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In a scenario-based survey with N = 507 participants we investigated how perceptions of trust, fairness, accuracy, and support for specific FRT applications were influenced by general AI knowledge, trust in law enforcement, and application type. Masked face identification and kinship verification consistently received the lowest trust, fairness, accuracy, and support ratings, while face verification gathered the highest levels of acceptance. Contrary to expectations, deeper general AI knowledge was linked with decreased trust and support for FRTs in policing contexts. This suggests that technological literacy enhanced critical awareness of algorithmic limitations and ethical concerns. Participants expressed significant concerns about algorithmic bias, privacy implications, and surveillance capabilities. Trust in law enforcement emerged as the strongest predictor of FRT acceptance, indicating that acceptance of AI is embedded in broader socio-political relationships rather than determined by technological concerns alone."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"AI-driven policing"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"AI ethics"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"AI literacy"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"surveillance"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"institutional legitimacy"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Published by Elsevier Ltd. 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