familiar narratives.
Yet Vatreš argues that algorithmic mediation does not operate solely through isolation. It also generates confrontation, and this is where the concept of filter clashes becomes analytically important. Filter clashes occur when antagonistic positions collide across algorithmically curated realities. These are not moments of open dialogue or mutual understanding; rather, they are structured encounters in which users move beyond their own informational environments in order to challenge, confront, or discredit opposing views. These clashes are intensified by algorithms because platforms tend to amplify conflictual and emotionally charged content. Thus, digital mediation not only separates publics but also stages their encounters under conditions that privilege antagonism over deliberation.
From a communication studies perspective, Vatreš insists that the core problem is not simply the absence of constructive dialogue. After all, such dialogue is often limited even in offline or analog contexts. The deeper problem concerns which messages reach users, how those messages are framed, and how they provide justification for particular political demands. What emerges is a fragmented communicative space composed of micro-publics, each structured by its own patterns of visibility, affect, and interpretation.
Here Vatreš introduces an important theoretical insight drawn from Ernesto Laclau’s work on populism. She suggests that the fragmentation of digital publics makes it difficult to create broader “chains of equivalence” through which dispersed grievances might be articulated into a coherent collective project. Although algorithmic environments intensify grievances and facilitate their circulation, they do not necessarily enable their stabilization into durable political meanings. Instead, political affect often remains at the level of reactive polarization. What appears as mobilization may in fact be a simulation of politics—an expression of identity without durable articulation or strategic coherence.
This leads to one of the presentation’s most important conclusions: in algorithmically mediated environments, the “people” do not emerge as a stable political subject. Rather, what one finds is a constant process of mobilization without consolidation. Algorithms generate intensity, accelerate circulation, and produce moments of antagonistic visibility, but they do not provide the conditions for lasting unity. In this sense, populism becomes both effective and fragile. It is effective because it fits the logic of algorithmic systems, simplifying complexity into the stark opposition between “the people” and “the elites.” But it is fragile because it operates within an environment that continuously fragments meaning and reconfigures identity.
Vatreš returns to the Sarajevo protests as an example of this dynamic. What began as collective grief after a tragic accident was quickly transformed into a politically charged event mediated through digital platforms. Competing narratives emerged almost immediately, polarizing public discourse and restructuring the meaning of the protests in real time. Social media did not simply reflect social divisions; it actively organized them, creating the conditions under which different versions of “the people” could emerge, clash, and circulate.
In conclusion, Vatreš argues that the key question in a post-digital world is no longer simply who “the people” are, but how “the people” are produced through the interaction of users, platforms, and algorithmic systems. Algorithms sustain antagonism both by enclosing users within bubbles and by exposing them to conflict through clashes. At the same time, they undermine the stabilization of collective meaning by fragmenting publics and intensifying reactive affect. Populism, in this context, appears both as a strategy of articulation and as a symptom of fragmentation.
Her final argument is particularly striking: algorithms do not produce “the people” as a unified and enduring collective subject. Rather, they create the conditions under which “the people” can continuously emerge and just as continuously dissolve. What remains, therefore, is not a stable democratic collectivity but a shifting field of fragmented, algorithmically mediated identities. In this sense, Vatreš’s presentation offers a compelling theoretical framework for understanding the unstable relationship between digital infrastructures, populist articulation, and democratic subject formation in the contemporary political landscape.
Discussants’ Feedback
Feedback by Assist. Prof. Jasmin Hasanović
Dr. Jasmin Hasanović is an Assistant Professor and researcher at the Department for Political Science at the University of Sarajevo – Faculty of Political Science.
In his role as discussant at Session 14 of the ECPS Virtual Workshop Series, Dr. Jasmin Hasanović offers a wide-ranging and theoretically grounded set of reflections that both synthesize and critically interrogate the panel’s contributions. His feedback is marked by a consistent effort to situate the presented papers within a broader conceptual shift—from understanding “the digital” as an external domain to recognizing a fully post-digital condition in which technological systems are deeply embedded in the fabric of everyday social and political life.
Dr. Hasanović opens by commending the panel for collectively demonstrating that digital technologies—particularly platforms, algorithms, and artificial intelligence—can no longer be treated as novel or disruptive add-ons to political analysis. Rather, they constitute an integral and normalized dimension of contemporary social reality. This framing establishes the conceptual foundation of his intervention: that political theory must now grapple with a condition in which the boundaries between the technological and the social have effectively dissolved.
Turning first to the presentation by Professor Joan Font, Dr. Hasanović identifies a central theoretical issue raised by the study: the question of political legitimacy in the age of artificial intelligence. While classical political theory has traditionally conceptualized legitimacy in relation to human actors and institutions, the increasing role of algorithmic systems in decision-making processes necessitates a rethinking of this foundational concept. He praises the paper for innovatively linking attitudes toward AI with broader democratic preferences, thereby demonstrating that technological attitudes cannot be analytically separated from underlying normative conceptions of democracy.
However, Dr. Hasanović also identifies several areas requiring further development. Most notably, he calls for a deeper exploration of the finding that individuals with authoritarian orientations tend to exhibit stronger support for AI in political decision-making. Without a substantive theoretical explanation, he argues, such empirical observations remain descriptively interesting but analytically limited. The critical question—why authoritarian or technocratic predispositions correlate with support for AI—remains insufficiently addressed. This omission is particularly consequential given the normative implications: if support for AI aligns with authoritarian tendencies, then AI cannot be regarded as a neutral instrument but must instead be understood as potentially facilitating depoliticization and the concentration of power.
Relatedly, Dr. Hasanović raises concerns about the implicit conceptualization of AI within the study. He suggests that the analysis risks naturalizing the idea of AI as an autonomous political subject, thereby obscuring the human, institutional, and economic structures that underpin algorithmic systems. This critique redirects attention to the political economy of AI: who designs these systems, under what conditions, and for whose benefit. In doing so, Dr. Hasanović underscores that debates about AI’s role in governance cannot be divorced from questions of power, ownership, and capital.
This line of critique leads him to articulate a broader interpretive framework: the future role of AI in politics is inseparable from the capacity of capitalism to adapt and transform. Technological development, he notes, is driven not only by innovation but also by capital investment and, in many cases, military interests. Thus, the question of whether AI will enhance or undermine democratic governance must be situated within this structural context.
In his engagement with Alonso Escamilla’s presentation, Dr. Hasanović shifts focus to the cultural and epistemic dimensions of artificial intelligence. While acknowledging the methodological ingenuity of interrogating ChatGPT as an analytical subject, he suggests that the study would benefit from a comparative perspective. Specifically, he proposes examining how generative AI models conceptualize different cultural heritages in relation to democracy, rather than focusing exclusively on the European case. Such an approach, he argues, would help reveal potential biases embedded within AI systems.
Here, Dr. Hasanović advances a critical argument concerning the Eurocentrism of generative AI. He emphasizes that the dominant training data for models like ChatGPT are heavily skewed toward Western intellectual and cultural traditions. This asymmetry is further compounded by the global division of labor underlying AI production, where data annotation and content moderation are often outsourced to regions such as Africa and Asia under conditions of economic inequality. By invoking the example of companies such as Sama in Kenya, he highlights the often-invisible labor infrastructures that sustain AI systems.
This critique culminates in a broader theoretical point: AI should not be understood as an autonomous or abstract intelligence, but as a socio-technical product shaped by material conditions, labor relations, and global inequalities. In this regard, Dr. Hasanović invokes a Marxian perspective, emphasizing that technologies are “objectified knowledge” produced through human labor. The data that feed AI systems, he notes, are derived from collective social activity—often voluntarily provided by users through digital platforms—yet appropriated within capitalist frameworks for profit generation.
This political economy perspective also informs his engagement with Aly Hill’s presentation, which he identifies as particularly valuable for “humanizing” the discussion of technology. He expresses interest in the possibility of alternative technological paradigms that move beyond capitalist imperatives. This raises a normative and political question that extends beyond the panel: whether it is possible to imagine forms of technology organized around social benefit, communal ownership, or democratic control, rather than profit maximization.
Dr. Hasanović’s comments on Amina Vatreš’s presentation further deepen his theoretical intervention. He strongly endorses her conceptualization of populism as a discursive practice rather than a fixed ideology, aligning it with post-foundational approaches in political theory. He argues that her analysis convincingly demonstrates how algorithmic systems facilitate the partial construction of antagonistic identities—“us” versus “them”—through mechanisms such as filter bubbles and filter clashes.
At the same time, he highlights a crucial limitation identified in her work: the inability of algorithmically mediated environments to stabilize these antagonisms into coherent political subjects. Drawing on Ernesto Laclau’s theory, Dr. Hasanović emphasizes that the formation of a “people” requires the articulation of diverse demands into a unified chain of equivalence. However, in digital environments characterized by rapid fragmentation and continuous reconfiguration, such stabilization becomes increasingly difficult. As a result, political subjectivities emerge and dissolve in rapid succession, producing a condition of perpetual mobilization without consolidation.
This insight leads Dr. Hasanović to a critical reflection on the limits of contemporary digital activism. While early examples such as Occupy Wall Street or the Arab Spring suggested that social media could serve as tools for political mobilization, recent developments—such as algorithmic suppression or “shadow banning”—indicate that these platforms are no longer neutral arenas for political engagement. Instead, they are governed by opaque logics that users can neither fully understand nor effectively influence.
In light of these constraints, Dr. Hasanović proposes a shift in analytical and political focus: from engagement withintechnology to engagement over technology. Rather than merely adapting to algorithmic systems, he suggests the need for strategies that seek to intervene in, reshape, or even “untrain” these systems. This raises the possibility of a more active and critical form of technological engagement—one that challenges the structures of algorithmic governance rather than passively reproducing them.
In conclusion, Dr. Hasanović’s feedback provides a unifying and critical perspective on the session’s contributions. By foregrounding the post-digital condition, the political economy of technology, and the limits of algorithmically mediated politics, he not only identifies key theoretical tensions but also points toward new avenues for research and political intervention. His remarks underscore the necessity of rethinking core concepts—such as legitimacy, subjectivity, and collective identity—in light of the profound transformations brought about by digital and algorithmic systems.
Feedback by Dr. Alparslan Akkuş
Dr. Alparslan Akkuş is a Teaching Fellow at the Institute of Political Science, Eberhard Karls University Tübingen, Germany.
In his role as discussant, Dr. Alparslan Akkuş offers a reflective and experience-driven intervention that situates the panel’s contributions within a broader historical and technological trajectory. His remarks are characterized by an effort to bridge empirical findings with long-term patterns of technological transformation, emphasizing both the inevitability of artificial intelligence (AI) and its profound implications for political, social, and epistemic structures.
Dr. Akkuş opens his commentary by underscoring the timeliness and importance of the session’s theme, noting that the diverse presentations collectively illuminate multiple dimensions of what he describes as “this AI thing.” Rather than approaching AI as a distant or speculative phenomenon, he firmly situates it within the present, arguing that societies and institutions have already entered a new technological epoch. To illustrate this point, he draws on a personal anecdote from his professional experience in an innovation company in Germany. Recounting a management debate over whether to adopt AI, he invokes a historical analogy from the Ottoman Empire’s delayed adoption of the printing press. For Dr. Akkuş, this example serves as a cautionary tale: resistance to transformative technologies—particularly those central to knowledge production—can have long-term consequences for institutional and societal vitality. The implicit lesson he derives is clear: AI cannot be ignored or postponed; it must be actively engaged and integrated.
This historical framing is further extended through a comparison with the Industrial Revolution. Dr. Akkuş suggests that while earlier technological transformations primarily displaced manual and routine labor, AI represents a qualitatively different shift insofar as it encroaches upon cognitive and creative domains traditionally associated with human agency. This observation introduces a central concern that runs throughout his commentary: the potential reconfiguration of human roles, authority, and autonomy in an AI-driven environment. At the same time, he highlights the risks of bias embedded within such systems, thereby linking technological expansion with normative and political challenges.
Engaging with Professor Joan Font’s presentation, Dr. Akkuş focuses on the ambivalent attitudes of citizens toward AI in governance. He notes that while individuals may accept the use of AI for administrative or technical tasks, they exhibit significant resistance when AI is associated with core political functions such as decision-making or electoral processes. This distinction, he suggests, reveals an important boundary in public trust: AI is tolerated as an instrument but resisted as an authority. Drawing attention to the empirical finding that individuals with more technocratic or authoritarian orientations tend to be more supportive of AI governance, Dr. Akkuş interprets this as indicative of deeper political dispositions. In his reading, critical and reflective citizens are more likely to question the expansion of AI into political domains, whereas those aligned with technocratic or hierarchical frameworks may be more receptive to delegating authority to algorithmic systems.
However, Dr. Akkuş also raises a methodological and contextual concern regarding the generalizability of these findings. He points out that Spain’s political history, which he characterizes as lacking a strong technocratic tradition, may limit the broader applicability of the results. This observation highlights the importance of situating empirical studies within specific historical and institutional contexts, and suggests that the relationship between technocracy and AI acceptance may vary across political systems.
Turning to Alonso Escamilla’s presentation, Dr. Akkuş offers a more normative and critical reflection on the state of European values. While acknowledging the conceptual link between cultural heritage and democratic norms, he expresses skepticism regarding the contemporary vitality of these values. Drawing on his own experiences in Europe, he argues that the foundational democratic principles historically associated with the European project have been significantly eroded, due in part to crises such as migration, the COVID-19 pandemic, and geopolitical tensions. Within this context of perceived decline, he suggests that AI may emerge not merely as a tool but as a potential framework for reconstructing social and political realities. This perspective introduces a provocative dimension to his commentary: that AI could serve as an alternative—or even substitute—for weakened normative structures.
Dr. Akkuş’s engagement with Aly Hill’s presentation shifts the focus to the political economy of technology. He strongly concurs with the argument that the relationship between political actors and major technology companies is fundamentally driven by financial interests. Using the United States as an illustrative case, he describes a dynamic interplay between different forms of capital—particularly the technology and defense sectors—and their influence on political decision-making. His interpretation frames political alignments not primarily in ideological terms, but as outcomes of competing economic interests.
At the same time, Dr. Akkuş extends Hill’s analysis by emphasizing the fluidity and replaceability of both human actors and technological systems within this political-economic landscape. He notes that not only can individuals—such as technocratic elites—be rapidly replaced when they become politically inconvenient, but even major technology companies are subject to similar dynamics. Referring to recent developments in US federal procurement decisions, he highlights how shifts in political authority can reconfigure technological infrastructures, thereby underscoring the contingent and strategic nature of AI deployment in governance.
In his comments on Amina Vatreš’s presentation, Dr. Akkuş engages with the conceptual distinction between “filter bubbles” and “filter clashes.” He identifies this distinction as a valuable contribution that moves beyond the more commonly discussed notion of echo chambers. While echo chambers emphasize the reinforcement of homogeneous viewpoints, the concept of filter clashes introduces a new analytical layer by examining the spaces and mechanisms through which opposing narratives confront one another. Dr. Akkuş interprets this as an important advancement in understanding the dynamics of digital communication, particularly in relation to populism, where antagonistic interactions play a central role.
Beyond his engagement with individual papers, Dr. Akkuş concludes with a broader reflection on the accelerating development of AI technologies. Drawing on his own experience working with large language models, he emphasizes the rapid pace at which these systems learn and evolve. He notes that AI is not only trained through user interaction but also through the involvement of human labor in model development and refinement. This observation reinforces his earlier point about the inevitability of AI’s integration into everyday practices, including academic writing and knowledge production.
Importantly, Dr. Akkuş acknowledges the transformative impact of AI on intellectual labor. He contrasts his previous experience as a journalist—when writing was a wholly human endeavor—with contemporary practices in which tools like ChatGPT are routinely used to generate and refine text. This shift, he suggests, is not merely technical but ontological: it alters the very nature of authorship, creativity, and reality construction. In this sense, AI does not simply assist in communication; it actively shapes the content and form of knowledge itself.
In conclusion, Dr. Akkuş’s feedback offers a multifaceted and thought-provoking perspective that complements the session’s scholarly contributions. By combining historical analogies, empirical observations, and personal experience, he underscores the urgency of engaging with AI as a transformative force. His remarks highlight both the opportunities and the risks associated with this technological shift, while also pointing to the broader structural and normative questions that it raises for democracy, governance, and human agency.
Questions by Participants
The Q&A session of Panel 14 was marked by a set of conceptually rich and forward-looking interventions that deepened the panel’s central concern with the transformation of democracy under conditions of rapid technological change. Participants’ questions coalesced around the ontological, normative, and political implications of artificial intelligence, particularly its status within democratic systems and its role in reshaping power relations.
A central intervention, raised by Dr. Bulent Kenes, crystallized a key theoretical tension: whether artificial intelligence should be conceptualized not merely as a tool or infrastructure, but as a political agent. Building on earlier remarks by Dr. Jasmin Hasanović, who framed AI as a potential “subject,” Kenes sharpened the inquiry by explicitly asking whether AI possesses—or is evolving toward—agentic qualities within political processes. Directed to Professor Joan Font, this question foregrounded the need to interrogate the boundaries between human and non-human actors in governance, as well as the implications of delegating decision-making authority to algorithmic systems.
Expanding the discussion, Dr. Paolo Gerbaudo encouraged participants to reflect on the broader theoretical takeaways of their research in relation to democratic transformation. His intervention connected empirical, conceptual, and normative strands across the panel, inviting speakers to consider how AI-mediated governance, platform power, and algorithmic knowledge production intersect with the rise of populism and evolving forms of political subjectivity. Collectively, the questions underscored a shared concern with the reconfiguration of agency, legitimacy, and public awareness in an increasingly AI-mediated democratic landscape.
Responses
Response by Amina Vatreš
In her response, Amina Vatreš provided a theoretically sophisticated reflection on the phenomenon of AlgoSpeak, situating it firmly within the broader dynamics of algorithmic mediation and post-digital populism. Engaging with the question raised by Dr. Jasmin Hasanović, she argued that AlgoSpeak should not be understood merely as a linguistic workaround designed to evade platform moderation. Rather, it constitutes a revealing symptom of algorithmic power over visibility, communication, and the structuring of public discourse.
Vatreš emphasized that AlgoSpeak emerges from users’ growing awareness that both the content and form of their communication are continuously filtered, ranked, and potentially suppressed by platform algorithms. This awareness, she suggested, marks a fundamental shift: communication is no longer oriented solely toward other users but is increasingly shaped by strategic considerations directed at algorithmic systems themselves. In this sense, digital expression becomes dual-facing—simultaneously social and computational.
Importantly, she linked AlgoSpeak to the production of collective identity, arguing that it illustrates the active role of users in negotiating and adapting to algorithmic constraints. Users are not passive recipients of curated content; rather, they demonstrate agency by modifying language, employing coded expressions, and experimenting with alternative forms of communication. However, this agency remains structurally limited. As Vatreš noted, such practices operate within the very systems they seek to circumvent, rendering them reactive rather than transformative.
Consequently, AlgoSpeak is neither external to the problem nor a solution to it. Instead, it exemplifies the post-digital condition in which algorithmic systems shape not only what is seen but also how individuals speak, express political positions, and construct collective identities. While users may tactically adapt to algorithmic governance, these adaptations do not fundamentally alter the underlying structures of power. In this regard, AlgoSpeak reflects adaptation rather than resistance, underscoring the enduring constraints of platform-mediated communication.
Response by Aly Hill
In her response, Aly Hill offered a reflective and analytically nuanced engagement with broader questions concerning the political economy of digital platforms, the possibilities of resistance, and the evolving nature of political activism in a technologically mediated environment. Her intervention extended her presentation’s central themes by exploring alternative platform architectures and the limits of contemporary digital mobilization.
Hill first addressed the question of whether technology might exist outside the dominant logics of capital-driven platforms. In this context, she introduced a distinction between centralized and decentralized media systems. Decentralized platforms—such as Reddit or emerging alternatives like Bluesky—were presented as potential counter-models to the monopolistic tendencies of large-scale technology companies. These platforms, characterized by community-based moderation and less centralized algorithmic control, may mitigate some of the pathologies associated with mainstream platforms, including content homogenization, harassment, and the concentration of communicative power. However, Hill remained cautious, noting that the structural dominance of major tech actors raises serious doubts about the scalability and transformative potential of such alternatives.
Turning to the question of political activism, Hill reflected on the growing instability of political identities and movements in the digital age. She suggested that while online platforms enable rapid mobilization and broad dissemination of information, they may lack the durability required for sustained political change. Drawing on insights from Zeynep Tufekci’s work, she highlighted the tension between digitally facilitated protest and long-term organizational capacity. While offline, on-the-ground mobilization retains significance—particularly in contexts of internet shutdowns—Hill expressed skepticism about its ability to fully substitute for the reach and immediacy of digital networks.
Ultimately, her response underscored a dual condition: digital platforms remain indispensable for contemporary activism, yet their structural constraints continue to shape—and potentially limit—the prospects for transformative political change.
Response by Alonso Escamilla
In his response, Alonso Escamilla provided a reflective and forward-looking elaboration on his exploratory research, emphasizing both its conceptual scope and its potential for future development. Acknowledging the feedback and critical insights offered by discussants and participants, he framed his study as an initial step—“the tip of the iceberg”—within a broader research agenda aimed at systematically examining the relationship between artificial intelligence, cultural heritage, and democracy.
Escamilla highlighted the importance of comparative analysis as a key direction for future inquiry. He underscored that cultural heritage is not a monolithic category, but rather a multifaceted domain encompassing tangible, intangible, industrial, and increasingly digital forms. Accordingly, he suggested that the relationship between cultural heritage and democratic values may vary significantly across these different dimensions, as well as across regional and cultural contexts. In particular, he emphasized that comparing European cultural heritage with non-European traditions could reveal underlying biases and asymmetries in how democracy is conceptualized and reproduced.
A central theme of his response concerned the role of youth and sectoral diversity in shaping contemporary engagements with cultural heritage. Drawing on his ongoing research, Escamilla noted that different sectors—such as education, youth work, and sports—approach cultural heritage and democratic participation in distinct ways. He pointed to youth organizations as particularly significant actors in preserving civic-oriented values, even as broader European policy frameworks increasingly prioritize competitiveness and strategic preparedness. In this context, he suggested that youth initiatives often act as a form of normative “buffer,” resisting the erosion of participatory and democratic ideals.
Importantly, Escamilla also reflected on the growing entanglement between digital and physical realities. He illustrated how young people integrate traditional, hands-on practices with digital tools such as 3D printing, thereby creating hybrid forms of cultural production. This interplay, he argued, exemplifies how artificial intelligence and digital technologies are not only reshaping cultural heritage but also redefining spatial and social environments—from urban design to everyday practices of self-representation.
In conclusion, Escamilla emphasized that artificial intelligence is no longer a future prospect but an already operative force that is actively transforming both cultural and democratic landscapes. While the same technological tools are globally available, their meanings and effects remain context-dependent, underscoring the need for nuanced and comparative research moving forward.
Response by Professor Joan Font
In his response, Professor Joan Font offered a reflective and methodologically self-critical engagement with the comments raised by participants, while clarifying key conceptual and empirical dimensions of his research on public attitudes toward artificial intelligence in governance.
A central theme of Professor Font’s intervention was the need to more explicitly integrate political theory into empirical research. Responding to remarks by Dr. Hasanović, he acknowledged that while his study implicitly addresses questions of political legitimacy, this foundational concept was not sufficiently foregrounded in the analysis. He identified this as a broader limitation within public opinion research, which often prioritizes operationalization and statistical modeling at the expense of deeper theoretical engagement. Moving forward, he suggested that a more explicit articulation of the relationship between public attitudes and legitimacy would significantly strengthen the analytical framework.
Responding to the question regarding whether artificial intelligence can be conceptualized as a political agent, Professor Font approached the issue with caution. While recognizing that AI increasingly performs functions that resemble decision-making authority, he did not endorse the view of AI as a fully autonomous political agent. Rather, he implied that AI should be understood as part of a continuum of decision-making arrangements shaped by human design, institutional contexts, and political actors. In this sense, AI may exercise delegated or mediated agency, but its authority remains embedded within—and ultimately dependent upon—human-driven structures of governance and accountability. This perspective aligns with his broader emphasis on legitimacy, suggesting that the critical question is not whether AI is an agent in itself, but how its use affects citizens’ perceptions of legitimate political authority.
Professor Font also addressed concerns regarding the conceptualization of artificial intelligence and the categorization of its roles. He recognized that the term “levels of decision-making authority,” employed in his study, may obscure important distinctions between qualitatively different uses of AI—ranging from routine administrative functions to more speculative or high-stakes political applications. While he justified the inclusion of this broad spectrum on the grounds that such uses are either already implemented or actively debated by political actors, he conceded that a more precise conceptual differentiation would enhance clarity and interpretive rigor.
Turning to the empirical findings, Professor Font acknowledged the limitations of survey-based research in establishing causal mechanisms. In particular, he reflected on the observed correlation between support for AI and what he termed “market-driven authoritarianism.” Rather than indicating outright anti-democratic attitudes, he suggested that this orientation may reflect a pragmatic willingness to prioritize efficiency and outcomes over procedural democratic norms—an interpretation that remains tentative but theoretically suggestive.
Finally, addressing questions of external validity, Professor Font noted that while Spain’s limited experience with technocratic governance may constrain generalization, comparative evidence—particularly from Germany—indicates similar attitudinal patterns. This suggests a degree of cross-national applicability, albeit with important contextual caveats.
Conclusion
Session 14 of the ECPS Virtual Workshop Series demonstrated that artificial intelligence can no longer be treated as an external or merely technical supplement to democratic life. Across the presentations and discussions, a shared insight emerged: AI, algorithms, and platform infrastructures are increasingly involved in shaping not only political communication and administrative decision-making, but also cultural memory, class consciousness, and the very conditions under which “the people” can be imagined and articulated.
What made the session especially valuable was its interdisciplinary breadth. Professor Joan Font’s empirical analysis illuminated the normative tensions surrounding algorithmic legitimacy; Alonso Escamilla’s exploratory study revealed the cultural and epistemic implications of generative AI; Aly Hill showed how Big Tech is reconfiguring populist narratives and working-class subjectivities; and Amina Vatreš offered a powerful theoretical account of identity formation in an algorithmically mediated world. The discussants further enriched the exchange by foregrounding the political economy of AI, the erosion of democratic norms, and the structural limits of digital agency.
Taken together, the session suggested that the future of democracy will depend not simply on whether AI is adopted, but on how it is governed, by whom, and in whose interests. If digital systems increasingly structure the horizons of visibility, participation, and legitimacy, then democratic theory and practice must confront the challenge of ensuring that these emerging infrastructures do not deepen depoliticization, fragmentation, and inequality, but instead remain subject to critical scrutiny, public accountability, and democratic contestation.
Dr. Oludele Solaja’s analysis introduces the concept of “Algorithmic Environmental Populism” to illuminate how digital platforms are reshaping the politics of waste across African cities. Moving beyond conventional policy-centered approaches, Dr. Solaja demonstrates how environmental degradation—from plastic pollution to urban flooding—has become a site of algorithmically mediated political contestation. In this emerging landscape, complex ecological crises are reframed into morally charged narratives of blame, privileging visibility, outrage, and immediacy over systemic understanding. By linking populism theory with digital governance and environmental politics, the article offers a novel framework for understanding how platform logics transform ecological grievances into potent political forces. It is an essential contribution to debates on populism, digital media, and environmental governance in the Global South.
Environmental politics is now occurring not only at policy and infrastructure levels, but also through algorithms—from the clogged drains of Lagos to flood-prone Accra to landfills in South Africa. Environmental degradation has become a politically charged phenomenon on social media, and the sensational, outrage-driven, and immediate nature of these platforms has created an environment where narratives of blame outpace formal, institutional action. I refer to this new phenomenon as Algorithmic Environmental Populism, and I argue that digital infrastructure has become paramount in the formation, circulation, and contestation of ecological grievances.
The environmental crisis is no longer merely a management problem but a digitally mediated political language across the African continent, in which grievance, blame, and claims to power or moral legitimacy are performed. Plastic pollution, floods, burning dumpsites, and informal recycling have entered platform ecologies within which, according to a range of criteria, the most intense, visible, and confrontational content receives algorithmic attention. From this combination emerges a condition in which the environmental crisis is abstracted from complex systemic causes and reframed as a direct moral confrontation between “the people” and villains: polluters, corrupt elites, those who ship waste to Africa, and absent governments. In this process, platform algorithms prioritize the most engaging framing rather than the most policy-relevant one (Zeng & Schfer, 2023; Heidenreich et al., 2022).
The concept offers a way of extending understandings of populism and digital media, by foregrounding the environmental as a key site of algorithmically mediated political struggle. Classical theory on populism deals with the ideological construction of ‘the people’ and ‘the elite,’ while the infrastructures through which populist rhetoric is dispersed have been historically overlooked. Algorithmic Environmental Populism instead draws focus to platform logics, showing how they shape the contours and narratives of ecological complaint. By this it builds on research on algorithmic governance, the increasing role of algorithms in policy perception and the legitimacy of state power (Parthasarathy & Rajala, 2023).
In African cities the role of algorithms in producing a political context for waste is further amplified by its material presence on everyday life. Clogged drains, plastic-choked lagoons, burning dump sites and litter, produces and feeds readily available data streams, which produce, or a “condition of constant possibility” for data to be recorded and transmitted, resulting in environmental breakdown becoming rapidly politicisable. Take, for example, Nigeria. When the Lagos State government implemented restrictions on single-use plastics in 2025, environmental considerations took a back seat to narratives of bias, and selective policy enforcement. Viral image of floodwater pouring through plastic-clogged drains fed accusatory commentary that blamed the state, turning environmental degradation into a performance of political betrayal.
Although it is true that a massive volume of plastic waste is annually dumped in Lagos State, these digital conversations tend to flatten the systems behind environmental degradation into morally legible pronouncements of blame and victimhood, which are amplified in the digital domain for emotional impact, rather than for systemic nuance (Couldry & Mejias, 2023).
The significance of such arguments for politics in Africa is that these stories become diagnostically central. In such cases, a multiple-layered system of production, consumption, municipal service provision and global trade are collapsed into stark oppositional narratives because it is the only way in which environmental problems can be successfully broadcast within an algorithmic environment, where visibility takes priority over complexity. As digital media research shows, what gets amplified is content that triggers reactions: outrage, pity, and the assignment of blame.
Similarly, we can observe this in Kenya where political activism is closely tied to moral pronouncements. Though debates exist surrounding extended producer responsibility, green economy initiatives, and refill systems; their manifestation in the digital space, in an effort to capture attention and elicit reaction, tends to focus on “blame-allocation” rather than the mechanics of institutional responsibility between citizens, corporations, and the state. Floods in Kenya’s urban centers of Nairobi and Mombasa provided highly visual and charged contexts to exacerbate these dynamics, producing further blame-oriented discourse regarding governmental incompetence and the inadequacy of infrastructure. In essence, the digitally mediated form of this political problem is not merely transmitting it; it is actively transforming it.
Another significant dimension of the digital landscape is how it also creates new forms of political subjectivity. Waste pickers and scavengers, once entirely invisible components of the informal city, are now visible. They challenge their invisibility through interventions in the digital domain, attempting to recover material flows and claim their political agency. They are now recognized as integral parts of urban recycling systems, while remaining ignored in the policy sphere (Njeru & Ochieng, 2025). Their visibility can be attributed to algorithms that amplify their stories, portraying them as overlooked labor fighting back against systemic neglect. Locally based actions, such as coastal clean-ups by youth groups in Kenya, become symbolical performances. The clean-up has the effect of politicizing the environment, either as an assertion of the citizen’s responsibility, as an attack on state incompetence or as a demonstration of collaborative effort. Environmental activism is transformed into a moral battlefield on the digital platform.
In South Africa we see a similar phenomenon of politically charged, algorithmically amplified resistance to landfill expansion and waste siting decisions. In 2026 protests against landfill development in urban periphery settlements, turned into a national narrative of social and environmental injustice through media mobilization; landfill as a continuance of structural violence through spatial inequalities. The discourse produced and amplified across the networks links contemporary exposure to historical environmental inequities through these landfill developments. Here Algorithmic Environmental Populism and environmental justice are closely interwoven, as the narratives attributed to technology and its governance are interpreted through morally loaded systems of victimhood and violence. The broader implications of Algorithmic Environmental Populism in Africa are that the histories of unequally mediated ecological flows, including plastics, second-hand goods and e-waste that flow into African cities and homes as waste from global consumption and production patterns. Such stories tend to produce a framing where the external imposition of blame arises from deeper historical conditions known as waste colonialism – an unequal world where states and their inhabitants bear uneven burdens of waste (Mah, 2024; Dauvergne, 2022).
This links directly into concepts of waste sovereignty – a state of ownership and control over material waste flows, their meanings and governance. In the digital space, sovereignty can now be enacted through the control of narrative. Those able to frame environmental crises in terms of simple, easily accessible, morally legible oppositions, are gaining political ground regardless of their technical knowledge. Environmental politics of waste is no longer a question of physical waste, or of policy-makers’ actions, but increasingly a matter of the visibility of what it is that matters and to whom it matters, a battle of recognition, and control, within platform governed space.
Therefore, I suggest a three-stage process of digitally mediated waste politics: first, visible urban environmental decay; second, morally legible frames of attribution; and third, algorithmically favored amplification. It is in these stages that complexity is simplified and environmental disaster turns into visible, and therefore governable, political matter.
A certain democratizing aspect is that it allows for participation on new grounds, where citizens, informal waste workers and activist groups can join in debates around the environment on the internet. The downside is that these systems allow for a contraction of discourse: immediate visibility takes the form of sensation and outrage over deliberative engagement, bringing together political mobilization and propaganda (Heidenreich et al., 2022). Consequently, the environment has begun to be spoken of in conflicting terms: critical discourse clashes with simplified frameworks of accusation. A street in Accra that floods, or a dirty drainage canal in Kenya, or a burning landfill in South Africa, are instantly turned into evidence against the state, corporations, or the global system, obscuring underlying complexities.
This new discourse dynamic has major implications for environmental governance. Effectiveness is no longer solely about design and capacity but also about how environmental policies are understood, accepted, and engaged with on line. Municipalities and governments, as well as non-profit organizations need to operate in the digital space to manage the material and political aspects of waste. Scholars of environmental data governance agree that algorithms are key in framing environmental information (Gabrys, 2023). This is also significant for populist politics; waste cannot continue to be seen as an auxiliary or an afterthought. Instead, it has to be seen as a key component of the negotiations around citizenship, inequality, sovereignty and state power; the material traces of society that make social tensions visible and open to struggle. Algorithmic Environmental Populism provides an explanatory frame that connects environmental governance, digital media, and populist politics together, and helps to make sense of the way ecological grievance can be translated into potent political force by means of technologically managed visibility.
In short, the environmental politics of waste in Africa is no longer solely regulated by state and international institutions; its regulation is also about what becomes visible and how, within the spaces that platform logics control. What is now at stake is how we see waste, what we make of it in the discourse we construct, and the meaning that it is given within our digitally mediated attention economies. This transformation is an emblem of a broader shift: authority is no longer held by those who convene political discussions in spaces that are free from the influence of amplification. The management of waste, therefore, involves managing its meaning, a task that in the digital age depends greatly on the very politics of platforms.
References
Couldry, N. & Mejias, U. A. (2023). “Data colonialism and the future of social order.” New Media & Society, 25(4), 945–962.
Dauvergne, P. (2022). “Waste, pollution, and the global plastic crisis.” Global Environmental Politics, 22(1), 1–10.
Gabrys, J. (2023). “Digital waste and environmental data politics.” Information, Communication & Society, 26(9), 1785–1801.
Heidenreich, T., et al. (2022). “Populism and digital media: A comparative perspective.” Political Communication, 39(3), 345–362.
Mah, A. (2024). “Waste colonialism and global inequality.” Nature Sustainability, 7(1), 12–15.
Njeru, J. & Ochieng, C. (2025). “Plastic waste governance and informal economies in Africa.” Environmental Politics, 34(2), 256–275.
Parthasarathy, S. & Rajala, R. (2023). “Algorithmic governance and environmental policy.” Regulation & Governance, 17(4), 987–1003.
Zeng, J. & Schäfer, M. S. (2023). “Conceptualizing algorithmic populism.” New Media & Society, 25(8), 2015–2032.
This research note introduces high frequency “real-time” Google Trends data as a novel tool for studying public engagement with major political speeches. Unlike traditional dial-testing, which captures emotional reactions, “googling” patterns reveal cognitive engagement—moments when audiences actively seek information about claims, people, or policies mentioned by the speaker. Analyzing the 2026 State of the Union Address by President Donald J. Trump, the study shows that search activity spiked around issues such as TrumpRX, “Trump Accounts,” and D.E.I., as well as narratives tied to culture-war themes like the story of Sage Blair. The findings suggest that policy proposals addressing material needs—combined with culture-war framing—can mobilize significant public attention, echoing strategies seen in contemporary populist politics.
This research note introduces high frequency “real time” Google Trends data as a tool for research on the general public’s engagement with high-profile political speeches. Contrary to the well-known dial-testing – providing data on emotional engagement – “googling” patterns offer glimpse into the cognitive engagement – actual efforts to obtain additional information on the issues introduced in the speech.
The 2026 State of the Union (SOTU) Address by President Donald J. Trump offered promising testing ground for such tool, due to its prominence, extraordinary length, diverse content and involvement of extraordinary invitees personifying the key narratives. The results indicate that TrumpRX and “Trump Accounts” – generated substantial interest among audience – as well as D.E.I. (Diversity, Equity, and Inclusion). Moreover, search data revealed noticeable interest in the history of Sage Blair – an example of engaging framing of the culture war issues. These narratives could be applied in forthcoming campaigns to construct the mix of policies addressing material needs of anti-elitist voters and the culture war narrative – the sort of “bread and circuses” already deployed by Central European illiberals.
Introduction
On 24 February 2026 President Donald J. Trump delivered the first State of the Union (SOTU) address of his second term. The one hour and 47 minutes performance – breaking President Clinton’s 2000 record by over 20 percent (Peters, 2026) – provided unique communication opportunity for president facing tensions among his MAGA fandom as midterm elections approaches.
Staged in the most “presidential” setting imaginable – a joint session of the United States Congress in a year marking 250 years of US independence – President Trump’s spectacle involved proclamation of “the golden age of America,” litany of 47th President’s achievements and bashing on the “craziness” of his opponents. It also featured appearance of extraordinary invitees, personifying President’s narratives on the past, present and future of the United States. Indeed, as noticed by The Economist, the speech was “light on policy and heavy on theatre” as “more than 60% of it made no reference to specific proposals, far more than any other address in the past 50 year.”[1]
According to the Nielsen data, SOTU attracted 32.6 million TV viewers.[2] In a 24 February survey, conducted for CNN via text message using the SSRS Text Message Panel among 482 respondents who watched the speech,[3] 64% reacted positively (of them 38% very positively) and 36% negatively (of them 20% very negatively). Noteworthy, the sample was noticeably skewed towards the right – only 18% of respondents described themselves as Democrats, 41% as Republicans, and 41% as independents or others.
As put by W. Mead, “Trump does not speak in order to convey information to his hearers” but rather say things and then see how they react.[4] Undoubtedly SOTU spectacle offered extraordinary occasion for that, with President spending nearly two hours probing wide array of themes and narratives. In that sense the event can be considered an experiment, and the vast amount of collected data will likely be meticulously crunched in order to develop communication strategies for approaching midterm elections.
On top of surveys, such data can be collected using so called dial-testing – technique developed in 1984 to record real-time reactions of the focus group participants (Kirk & Schill, 2011). For example, Fox News enriched its covering of 2026 SOTU address with dial-testing results from panel made up of 29 Democrats, 30 independents and 41 Republicans.[5]
The goal of this research note is to introduce another data source, that can be applied to elicit real-time reactions audience of such political event – the “real time”[6] high-frequency Google Trends data.
Contrary to the dial-testing, aimed at recording feelings and attitudes (emotional reaction), Google Trends reflects actual behaviour of millions of people engaging in the effort to obtain additional information on the issues introduced by the speaker. That could involve attempts to fact-check or learn more about the piece of information mentioned as a part of the bigger narrative.
The rest of the note is structured as follows. Section II briefly introduces Google Trends as a data source, Section IIIapplies them to the President Trump’s 2026 SOTU address, focusing on people explicitly mentioned by the President, as well as keywords relevant for his key topics. Section IV concludes.
2) “Real Time” Google Trends data
Presented research design is based upon assumption that as of 24 February 2026, “googling” remained sufficiently popular tool for searching factual information in the USA (as compared to alternative search engines or conversations with AI chatbots), that Google Trends data can provide meaningful depiction of this process.
As explained in FAQ about Google Trends data,[7] its aim is to “display interest in a particular topic from around the globe or down to city-level geography.” Search data is normalized “to the time and location of a query … each data point is divided by the total searches of the geography and time range it represents to compare relative popularity … the resulting numbers are then scaled on a range of 0 to 100 based on a topic’s proportion to all searches on all topics.”
Some categories of searches are filtered out, including: (i) searches made by very few people; (ii) repeated searches from the same person over a short period of time; (iii) queries with apostrophes and other special characters as well as (iv) searches made by Google products and services. However, it is admitted that data “can also reflect irregular search activity, such as automated searches or queries that may be associated with attempts to spam our search results.”[8]
Technically, public Google Trends tool produces data using “largely unfiltered sample[9] of actual search requests made to Google.” The “real time” data relies on sample spanning seven days only, however it can be accessed in intervals up to one minute – frequency sufficiently high to trace reactions to the political speech. Unfortunately, reliance on sampling and the “rolling” character of the data diminishes replicability of the results.
Summing up, the search data provided by public Google Trends tool have serious limitations from the scientific point of view. Indeed, users are directly reminded that it is “not scientific and might not be a perfect mirror of search activity.”
However, it offers too many opportunities to be simply ignored, as indicated by application to the topics ranging from macroeconomics (Varian & Choi, 2012), electoral politics (Prado-Román et al. 2021) and pandemic dynamics (Saegner & Austys, 2022).
3) The Results
To gain in-depth insight into the search patterns of US general public during the SOTU address, “real time” Google Trends data for the territory of the United States had been collected with highest available frequency – i.e. with one-minute intervals. The data spanned window from 9:00 PM to 11:00 PM Eastern Time, with SOTU address scheduled at 9:00 PM ET (actually started at 9:11 PM ET).
By design, the values of the search volume index ranged from 0 to 100 – which, in this particular sample, denoted the search volume for “Trump” at 9:42 PM, after President discussed “Trump Accounts”.
3.1. Searches related to the individuals mentioned during the 2026 SOTU address
To demonstrate analytical potential of “real time” Google Trends data for analysis high-profile political speeches, search volume for each of the 30 individuals explicitly referred to by the President Trump during 2026 SOTU address (see table 1 for list) had been plotted on figure 1.
Table 1. Summary of individuals mentioned by President Donald J. Trump during 2026 SOTU address
Name
Description based on the President Trump’s address and open sources
Joe Biden
46th US President
Connor Hellebuyck
Ice-hockey goaltender, gold medalist of Team U.S.A.
Buddy Taggart
World War II veteran
Milly Cate McClymond
Survivor of Texas flood of 4 July 2025
Scott Ruskan
Coast Guard rescue swimmer during Texas flood of 4 July 2025
Megan Hemhauser
Beneficiary of President Trump’s tax cuts
M. and S. Dell
Donors of the $6,250,000,000 to fund the “Trump accounts”
Brad Gerstner
Another donor for “Trump accounts”
Catherine Rayner
Beneficiary of President Trump’s drug discounts, undergoing IVF
Raysall Wiggins
Placed bids on 20 homes but lost to gigantic investment firms
Nancy Pelosi
Member of the U.S. House of Representatives
Dalilah Coleman
Victim of a car crash caused by “illegal alien”
Lizbeth Medina
Victim of a murder committed by “illegal alien”
Sage Blair
In 2021 socially transitioned to a new gender
Melania Trump
The First Lady
Charlie Kirk
Assassinated MAGA activist
Anya Zarutska
Ukrainian war refugee, victim of a murder
Sarah Beckstrom
National Guard Specialist killed in the terrorist attack in Washington, DC
Andrew Wolfe
National Guard Staff Sgt., survivor of the terrorist attack in Washington, DC
Steve Witkoff
Special Envoy
Jared Kushner
Special Envoy, Ivanka Trump’s husband
Marco Rubio
U.S. Secretary of State
Suleimani
Iranian Islamic Revolutionary Guard Corps general killed in U.S. attack
Nicolás Maduro
President of Venezuela raided by US forces in 2026
Delcy Rodríguez
Acting president of Venezuela
E. and A. Gonzalez
Venezuelan opposition leader freed from prison and his niece
Eric Slover
U.S. Army Chief Warrant Officer 5, helicopter pilot during Maduro raid
Royce Williams
World War II, Korean war and Vietnam war veteran
Thomas Jefferson
Founder of the USA, Third US President
Source: Own compilation based on transcript by The New York Times[10]
As one could expect, celebrity status of C. Hellebuyck and Melania Trump was reflected in the volume of related searches. Other individuals mentioned by President Trump, who attracted highest search volumes involved: (i) Michael and Susan Dell and (ii) Brad Gerstner – “Trump Accounts” donors, (iii) Nancy Pelosi, (iv) Sage Blair – personifying narrative on risks associated with gender transition, (v) Charlie Kirk – assassinated MAGA activist, (vi) Andrew Wolfe – Washington D.C. terrorist attack survivor , (vii) Marco Rubio – US Secretary of State and (viii) Royce Williams – war veteran awarded with Congressional Medal of Honor.
Undoubtedly the exact reasons for “googling” specific individuals in a given time can differ. To use example of Nancy Pelosi, first peak involved President’s quip on Stop Insider Trading Act, and the second coincided with her appearance in Fox broadcast[11] wearing “Release the Files” button.[12] Despite that, the search volume for “Epstein” remained unaffected (see fig. 2). One can imagine that peak for Thomas Jefferson reflected the attempts to fact-check date of his death provided by the President.
3..2. Search words related to key issues raised by President Trump during 2026 SOTU address
Figure 2 plots second group of keywords examined in this note – those related to the topics raised by the President Trump, selected on the basis of the transcript of the speech.
The top panel illustrates the most-searched keywords, starting with the President himself, D.E.I. and two Trump-named programs – “Trump accounts” (saving vehicle for American children[13]) and TrumpRX (website providing access to large discounts on high-priced medicines[14]). Also, the recent decision of the Supreme Court on tariffs and President’s quip on the renaming of Fort Bragg had been reflected in “googling” data.
The middle panel illustrates primarily keywords referring to the economy and costs of living. Despite President Trump’s references to the inflation data or the remarks on the price of eggs and beef, there is no doubt that “$1.85 a gallon for gasoline” inspired the most factchecking.
Finally, the searches on crime and murder peaked as President Trump urged Congress to pass “tough legislation to make sure violent and dangerous repeat offenders are put behind bars, and importantly, that they stay there” (search volume for murder previously peaked when President proclaimed that the “murder rate saw its single largest decline in recorded history”). Also, President’s references to the insider trading and voter ID legislation – as well as quips on “Somali pirates who ransacked Minnesota” – had been reflected in the respective keywords search volumes.
In a survey conducted for the CNN,[15] 45% of respondents claimed that the President focused too little on the economy and costs of living (according to 53% it was the right amount) and 38% claimed that he focused too much on immigration (according to 56% it was the right amount) – assessment that seems consistent with patterns observed in web searches. As of foreign policy 62% claimed the President devoted the right amount.
Given substantial search volumes for D.E.I. and two Trump-named programs, it is interesting to explore their state-level differences. The data indicates that in some states D.E.I. was “googled” much more intensely than both Trump-named programs (like Rhode Island and Vermont). TrumpRX attracted considerably more attention than D.E.I. in several Republican states, as well as District of Columbia and Virginia. “Trump Accounts” did so in Alaska, Montana and D.C., but not in South Dakota.
4) Conclusions
The goal of this note was to introduce high frequency “real time” Google Trends data as a tool for examining the general public’s reactions to the high-profile political speeches. Contrary to the well-known dial-testing – providing data on emotional reactions – “googling” patterns offers glimpse into the cognitive reactions – actual efforts to obtain additional information on the issues introduced in the speech. The 2026 SOTU address by President Trump offered promising testing ground for such tool, due to its prominence, length, range of topics and extraordinary invitees personifying the key narratives.
To illustrate its analytic potential, one can compare obtained results with the conventional wisdom on 2026 SOTU. In particular, relatively scant attention is paid to the issue of TrumpRX or “Trump Accounts” – that actually inspired a lot of information searching.
That could indicate, that as of 2026, programmes directed at the material needs of voters – although with distinct, US characteristics, like reliance on market mechanisms and billionaire donations – could resonate among President Trump’s bases. Thereby, their importance in his political strategy could increase.
Moreover, as judged by “googling” patterns, topics like D.E.I., political correctness (like renaming Fort Bragg) still attract attention of US public. The interest in the history of Sage Blair confirmed that her story offered engaging example of framing culture war issues.
If indeed deployed, the mix of policies addressing material needs of anti-elitist voters coupled with the culture war narrative could provide MAGA with the sort of “bread and circuses” already deployed by Central European illiberals, ending what Timothy Snyder called “sado-populism.”
(*) Kamil Joński, Ph.D. is an assistant in the Department of Tax Law at the Warsaw School of Economics (SGH) and an economist by training. He holds a degree from SGH and is currently employed as part of a research project at the institution. Dr. Joński has participated in several research projects funded by the National Science Centre and conducted at the Warsaw School of Economics, the University of Economics in Kraków, and Adam Mickiewicz University in Poznań. His research focuses on the functioning of public institutions—particularly common and administrative courts—as well as public policy formulation and implementation, tax policy, and legislative processes.
References
Peters, G. (2026). “Length of State of the Union Addresses in Minutes (from 1966).” The American Presidency Project. Ed. John T. Woolley and Gerhard Peters. Santa Barbara, CA: University of California. 1999-2026. Available at: https://www.presidency.ucsb.edu/node/324136/ (accessed on February 26, 2026).
Prado-Román, C.; Gómez-Martínez, R.; Orden-Cruz, C. (2021). “Google Trends as a Predictor of Presidential Elections: The United States Versus Canada.” American Behavioral Scientist. 2021;65(4):666-680. doi:10.1177/0002764220975067
Saegner, T; Austys, D. (2022). “Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.” International Journal of Environmental Research and Public Health, 2022, Sep 29;19(19):12394. doi: 10.3390/ijerph191912394.
Kirk R.; D. Schill. (2011). “CNN’s Dial Testing of the Presidential Debates. Parameters of Discussion in Tech Driven Politics.” In: Hendricks, J.A., & Kaid, L.L. (Eds.), Techno Politics in Presidential Campaigning: New Voices, New Technologies, and New Voters, Routledge. https://doi.org/10.4324/9780203851265
Footnotes
[1] https://www.economist.com/graphic-detail/2026/02/25/our-language-analysis-of-donald-trumps-state-of-the-union-address (Accessed 2 March 2026).
[2] https://www.nielsen.com/news-center/2026/32-6-million-watch-2026-state-of-the-union-address/ (Accessed 2 March 2026).
[3] https://www.documentcloud.org/documents/27411442-cnn-poll-conducted-by-ssrs-state-of-the-union-reaction/ (Accessed 2 March 2026).
[4] LSE public event “American foreign policy in the age of Trump”, 19 February 2026, available at: https://youtu.be/5OhbCXoJ-kM?list=PLK4elntcUEy3kR3B4Ws8PcKndb1g5a68Y&t=779 11584551 (Accessed 2 March 2026).
[5] https://www.foxnews.com/politics/voters-react-trump-touts-signature-tariff-plan-state-union (Accessed 2 March 2026).
[6] https://medium.com/google-news-lab/what-is-google-trends-data-and-what-does-it-mean-b48f07342ee8 (Accessed 2 March 2026).
[7] https://support.google.com/trends/answer/4365533 (Accessed 2 March 2026).
[8] It is explained that “these searches may be retained in Google Trends as a security measure: filtering them from Google Trends would help those issuing such queries to understand we’ve identified them”.
[9] As explained later: “Providing access to the entire data set would be too large to process quickly. By sampling data, we can look at a dataset representative of all Google searches, while finding insights that can be processed within minutes of an event happening in the real world”.
[10] https://www.nytimes.com/2026/02/25/us/politics/state-of-the-union-transcript-trump.html (Accessed 2 March 2026). See also text and video available at: https://www.presidency.ucsb.edu/node/386357 (Accessed 2 March 2026).
[11] Video recording by LiveNOW from FOX, available at: https://www.youtube.com/watch?v=zF7Vve53z4k (Accessed 2 March 2026).
[12] https://nypost.com/2026/02/24/us-news/democratic-womens-caucus-reps-wear-all-white-attire-epstein-related-pins-to-state-of-the-union-2026-address/ (Accessed 2 March 2026).
[13] https://www.whitehouse.gov/research/2025/08/trump-accounts-give-the-next-generation-a-jump-start-on-saving/ (Accessed 2 March 2026).
[14] https://www.whitehouse.gov/fact-sheets/2026/02/fact-sheet-president-donald-j-trump-launches-trumprx-gov-to-bring-lower-drug-prices-to-american-patients/ (Accessed 2 March 2026).
[15] https://www.documentcloud.org/documents/27411442-cnn-poll-conducted-by-ssrs-state-of-the-union-reaction/ (Accessed 2 March 2026).
In this ECPS interview, Professor Daniel Treisman examines how Trump’s political style intersects with the logic of informational autocracy and democratic backsliding. Drawing on “Informational Autocracy,” he argues that contemporary authoritarianism often relies less on mass repression than on “controlling narratives, selective coercion, and performance legitimacy.” Trump’s pressure on comedians, broadcasters, universities, and law firms, Professor Treisman suggests, reflects a familiar “inclination” toward intimidation—yet “the outcome was different,” because democratic institutions can still generate pushback. The core issue, he stresses, is whether US checks and civil society can withstand “executive aggrandizement”—the drive to “go beyond the formal or traditional powers of the office and consolidate control.”
In an era marked by democratic backsliding, populist leadership, and the reconfiguration of informational power, the resilience of liberal democracy has become a central concern for scholars and policymakers alike. In this wide-ranging interview with the European Center for Populism Studies (ECPS), Professor Daniel Treisman—Professor of Political Science at the University of California, Los Angeles, and Research Associate at the National Bureau of Economic Research—offers a nuanced and empirically grounded assessment of how Donald Trump’s political strategy intersects with the logic of informational autocracy, executive aggrandizement, and democratic fragility.
Drawing on his influential work Informational Autocracy (co-authored with Sergei Guriev), Professor Treisman situates Trump’s threats against comedians, journalists, universities, and other institutional actors within a broader global pattern in which contemporary autocrats rely less on mass repression than on “controlling narratives, selective coercion, and performance legitimacy.” While Trump’s behavior often resembles that of informational autocrats, Professor Treisman emphasizes a crucial distinction: “So, while the inclination is similar, the outcome was different.” Episodes such as the pressure placed on late-night comedian Jimmy Kimmel reveal Trump’s “tendency to expand his power and to overstep traditional limits,” but also the continued—if uneven—capacity of democratic institutions and civil society to push back.
At the core of the interview lies a central analytical question: whether Trump’s conduct represents a failed or incomplete attempt to translate informational autocracy into a still-competitive democratic system. As Professor Treisman puts it, “The real question… is how resilient democratic societies and civil societies in democratic settings can prove to be in response to a leader who seeks what is often called executive aggrandizement.” This concern animates Professor Treisman’s discussion of selective intimidation, signaling repression, and the targeting of elite institutions—strategies designed to “score some visible victories” and deter broader resistance without resorting to outright censorship.
The interview also explores how new media ecosystems and the rise of a tech “broligarchy” complicate classical models of informational control. Professor Treisman highlights the hybrid arrangements created by platform ownership, algorithmic amplification, and strategic alignment between populist leaders and tech elites, noting that these dynamics allow political actors to undermine epistemic authority “without overt censorship.” While Trump has aggressively pressured legacy media through litigation and regulatory threats, his relationship with major technology firms remains more transactional and indirect—distinct from the tightly coordinated media control characteristic of full informational autocracies.
Beyond the US case, Professor Treisman offers comparative insights into charismatic populism in Latin America, bureaucratized authoritarianism in Russia and Hungary, and the structural uncertainties surrounding democratic decline. Reflecting on Democracy by Mistake, he cautions against deterministic readings of democratic erosion, stressing that “mistakes can be forces for good” as well as for authoritarian empowerment. In closing, Professor Treisman urges analytical humility: distinguishing between cyclical stress and durable authoritarian transformation, he argues, remains inherently uncertain, as history “does not come with labels that are easy to read.”
Taken together, this interview provides a sober, theoretically informed reflection on Trumpism, informational power, and the fragile boundaries between democratic contestation and authoritarian drift.
Here is the edited transcript of our interview with Professor Daniel Treisman, slightly revised for clarity and flow.
Trump Has Shown Every Inclination of Informational Autocrats
US President Donald Trump held a campaign rally at PPG Paints Arena in Pittsburgh, Pennsylvania, on November 4, 2024. Photo: Chip Somodevilla.[/caption]
Professor Daniel Treisman, thank you so much for joining our interview series. Let me start right away with the first question: In “Informational Autocracy,” you argue that contemporary autocrats rely less on overt repression and more on controlling narratives, selective coercion, and performance legitimacy. How should we analytically situate Trump’s recent threats against broadcasters and comedians within this framework—are we observing an attempted translation of informational autocracy into a still-competitive democratic setting?
Professor Daniel Treisman: It’s very interesting to think about the various tactics and approaches that Trump has used and to compare them with the kinds of practices we see in informational autocracies. Clearly, there are many parallels, and a great deal looks very familiar.
For instance, in the early 2000s in Russia, President Putin was offended by a comedy show that portrayed him in an unflattering light. It was a satirical program called Kukly. He made it apparent to the authorities at that station that the show had to be canceled, and it was indeed canceled.
You mentioned Trump and comedy in the US, and we know about the recent Jimmy Kimmel case. What is interesting is that, on the surface, the situation looks very similar. Trump was offended by jokes Kimmel had been telling on his show, and he made it clear to the owners of the station that he thought Kimmel should be canceled. The head of the FCC (Federal Communications Commission) then put pressure on the channel.
The outcome, however, was different. Kimmel was taken off the air for a few days—about a week—and then reinstated. He returned very forcefully, speaking about freedom and the need for separation between government and television.
So, while the inclination is similar, the outcome was different. We often see in Trump a tendency to expand his power and to overstep traditional limits. The real question, for me, is how resilient democratic societies and civil societies in democratic settings can prove to be in response to a leader who seeks what is often called executive aggrandizement—going beyond the formal or traditional powers of the office and consolidating control in his own hands. This is precisely the process that characterizes democratic backsliding toward informational autocracy.
In that sense, this episode illustrates how Trump has shown every inclination to do the sorts of things that informational autocrats do, and if he were free to do so, I am sure he would move toward a more authoritarian or informationally autocratic setup. So far, however, we have seen a considerable degree of pushback and resilience on the part of American societal and democratic structures—through checks and balances and other mechanisms.
That said, it has been disappointing that we have not seen more resistance. The docility of Congress under Republican leadership and the questionable judgments of some courts have been troubling for those who view the White House’s attacks on the media, universities, and subnational governments as real threats to democracy. Those developments are certainly discouraging.
Nevertheless, across the board, we continue to see significant resistance, and that is what truly distinguishes full-fledged informational autocracies from developed democracies that manage to survive as democracies. It is not that democracies never produce populist politicians who want to push in an authoritarian direction—they do. These are politicians with authoritarian impulses, sometimes driven by narcissism or by a highly cynical political strategy. What ultimately varies is how far they are able to go.
Trump Is a Populist Proud of Defying Democratic Norms
Much of your work emphasizes that informational autocrats avoid crossing visible “red lines” that would trigger mass backlash. Does Trump’s increasingly explicit intimidation of the media suggest either miscalculation or a belief that democratic norms of speech protection have already eroded enough to absorb such shocks?
Professor Daniel Treisman: That’s a very good question, and it’s difficult to give a simple answer. I think there is sometimes an element of miscalculation. But let me step back for a moment—it’s not entirely clear that this is miscalculation, because we don’t fully understand what Trump’s strategy is.
In some ways, as I’ve said, he looks quite similar to various informational autocrats in authoritarian societies. But in other ways, he is quite different. As you noted, informational autocrats typically try not to appear overtly to be transgressing the rules of democracy. They present themselves as genuine, loyal democrats. They claim to follow constitutional procedures, often using legalistic language, and they frame their power grabs as legitimate exercises of authority for ostensibly valid purposes, such as protecting the public from pornography, terrorism, or similar threats.
The goal of genuine informational autocrats is not to challenge the system openly, but to create the impression that they are operating fully within democratic rules, while accusing their opponents of being undemocratic. They seek to project an image of competence, benevolence, and modernity, and to portray critics as those who threaten democracy.
There is an element of this in Trump’s behavior. He certainly accuses Democrats of being undemocratic. But there is also a distinct bravado—a deliberate defiance of democratic rules and norms. He openly states that when he pushes the Justice Department to investigate his critics and rivals, he is motivated by a desire for retribution. He rejects the idea of impartial justice and openly embraces the politicization of the justice system. In doing so, he often deliberately says things that are meant to provoke outrage and that are clearly undemocratic.
In this sense, he is not an authoritarian pretending to be a democrat. He is a populist politician who is, in some respects, openly proud of being undemocratic. He might argue that this is still democratic because his base supports him—and indeed, he does say that. But he also claims that there are no checks and balances, that the only constraint on him is his own morality, which amounts to a direct denial of the democratic system rather than a pretense of adherence to it.
So, it is difficult to determine whether this behavior reflects miscalculation or is simply part of his strategy, and whether he differs in this respect from informational autocrats. He appears to recognize that he is operating within a democratic system with a powerful civil society and has chosen to confront it directly and test its limits, rather than behaving like informational autocrats such as Orbán or early Putin, who presented themselves as ordinary democratic leaders supported by the majority while depicting their opponents as extremists seeking to undermine or overthrow democracy.
The Strategy Is to Score Visible Victories That Intimidate Others
Donald Trump delivers a victory speech after his big win in the Nevada caucus at Treasure Island Hotel & Casino, flanked by his sons Eric (right) and Donald Jr. (left) in Las Vegas, NV. Photo: oe Sohm.
Informational autocracies often rely on signaling repression—making examples rather than governing through mass coercion. How should we interpret Trump’s selective targeting of journalists, broadcasters, and universities in this light?
Professor Daniel Treisman: Well, it’s not just Trump, of course. This time he came in with a team that had thought carefully about how to attack various institutions in American society that they deeply opposed, including universities, law firms, some courts, and various subnational governments. The goal was quite directly to weaken those parts of what they viewed as a dominant political and cultural elite.
In part, yes, the strategy was to score some visible victories that would intimidate other members of a particular sector. So, you go after one university—like Columbia—very hard, essentially intimidating it into doing a deal, and then all the other universities would cave and negotiate individually with the Department of Education or the White House. There is an element here of signaling toughness, of attempting intimidation on a kind of wholesale scale.
That is quite similar to informational autocracies. There is less, as I mentioned earlier, of a concern with constraining actions to fit the appearance of democracy and normal democratic politics. Instead, there is a deliberate challenge—within the US context—to many of the legal underpinnings and long-standing understandings of the relationship between the presidency and other institutions, some of which have prevailed for decades or even centuries.
That said, this behavior is not entirely distinctive to authoritarian politics. All politicians try to signal their intentions by demonstrating, through particular cases, what their approach will be. What is distinctive here is that the goals of the Trump administration regarding universities and law firms have been very extreme. Essentially, they want greater control and a particular ideological orientation within universities, and they want to exclude intellectual approaches and philosophies they oppose.
With law firms, the aim is to discourage large, professional firms from opposing them or taking cases against them. That message was sent deliberately, through a barrage of attacks on different fronts very quickly during the first weeks and months of the administration, precisely in order to signal resolve and warn others.
So, in some respects, this does resemble informational autocracy. But it is also part of a broader phenomenon. Revolutionary politicians—or politicians seeking to implement fundamental changes—often come into office with a program and strike very hard at the outset to test how far they can go before resistance organizes and pushes back. Sometimes this is an effective strategy: if the initial blow is strong enough, opposition may fail to organize in time, allowing a new status quo to take hold.
Tech Billionaires Are Treated as Leverage Points
How does the rise of a tech “broligarchy”—with key digital venues controlled by figures such as Elon Musk, Mark Zuckerberg, and Jeff Bezos—complicate the classic logic of informational control? How do platform ownership, algorithmic governance, and strategic collaboration with populist leaders such as Donald Trump reshape the dynamics of informational autocracy? To what extent do these hybrid arrangements—combining formal pluralism with asymmetric visibility and amplification—enable populist actors to undermine epistemic authority and institutional trust without resorting to overt censorship?
Professor Daniel Treisman: That’s a great—and complicated—question. I think both informational autocracy and populism are closely tied to information and media. They tend to thrive in periods of technological change, when new media forms emerge.
In the early days of mass newspapers, for instance, that medium created new opportunities for populists to appeal to broader constituencies than had previously been mobilized in politics. We see something similar with the internet. As it became more developed and central to everyday life, it opened up new avenues for outsiders to engage in a different kind of politics. In democracies, this has been a major foundation of the recent populist wave.
In authoritarian contexts, similar opportunities have allowed authoritarian leaders to use the internet to communicate in new ways and to present themselves as democratic and competent through manipulation—much more effectively than old-style propaganda, which relied heavily on intimidation but was less successful in creating a convincing, all-encompassing political image. In this sense, new information technologies have reshaped not only perceptions of individual politicians but also broader understandings of the political system itself.
New information technology is therefore a central driver of the changes we are seeing in both democratic and authoritarian systems. In the American case, more specifically, the relationship between Trump and major technology firms—led by tech billionaires such as Elon Musk, Mark Zuckerberg, and others—is complex.
Going into Trump’s second term, there was something of a meeting of the minds between Silicon Valley and the Trump team. Many in the tech sector felt that the industry—and tech billionaires personally—had been mistreated by the Biden administration, citing what they perceived as hostility, attempts to censor right-wing or libertarian views, overregulation, and even the debanking of entrepreneurs involved in new areas such as cryptocurrency. This generated real antagonism toward the Democrats among parts of Silicon Valley, aligning well with the attitudes and plans of the Trump camp.
This was particularly evident in the case of Elon Musk, who was effectively given carte blanche to move aggressively against the federal bureaucracy and dismantle large parts of the government in a short period of time. At the same time, there have also been tensions—if not open confrontations—between the Trump administration and some tech leaders. Still, many of them appear to perceive shared opportunities.
Although Musk is no longer in the administration and clearly disagrees with Trump on certain issues, such as fiscal policy, he—and many other tech billionaires—continue to see opportunities in the current political environment. Not all, of course; some remain aligned with the Democrats. But many hold libertarian views and see Trump as more receptive to their ideas about technological development, the treatment of billionaires, and the balance between regulation and freedom.
The Trump administration has also actively sought to influence the media environment, particularly legacy media, by pressuring the owners of major networks. In ways reminiscent of informational autocracies, Trump has relied on defamation suits, libel actions, and other legal tools to intimidate and pressure media organizations.
With social media, however, the approach has been more indirect. Trump created his own social network and has shown little interest in directly regulating platforms such as X or Facebook. Instead, he treats tech billionaires much like other wealthy actors—as leverage points. If he wants something, he applies pressure, and as long as his demands are not too costly, they tend to comply. There is little incentive for them to engage in open confrontation.
That said, this does not amount to the kind of comprehensive, day-to-day control characteristic of full informational autocracies, where authorities maintain close, behind-the-scenes relationships with most media outlets and allow only marginal opposition voices without real influence or mass reach.
In short, the parallel between Trump and informational autocrats in this domain—much like in others—is imperfect. Some features are strikingly reminiscent of informational autocracy, while others differ substantially. These differences reflect both contextual factors—such as the scale and global reach of US-based technology companies compared to media in smaller authoritarian states—and Trump’s own distinctive political style.
Caricature: Shutterstock.
Pluralism Survives, but the Playing Field Is Tilted
You and Sergei Guriev stress that modern autocrats seek to preserve the appearance of pluralism while hollowing it out. To what extent do Trump’s regulatory threats and litigation strategies resemble this logic of simulated legality rather than outright censorship?
Professor Daniel Treisman: I don’t think there is outright censorship. I don’t see outright censorship. It is much more a matter of trying to persuade—trying to send signals to the media to tone down criticism—or, as I mentioned, of confronting them with defamation suits or costly regulatory interference.
So, I think pluralism does exist; we do see pluralism in the United States. At the same time, there are constant efforts to tilt the playing field. Many of these efforts are not new. Republicans in the US political system have been doing this for a very long time—and not just Republicans; Democrats often use similar tools—to gain small, localized advantages, or sometimes larger ones, through practices such as gerrymandering or by refining voting laws in ways they believe will favor them.
All of that is, sadly, part of the American political tradition. Trump has often turbocharged this kind of behavior, as in the Texas mid-decade gerrymandering of congressional constituencies, but it is not radically new.
So, pluralism survives. There are efforts to win within a pluralist context, and there are also efforts to intimidate the opposition in this Trumpian, rather anarchic and blatant way. But I do not see real censorship or the kind of cohesive system we find in fully developed informational autocracies.
It is much more anarchic. Who knows how things will develop? Nobody can predict the future, but at present, it looks rather different to me.
Mistakes Are Easier to See in Retrospect
In“Democracy by Mistake,” you highlight how democracy often emerges—and collapses—not through design but through elite error. Looking at the US today, which elite misjudgments (judicial restraint, partisan polarization, media fragmentation) most plausibly explain the vulnerability of democratic guardrails?
Professor Daniel Treisman: In the US, we don’t really know. We don’t yet know whether what we are witnessing is an intense challenge to the democratic system—one that the forces of democracy will ultimately defeat—or whether we are observing a more gradual, long-term erosion in the quality of American democracy. For now, we have to reserve judgment.
Mistakes are much easier to identify in retrospect than as they are happening. One could argue that Trump has made many mistakes, and one could equally argue that leaders of democratic forces in the US have made many mistakes as well. Mistakes are universal and ubiquitous. Not all mistakes lead to the collapse of a regime—far from it.
For that reason, it is difficult to look at the US system and identify a single fateful mistake whose consequences we will clearly see five years from now. The main message of that article, for the current situation is this: we should not assume that everything is rational or part of a carefully crafted plan. Mistakes can be forces for good when they contribute to the failure of anti-democratic politicians and regimes. But mistakes can also be forces for harm when they enable or empower authoritarian actors.
Trump Fits the Family of Charismatic Populists
This editorial image, captured in Belgrade, Serbia, showcases an array of novelty socks featuring the likenesses of Vladimir Putin, Aleksandr Lukashenko, Viktor Orban, and Donald Trump in Belgrade, Serbia on December 12, 2024. Photo: Jerome Cid.
Comparatively, how should we distinguish Trump’s personalization of power from Latin American charismatic populism (e.g., Chávez) and from the more bureaucratized authoritarianism of leaders like Putin or Orbán?
Professor Daniel Treisman: Clearly, Trump isn’t very good at bureaucracy. There are some people in his administration who do bureaucracy well—Russell Vought, head of the Office of Management and Budget, for example—and that is why they have had a greater impact on the federal bureaucracy than in Trump’s first term. But as an individual, Trump is clearly not a very systematic bureaucratic operator.
In that respect, he is more like charismatic populists. Putin does not have this kind of anarchic character, and Orbán is also much more systematic and skilled in statecraft and bureaucratic politics—although, of course, Orbán is also an effective populist and could be described by some as charismatic.
With regard to Chávez and other Latin American populists, Trump is obviously not quite like the left-wing populists of Latin America. Chávez had a revolutionary, Bolivarian discourse and a semi-Marxist worldview, and he maintained close emotional and political ties with other left-wing administrations across Latin America and Central America. That is quite different from Trump. Trump, after all, arrested the leader of the regime that evolved out of Chávez’s rule.
That said, there are right-wing populists in Latin America as well—Bolsonaro, for example—who are much more similar to Trump. Although Bolsonaro has more of a military background, in terms of personality and political approach Trump is closer to that type. Even when compared with left-wing populists like Chávez, Trump shares the fact that he is a populist who appeals—at least rhetorically, if not always through policy—to the masses of ordinary people whom he claims have been neglected and disrespected. That was also a central part of Chávez’s appeal.
So, I would say that Trump is distinctive in many ways, but he also clearly fits within the broader family of charismatic populists.
History Does Not Come with Labels
Finally, drawing on your work on predictability and early warning, which indicators should scholars prioritize to distinguish between episodic democratic stress and the onset of durable authoritarian transformation?
Professor Daniel Treisman: I should say at the outset that my work on predictability and prediction is quite limited, but I have been thinking about what is a philosophically deep question: the difference between trends and cycles. And I think the basic answer is that there is no definitive answer. You cannot know whether what appears to be changing at a particular moment represents a shift in the underlying trend—a breakpoint toward a new trajectory—or merely a cyclical fluctuation.
We see this across many spheres. If we look at the spread of democracy over the past 200 to 250 years—focusing here on the West, on Europe and the Americas—we observe both a very strong upward trajectory, from almost no democracies (depending, of course, on how one defines democracy) to a much larger number of countries that can be considered at least electoral democracies.
At the same time, we have seen waves: periods in which the share of democracies increases, followed by periods in which it declines or at least plateaus. In each of these moments of cyclical slowdown or reversal, people have proclaimed, “This is the end of democracy.” In every reverse wave, there has been fear that what we were witnessing was not just a cycle but a permanent shift away from democracy as a long-term reality. So far, those fears have been proven wrong in each case.
That said, I do not think there is any particular indicator or observational technique that can reliably tell us whether a change will be permanent or temporary. This reflects a deep feature of the world we live in and of our ability to understand history from within, rather than in retrospect. Looking backward, it is easy to apply statistical tests or analytical frameworks to determine whether a change was cyclical or represented a trend shift—it is almost trivial. But as history unfolds, I do not think there is any way to know for sure whether we are seeing something genuinely new or something that is repeating in a familiar pattern.
Different scholars have developed different mental models of the world, emphasizing one perspective or the other. Some believe in progress; others emphasize stagnation or endless repetition. This tension has run through Western philosophy and social science from the very beginning. My own position is to emphasize the high degree of uncertainty involved, and to push back against claims that we can clearly identify a change in the trend when it may well be a change in the cycle.
This is why I have written critically about responses to what some describe as a democratic recession, or even a reverse wave of democracy, in recent years. I think the evidence has not—or at least has not yet—fully supported such claims. There is growing evidence of a slowdown in the rate of democratic advance, and probably some degree of average backsliding. But there is an important distinction between backsliding and the long-term collapse of democracy.
So, we all need to remain attentive to this distinction and recognize that events, as they unfold, do not come with easily readable labels. We should have some respect for long-term trends, without assuming that they will automatically continue. There does seem to be a certain structural logic at work in many domains. The same is true of the stock market: there are both trends and cycles, and it is impossible to know on any given day whether a sharp drop is cyclical or part of a new trend. As we know, people have made—and lost—trillions of dollars betting on precisely that distinction.
Please cite as: Syvak, Nikoletta. (2026). “Post-Truth Populism: A New Political Paradigm.” ECPS Book Reviews. European Center for Populism Studies. January 19, 2026. https://doi.org/10.55271/br0025
This review assesses Post-Truth Populism: A New Political Paradigm (2024), edited by Saul Newman and Maximilian Conrad, a timely and theoretically ambitious contribution to the study of contemporary populism. The volume advances the argument that post-truth populism is not merely about political lying, but about a deeper transformation in the status of facts, expertise, and epistemic authority in democratic life. Combining political theory, media studies, and comparative analysis, the book conceptualizes post-truth populism as an epistemic struggle in which claims to “truth” are grounded in identity and moral antagonism rather than verification. While the collection’s conceptual breadth sometimes comes at the expense of analytical coherence, it offers valuable insights into how populism reshapes knowledge, trust, and democratic governance in an era of information disorder.
Reviewed by Nikoletta Syvak*
This book review examines the edition 2024 – Post-Truth Populism: A New Political Paradigm, edited by Saul Newman and Maximilian Conrad, which explores the relationship between populism and post-truth in contemporary politics. The book offers an interpretation of post-truth populism (PTP) as a stable political complex in which anti-elitist mobilization logic is combined with a crisis of trust in expert knowledge and institutional sources of information. The review evaluates the central thesis of the collection, its place in political science literature, the quality of its arguments and empirical evidence, as well as its methodological strengths and limitations. It concludes that the book makes a significant contribution to the study of populism and political communication, although a unified conceptual framework is not always maintained at the level of individual chapters.
The main thesis of the collection is that post-truth is not limited to “lies in politics,” but reflects a change in the status of facts and expertise in the public sphere. The editors emphasize that populism has epistemic potential: the opposition between “the people” and “the elites” turns into a conflict between “the truth of the people” and “the manipulation of the elites,” where plausibility is subordinated to political identity (p. 4). In this sense, post-truth populism can be understood as a form of politics that not only ignores facts but actively redefines the conditions under which facts become legitimate in the first place. Particularly important is the idea that post-truth should be understood not as relativism, but as a kind of “truth fundamentalism”: actors can reject verifiable data while offering their own “only true” reality (p. 8).
The book is organized into four sections: theoretical debates about PTP, followed by chapters on political communication and media, counter knowledge and conspiracy narratives, and finally, the consequences for democracy (pp. 11-16). Thus, the collection combines political theory, media studies, and comparative politics, showing that post-truth politics concerns not only information bubbles but also the transformation of democratic institutions.
First, the book clearly positions itself within the political science literature on populism. The editors use an approach in which populism is understood as a “thin-centered ideology” based on a moral division of society into “pure people” and “corrupt elites” (p. 4). However, the collection also draws on the more recent “epistemic turn” in populism studies, which views populist politics as a struggle over knowledge, trust, and authority (p. 1). This allows the book to go beyond interpretations of populism exclusively as an electoral strategy or a reaction to economic crises.
Second, methodologically, the book is an edited volume, which means it includes different approaches. Qualitative methodology dominates conceptual analysis, a discursive approach, and case-oriented argumentation. However, the collection is not limited to theory. For example, the section on communication and media includes a study that uses experimental design to test how populist messages influence the perception of facts and the tendency toward “factual relativism.” This strengthens the book’s evidence base and shows that the PTP framework can be operationalized and tested, rather than just discussed at the level of metaphor.
Thirdly, the quality of writing and clarity of argumentation are generally high. The introduction provides a good introduction to the problem, quickly identifies its empirical relevance, and explains why post-truth populism cannot be reduced to moral condemnation of politicians. At the same time, it should be noted that some chapters in the collection may be theoretically dense and difficult for readers without prior knowledge: this is a typical feature of edited volumes, where a uniform style is not guaranteed.
Finally, the main question is how convincing the argument is and why it is important for us to pay attention to it. The strength of the book lies in its demonstration that PTP is not only about “fakes” and manipulation, but also about the erosion of trust as a resource of democratic governance. If citizens no longer share basic procedures for determining facts, rational public debate becomes impossible, and politics turns into a competition of moral narratives and identities. In this sense, the book raises a fundamentally important topic for contemporary political science
However, there are limitations. The term “post-truth populism” may be too broad and applicable to too many different phenomena, from anti-elite rhetoric to conspiracy theories and platform disinformation.
Furthermore, the claim of a “new paradigm” requires strict criteria: what exactly distinguishes PTP from mere populism plus media scandals? The collection presents a compelling formulation of the problem but does not always offer a single set of verifiable criteria that would allow PTP to be clearly distinguished from other forms of political communication.
Conclusion
Overall, the book makes a significant contribution to political science: it shows that populism should be analyzed not only as an ideology or mobilization strategy, but also as epistemic politics-the struggle for the legitimacy of knowledge and the right to “truth” in the public sphere (pp. 4-8). Despite its methodological heterogeneity and risk of conceptual vagueness, the collection is useful for researchers of populism, political communication, democratic theory, and the crisis of trust. The main merit of the book is its ability to explain why post-truth populism has become not a temporary anomaly but a symptom of structural changes in modern democracies.
(*) Nikoletta Syvak is a Graduate Student, Department of Political Science and International Relations, East China Normal University (ECNU). Email: syvaknikoletta@gmail.com
Newman, Saul & Conrad, Maximilian (eds.). Post-Truth Populism: A New Political Paradigm. Cham: Palgrave Macmillan, 2024. 349 pp. ISBN: ISSN 2946-6016
While not elaborating each step in detail, Professor Diamond underscored the critical importance of electoral manipulation and control, identifying it as the decisive stage in authoritarian consolidation. He noted that this dimension often determines whether democratic decline becomes entrenched, referencing recent developments in Hungary as a salient example. Turning to the United States, Professor Diamond traced the evolution of authoritarian tendencies under Donald Trump, emphasizing both continuity from the first term and new developments in the second.
US President Donald Trump held a campaign rally at PPG Paints Arena in Pittsburgh, Pennsylvania, on November 4, 2024. Photo: Chip Somodevilla.[/caption]
