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

Author

Listed:
  • Othmar Manfred Lehner
  • Kim Ittonen
  • Hanna Silvola
  • Eva Ström
  • Alena Wührleitner

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.

Suggested Citation

  • Othmar Manfred Lehner & Kim Ittonen & Hanna Silvola & Eva Ström & Alena Wührleitner, 2022. "Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 35(9), pages 109-135, June.
  • Handle: RePEc:eme:aaajpp:aaaj-09-2020-4934
    DOI: 10.1108/AAAJ-09-2020-4934
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    Citations

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    Cited by:

    1. Yixuan Peng & Sayed Fayaz Ahmad & Ahmad Y. A. Bani Ahmad & Mustafa S. Al Shaikh & Mohammad Khalaf Daoud & Fuad Mohammed Hussein Alhamdi, 2023. "Riding the Waves of Artificial Intelligence in Advancing Accounting and Its Implications for Sustainable Development Goals," Sustainability, MDPI, vol. 15(19), pages 1-12, September.
    2. Grosu, Veronica & Cosmulese, Cristina Gabriela & Socoliuc, Marian & Ciubotariu, Marius-Sorin & Mihaila, Svetlana, 2023. "Testing accountants' perceptions of the digitization of the profession and profiling the future professional," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Adrian GROȘANU & Melinda-Timea FÜLÖP & Nicolae MĂGDAȘ, 2024. "Ethical Dilemmas in Digital Accounting: A Comprehensive Literature Review," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 5(4), pages 56-67, April.
    4. Sinziana-Maria Rindasu & Ioan Dan Topor & Liliana Ionescu-Feleaga, 2023. "The Evolution of Management Accountants' Digital Skills in Industry 4.0: A Qualitative Approach," Oblik i finansi, Institute of Accounting and Finance, issue 1, pages 38-48, March.

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