Feeling the Algorithm: Motivated Reasoning, Status Quo Bias, and Legitimacy in AI-Enabled Border Governance

The rapid expansion of artificial intelligence and digital security infrastructures has intensified public debate about legitimacy, trust, and democratic oversight. This paper examines how citizens evaluate the legitimacy of AI-enabled governance tools, with a particular focus on public attitudes toward emerging digital border-management systems such as electronic travel authorization (ETA) schemes. Drawing on a mixed methods strategy—two survey experiments with 3,000 UK residents and two waves of interviews with 70 participants—we explore how individuals assess the legitimacy of automated systems that govern others' entry into their country. We argue that ordinary citizens lack technical understanding of how these systems function, yet form strong affective responses to them nonetheless. Our analysis identifies two emotion-laden cognitive shortcuts structuring legitimacy judgments: motivated reasoning and status quo bias. Citizens penalize systems perceived as conflicting with their policy preferences and favour familiar arrangements regardless of substantive content. We demonstrate that affective polarization plays a central role in activating these heuristics, as citizens react not only to design features but to whether systems affirm or threaten their political identities and corresponding affective states. P10