Laszlo Horvath , Oliver James , Susan Banducci , Ana Beduschi
{"title":"Citizens' acceptance of artificial intelligence in public services: Evidence from a conjoint experiment about processing permit applications","authors":"Laszlo Horvath , Oliver James , Susan Banducci , Ana Beduschi","doi":"10.1016/j.giq.2023.101876","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"40 4","pages":"Article 101876"},"PeriodicalIF":7.8000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0740624X2300076X/pdfft?md5=b05b1f0ab3c85643c0f9c23138a283d8&pid=1-s2.0-S0740624X2300076X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Government Information Quarterly","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0740624X2300076X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Government Information Quarterly (GIQ) delves into the convergence of policy, information technology, government, and the public. It explores the impact of policies on government information flows, the role of technology in innovative government services, and the dynamic between citizens and governing bodies in the digital age. GIQ serves as a premier journal, disseminating high-quality research and insights that bridge the realms of policy, information technology, government, and public engagement.