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Citizens' acceptance of artificial intelligence in public services: Evidence from a conjoint experiment about processing permit applications

感知 经验证据 政府(语言学) 情感(语言学) 联合分析 透明度(行为) 营销 业务 计算机科学 心理学 经济 偏爱 计算机安全 哲学 语言学 沟通 认识论 神经科学 微观经济学
作者
László Horváth,Oliver James,Susan Banducci,Ana Beduschi
出处
期刊:Government Information Quarterly [Elsevier]
卷期号:40 (4): 101876-101876 被引量:25
标识
DOI:10.1016/j.giq.2023.101876
摘要

Citizens' acceptance of artificial intelligence (AI) in public service delivery is important for its legitimate and effective use by government. Human involvement in AI systems has been suggested as a way to boost citizens' acceptance and perceptions of these systems' fairness. However, there is little empirical evidence to assess these claims. To address this gap, we conducted a pre-registered conjoint experiment in the UK regarding acceptance of AI in processing public permits: for immigration visas and parking permits. We hypothesise that greater human involvement boosts acceptance of AI in decision-making and associated perceptions of its fairness. We further hypothesise that greater human involvement mitigates the negative impact of certain AI features, such as inaccuracy, high cost, or data sharing. From our study, we find that more human involvement tends to increase acceptance, and that perceptions of fairness were less influenced. Yet, when substantial human discretion was introduced in parking permit scenarios, respondents preferred more limited human input. We found little evidence that human involvement moderates the impact of AI's unfavourable attributes. System-level factors such as high accuracy, the presence of an appeals system, increased transparency, reduced cost, non-sharing of data, and the absence of private company involvement all boost both acceptance and perceived procedural fairness. We find limited evidence that individual characteristics affect these results. The findings show how the design of AI systems can increase its acceptability to citizens for use in public services.
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