Unpacking the Intersection of Political Trust and AI Regulation: A Literature Review

The regulation of artificial intelligence (AI) is a complex topic, characterised by divergent perspectives and a lack of clarity, particularly regarding the balance between fostering innovation and ensuring safety and societal well-being. As global authorities consider various approaches and trade-offs, the rapid advancement in AI and its integration into everyday life have raised concerns, ranging from job displacement to the use of lethal autonomous weapons. Consequently, public trust has emerged as a critical topic in discussions about AI, frequently appearing in international guidelines and national strategies. Nonetheless, recent studies identify a concerning trend within national AI strategies whereby public trust is treated as a strategic instrument to secure adoption, investment and global leadership, rather than as a reflection of genuinely trustworthy systems. Such a narrative risks diverting attention from essential conditions such as transparency, accountability and demonstrated effectiveness. Building trustworthy AI requires governments capable of defining its parameters in a credible, efficient, and transparent manner. Contemporary democracies, however, are facing a context of declining political trust in representative institutions, which can undermine regulatory legitimacy and public acceptance. Drawing on a literature review, this theoretical study examines the bidirectional relationship between political trust and AI regulation, exploring how political trust influences regulatory acceptance and effectiveness, while investigating how AI regulation may, over time, affect political trust. It argues that regulatory strategies should prioritise ensuring systems are genuinely trustworthy, rather than focusing on public trust. By doing so, the paper contributes to debates on political trust and AI governance, advancing understanding of the democratic legitimacy and effectiveness of AI regulation.