Who Trusts AI in Europe? Class and Government Views Shape Public Opinion

The European Union has staked its technological future on a bold wager: that it can become the world’s first-mover in artificial intelligence by writing the rules that everyone else will eventually follow. But a new study suggests that the success of this regulatory project may hinge on something far less glamorous than legal drafting — whether ordinary Europeans actually trust the technology and the governments that oversee it. Research published in the journal Global Public Policy and Governance by Colt Jensen of Georgia Southern University and Charlie Chen of Appalachian State University draws on large-scale survey data to map exactly which groups of EU residents are most skeptical of AI, and the results reveal fault lines that policymakers cannot afford to ignore.

The study rests on a deceptively simple premise drawn from democratic theories of policy implementation: laws and regulations succeed more often when the administrators who carry them out understand the distinctive characteristics and demands of the governed. Applied to artificial intelligence, this means the EU’s ambitious AI agenda — including its landmark regulatory framework — depends on knowing which citizens view the technology with suspicion and why. If large segments of the public distrust AI, or distrust the institutions deploying and regulating it, compliance becomes harder, public resistance grows, and the promised benefits of first-mover adoption may never materialize.

To answer the question, the researchers turned to Eurobarometer 95.2, a survey conducted in 2021 that measured European citizens’ knowledge of and attitudes toward science and technology during the COVID-19 pandemic. Eurobarometer surveys are the European Commission’s standard instrument for gauging public opinion across member states, and the 95.2 wave included detailed questions about how respondents perceived the impacts of AI on society and the economy. The dataset and all question wording are publicly available, allowing the authors to test associations between demographic characteristics, institutional attitudes, science engagement, and AI perceptions across the Union.

The central findings are striking in their clarity. Individuals who hold positive views of EU-level governments tend to hold more favorable views of artificial intelligence. This association matters enormously in the European context, because it is precisely the EU institutions — the Commission, the Parliament, and the member-state regulators acting under EU law — that serve as the primary AI regulators. A citizen who is skeptical of Brussels is, in effect, skeptical of the referee assigned to police the technology. The study thus links a well-documented phenomenon in European politics, the persistence of Euroscepticism, directly to the emerging politics of algorithmic governance.

Equally significant is the role of social class. The researchers found that people in higher social classes tend to have more positive perceptions of AI’s impacts. This class gradient echoes a long tradition in social science research showing that policy attitudes are stratified by socioeconomic position, and it raises uncomfortable questions about who stands to benefit from the AI transition. If working-class and lower-income Europeans view artificial intelligence with greater suspicion — perhaps because they perceive greater risks to their jobs, their communities, and their autonomy — then a top-down regulatory strategy crafted largely by and for educated elites risks deepening existing divides rather than bridging them.

The third pillar of the study concerns engagement with science and technology. Respondents who attended science museums and public meetings about science were associated with more favorable views of AI, as were those who expressed a preference for involving non-experts in scientific decision-making. This latter finding is particularly intriguing: it suggests that people who believe ordinary citizens should have a voice in science policy are not reflexively anti-technology. Instead, participation itself appears to breed confidence. Exposure to scientific institutions and ideas, whether through a museum visit or a town-hall discussion, seems to demystify technologies like AI and soften public apprehension.

Taken together, these findings expose a dual trust deficit that threatens the implementation of existing EU AI policies. On one side stands a class divide, in which the populations most likely to be affected by automation and algorithmic decision-making express the least enthusiasm for the technology. On the other side stands an institutional divide, in which citizens who distrust the EU and national governments extend that distrust to the AI systems those governments are charged with overseeing. The authors argue that both deficits pose genuine problems for policy implementation, because democratic legitimacy is not merely a matter of passing well-designed legislation — it requires that the governed accept and support what is being done in their name.

The remedy the study proposes is procedural rather than technological. By transparently engaging citizens in meetings on the topic of AI, and by including non-experts in the development of AI use cases, governments may be able to improve public views of the technology. This recommendation aligns with a growing body of research on transparency and trust, which has found that explaining how automated decisions are made can increase the perceived trustworthiness of algorithmic systems, and that transparency in government generally strengthens citizens’ confidence in public institutions. It also resonates with the citizen-science movement, which has demonstrated that involving laypeople in genuine research activities builds both scientific literacy and goodwill toward scientific institutions.

The stakes of getting this right extend well beyond Europe’s borders. The EU has positioned itself as a global standard-setter in AI governance, and its regulatory approach is already influencing lawmakers in other jurisdictions. But regulatory leadership is fragile if domestic publics are not on board. Previous technology policy debacles — from troubled government website rollouts to public backlash against automated decision systems in welfare administration — illustrate how quickly implementation can falter when citizens perceive systems as opaque, imposed, or unaccountable. The study’s findings suggest that the EU’s first-mover advantage depends as much on sustained public engagement as on legislative craftsmanship.

For the scientists and policymakers watching this space, the message is clear: artificial intelligence governance is not only a technical or legal challenge but a social one. The people least trusting of AI in Europe are those with less confidence in government and lower social standing, and the most promising path to winning them over runs through transparency, participation, and genuine inclusion of non-expert voices in shaping how AI is used. If the EU can close these trust deficits, it may yet convert its regulatory ambition into democratic legitimacy — and if it cannot, the first-mover advantage it seeks may prove elusive, no matter how sophisticated its rulebook becomes.

Subject of Research: Public trust in artificial intelligence and its implications for EU AI policy implementation

Article Title: Governing AI in the EU: public perception, policy dilemmas, and the path forward

Article References: Jensen, C., & Chen, C. (2025). Governing AI in the EU: public perception, policy dilemmas, and the path forward. Global Public Policy and Governance, 5(2), 162-185. https://doi.org/10.1007/s43508-025-00114-y

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00114-y

Keywords: artificial intelligence, European Union, public trust, AI regulation, Eurobarometer, social class, Euroscepticism, science engagement, policy implementation, citizen participation, algorithmic governance, public perception