Public Perceptions of AI-Assisted Judicial Decision-Making: A Survey Study
By Marta Sztogryn,
London Metropolitan University.
This study examined public perceptions of artificial intelligence (AI)-assisted judicial decision-making, focusing on the roles of technological familiarity, trust in AI technologies, and perceived fairness. Using a vignette-based survey design, 123 UK-based participants recruited through convenience and snowball sampling evaluated a hypothetical criminal sentencing scenario in which an AI system provided recommendations to a judge.
Multiple regression and mediation analyses examined whether technological familiarity and trust in AI predicted support for AI-assisted judicial decision-making, and whether perceived fairness mediated these relationships. Results indicated that trust in AI technologies significantly predicted support, both directly and indirectly through perceived fairness. In contrast, technological familiarity did not significantly predict perceived fairness or support. Following reliability analysis, the Perceived Fairness scale was revised from four to two items to improve internal consistency.
These findings highlight perceived fairness as a key psychological mechanism underlying public acceptance of AI in judicial contexts and suggest that trust and fairness perceptions may be more influential than technical familiarity in shaping attitudes toward AI-assisted legal decision-making.
DOI: https://doi.org/10.5281/zenodo.22811037