Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence

Benjamin P. Commerford, Sean A. Dennis, Jennifer R. Joe, Jenny W. Ulla

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Audit firms are investing billions of dollars to develop artificial intelligence (AI) systems that will help auditors execute challenging tasks (e.g., evaluating complex estimates). Although firms assume AI will enhance audit quality, a growing body of research documents that individuals often exhibit “algorithm aversion”—the tendency to discount computer-based advice more heavily than human advice, although the advice is identical otherwise. Therefore, we conduct an experiment to examine how algorithm aversion manifests in auditor judgments. Consistent with theory, we find that auditors receiving contradictory evidence from their firm's AI system (instead of a human specialist) propose smaller adjustments to management's complex estimates, particularly when management develops their estimates using relatively objective (vs. subjective) inputs. Our findings suggest auditor susceptibility to algorithm aversion could prove costly for the profession and financial statements users.

Original languageEnglish
Pages (from-to)171-201
Number of pages31
JournalJournal of Accounting Research
Volume60
Issue number1
DOIs
StatePublished - Mar 2022

Bibliographical note

Funding Information:
Accepted by Rodrigo Verdi. This paper benefited from thoughtful comments from an anonymous associate editor and an anonymous reviewer. We thank Sanaz Aghazadeh, Tim Bauer, Jessica Buchanan, Jon Grenier, Rick Hatfield, Sean Hillison, Blake Holman, Khim Kelly, Jared Koreff, Tamara Lambert, Justin Leiby, Curtis Mullis, EB Poziemski, Greg Trompeter, and Aubrey Whitfield as well as workshop participants at the University of Alabama, Baruch College, the University of Central Florida, the University of Kansas, and Kent State University for their helpful comments. We also appreciate the feedback received from participants at the University of Waterloo Centre for Accounting Ethics’ 2019 Ethics Symposium, 2019 PCAOB/TAR Conference on Auditing and Capital Markets, 2020 Hawaii Accounting Research Conference, and 2020 Auditing Section Midyear Conference. We also thank the audit firms that provided participants for this study and gratefully acknowledge funding from the Von Allmen School of Accountancy at the University of Kentucky.

Publisher Copyright:
© 2021 The Chookaszian Accounting Research Center at the University of Chicago Booth School of Business

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

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