Artificial Intelligence in Policing and Perceived Legitimacy: Does Gender Representation Make a Difference?

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Abstract
As artificial intelligence (AI) increasingly transforms public administration, understanding its impact on perceived legitimacy becomes paramount, particularly, in high‐stakes areas such as policing. While existing research offers mixed evidence on whether government AI use enhances or undermines citizens' perceptions of fairness and trust, the conditions moderating these effects remain underexplored. Drawing on representative bureaucracy theory, this study uses a survey experiment to investigate how gender representation moderates the effect of AI use on citizens' perceived fairness and trust in domestic violence units (DVUs). Results show that female representation positively moderates the legitimacy impact of a DVU's AI use; whereas AI use decreases female respondents' perceived fairness and trust in male‐dominated DVUs, these negative effects disappear in female‐dominated DVUs. Our findings identify representation as a key context shaping citizens' responses to government AI use, extending representative bureaucracy theory by demonstrating its indirect symbolic effects.

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