Beyond the machine: risk, fear, optimism and the foundations of public trust in AI - Steven David Pickering; Martin Ejnar Hansen; Yosuke Sunahara (AI & SOCIETY, 2026)
Abstract What drives public trust in artificial intelligence (AI)? This study examines the individual and institutional foundations of AI trust across two contrasting democracies: Japan and the United Kingdom. Drawing on original survey data ( N = 3235), we test a set of hypotheses derived from trust-transfer perspectives and self-efficacy research, covering institutional trust, AI self-efficacy, technological optimism, perceived societal threat, and job displacement anxiety. The results show that trust in AI is shaped by both psychological predispositions and broader beliefs about the trustworthiness of political and scientific institutions. Trust in government, university scientists, and other people consistently predicts AI trust in both countries, even when controlling for demographic and attitudinal variables. While optimism about AI’s benefits increases trust in both contexts, fear of AI plays a stronger negative role in the UK. Unexpectedly, the belief that AI will replace one’s job is positively associated with trust in Japan but unrelated in the UK. These findings highlight how national context shapes public confidence in emerging technologies and point to the importance of governance frameworks that foster informed capability and institutional legitimacy.