Explainable Artificial Intelligence (XAI) in auditing

IF 4.1 3区 管理学 Q2 BUSINESS International Journal of Accounting Information Systems Pub Date : 2022-09-01 DOI:10.1016/j.accinf.2022.100572
Chanyuan (Abigail) Zhang , Soohyun Cho , Miklos Vasarhelyi
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引用次数: 25

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are gaining increasing attention regarding their potential applications in auditing. One major challenge of their adoption in auditing is the lack of explainability of their results. As AI/ML matures, so do techniques that can enhance the interpretability of AI, a.k.a., Explainable Artificial Intelligence (XAI). This paper introduces XAI techniques to auditing practitioners and researchers. We discuss how different XAI techniques can be used to meet the requirements of audit documentation and audit evidence standards. Furthermore, we demonstrate popular XAI techniques, especially Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP), using an auditing task of assessing the risk of material misstatement. This paper contributes to accounting information systems research and practice by introducing XAI techniques to enhance the transparency and interpretability of AI applications applied to auditing tasks.

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可解释的人工智能(XAI)在审计
人工智能(AI)和机器学习(ML)在审计中的潜在应用越来越受到关注。在审计中采用它们的一个主要挑战是其结果缺乏可解释性。随着AI/ML的成熟,可以增强AI可解释性的技术也在成熟,即可解释的人工智能(XAI)。本文向审计从业人员和研究人员介绍了XAI技术。我们将讨论如何使用不同的XAI技术来满足审计文档和审计证据标准的要求。此外,我们展示了流行的XAI技术,特别是局部可解释模型不可知解释(LIME)和Shapley加性解释(SHAP),使用评估重大错报风险的审计任务。本文通过引入人工智能技术来提高人工智能应用于审计任务的透明度和可解释性,为会计信息系统的研究和实践做出了贡献。
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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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