{"title":"Algorithm aversion, emotions, and investor reaction: Does disclosing the use of AI influence investment decisions?","authors":"Tom Downen , Sarah Kim , Lorraine Lee","doi":"10.1016/j.accinf.2023.100664","DOIUrl":null,"url":null,"abstract":"<div><p>Businesses are increasingly using artificial intelligence (AI) in accounting systems to reduce uncertainty and improve accuracy. However, algorithm aversion (Dietvorst et al., 2015) indicates that individuals often avoid information provided by automated systems as compared to that provided by humans. This paper is an exploratory step towards documenting an emotional response to AI. We experimentally investigate how disclosing the use of AI rather than human staff for estimating the fair value of an asset influences investment decisions through lower levels of emotional response, particularly in pleasantness and attentiveness. Consistent with algorithm aversion, we find that disclosing the use of AI to estimate the asset’s fair value reduces the effect of information valence on nonprofessional investor responses. Specifically, when a company’s AI usage is disclosed, investors make smaller additional investments when fair value information is positive and smaller investment withdrawals when fair value information is negative, as compared to when human staff usage is disclosed. Importantly, we also find that emotions mediate the effect of information source (AI versus human staff) and moderate the effect of information valence on investment decisions.</p></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Accounting Information Systems","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1467089523000568","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Businesses are increasingly using artificial intelligence (AI) in accounting systems to reduce uncertainty and improve accuracy. However, algorithm aversion (Dietvorst et al., 2015) indicates that individuals often avoid information provided by automated systems as compared to that provided by humans. This paper is an exploratory step towards documenting an emotional response to AI. We experimentally investigate how disclosing the use of AI rather than human staff for estimating the fair value of an asset influences investment decisions through lower levels of emotional response, particularly in pleasantness and attentiveness. Consistent with algorithm aversion, we find that disclosing the use of AI to estimate the asset’s fair value reduces the effect of information valence on nonprofessional investor responses. Specifically, when a company’s AI usage is disclosed, investors make smaller additional investments when fair value information is positive and smaller investment withdrawals when fair value information is negative, as compared to when human staff usage is disclosed. Importantly, we also find that emotions mediate the effect of information source (AI versus human staff) and moderate the effect of information valence on investment decisions.
期刊介绍:
The International Journal of Accounting Information Systems will publish thoughtful, well developed articles that examine the rapidly evolving relationship between accounting and information technology. Articles may range from empirical to analytical, from practice-based to the development of new techniques, but must be related to problems facing the integration of accounting and information technology. The journal will address (but will not limit itself to) the following specific issues: control and auditability of information systems; management of information technology; artificial intelligence research in accounting; development issues in accounting and information systems; human factors issues related to information technology; development of theories related to information technology; methodological issues in information technology research; information systems validation; human–computer interaction research in accounting information systems. The journal welcomes and encourages articles from both practitioners and academicians.