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. Professor Joan Font (IESA-CSIC) examined citizens’ conceptions of democracy in relation to artificial intelligence in administration and government, asking who, if anyone, wants 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
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?”
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, including the management of elections. 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?”
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.”
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.”
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
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
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.
