Algorithm aversion, emotions, and investor reaction: Does disclosing the use of AI influence investment decisions?

IF 4.1 3区 管理学 Q2 BUSINESS International Journal of Accounting Information Systems Pub Date : 2023-12-21 DOI:10.1016/j.accinf.2023.100664
Tom Downen , Sarah Kim , Lorraine Lee
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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.

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算法厌恶、情绪和投资者反应:披露人工智能的使用是否会影响投资决策?
企业越来越多地在会计系统中使用人工智能(AI),以减少不确定性并提高准确性。然而,算法厌恶(Dietvorst 等人,2015 年)表明,与人类提供的信息相比,个人往往会回避自动系统提供的信息。本文是记录人工智能情感反应的探索性一步。我们通过实验研究了披露使用人工智能而非人工估算资产公允价值如何通过降低情绪反应水平(尤其是愉快度和专注度)来影响投资决策。与算法厌恶一致,我们发现,披露使用人工智能估算资产公允价值会降低信息价值对非专业投资者反应的影响。具体来说,与披露人工智能使用情况时相比,当披露公司使用人工智能时,当公允价值信息为正时,投资者追加投资的规模较小,而当公允价值信息为负时,投资者撤回投资的规模较小。重要的是,我们还发现,情绪对信息来源(人工智能与人力)的影响具有中介作用,并缓和了信息价值对投资决策的影响。
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来源期刊
CiteScore
9.00
自引率
6.50%
发文量
23
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.
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