Date of Award

Spring 5-24-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Information Systems

First Advisor

Craig Van Slyke

Abstract

As artificial intelligence (AI) systems become increasingly embedded in auditing processes, questions arise regarding how professional auditors perceive and allocate responsibility for AI-assisted decisions. This study investigates the effects of AI explainability and auditors’ perceived autonomy on perceived responsibility in the context of audit decision-making. Drawing on theories of moral responsibility and professional judgment, the study employs a 2x2 experimental design using hypothetical audit scenarios to manipulate levels of AI explainability and auditors’ autonomy. Hierarchical regression analysis reveals that perceived autonomy statistically significantly increases auditors’ perception of responsibility for AI-assisted decisionmaking, whereas AI explainability is not a significant predictor. Additionally, professional identity emerges as a significant factor shaping auditors’ perceived responsibility, highlighting the importance of self-concept in responsibility attribution. A follow-up qualitative analysis of participants’ open-ended textual responses further explores the rationale behind responsibility judgements. The findings not only validate the quantitative results but also offer nuanced insights into auditors’ cognitive reasoning when working with AI. The study contributes to our understanding of users’ perception of responsibility in human-AI collaboration in professional settings. It also offers practical implications for audit firms, educators, and regulators aiming to ensure responsible AI adoption.

Download

Share

COinS