Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Othmar Lehner*, Kim Ittonen, Hanna Silvola, Eva Ström, Alena Wührleitner

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Abstract
Purpose – This paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest’s four-component model of antecedents for
ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners.
Design/methodology/approach – This research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning
the years 2015–2020. This review’s narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods.
Findings – In the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest’s component model of antecedents for ethical decision-making as a stable
framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI.
Originality/value – This paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest’s model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.
Original languageEnglish
Peer-reviewed scientific journalAccounting, Auditing & Accountability Journal
Volume35
Issue number9
Pages (from-to)109-135
ISSN1368-0668
DOIs
Publication statusPublished - 2022
MoE publication typeA1 Journal article - refereed

Keywords

  • 512 Business and Management
  • Rest
  • Artificial intelligence (AI)
  • Decision-making
  • Ethics
  • Accounting

Areas of Strength and Areas of High Potential (AoS and AoHP)

  • AoS: Financial management, accounting, and governance

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