Artificial Intelligence and Ethical Decision-Making in Accounting and Auditing: Analysis of Related Challenges
Subject Areas :
Yashar
Azarsaeed
1
(M.A. in Economics, Payam Noor University, Karaj Branch, Alborz, Iran)
Shoeyb
Rostami
2
(Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran. Corresponding Author)
Received: 2023-07-09
Accepted : 2023-08-30
Published : 2023-09-23
Keywords:
challenges,
Future of accounting,
Abstract :
AbstractThis article examines the ethical challenges of using accounting systems based on artificial intelligence for decision-making and presents the correct decision-making in the framework of the four-component model of Rest. The following article contributes to the literature related to accounting as a mental act as well as the function of an intermediary in the 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. The topic has been reviewed among 138 articles from 43 prestigious international accounting journals between 2015 and 2020. In the thematic coding of the selected articles, five major ethical challenges of decision-making based on artificial intelligence in accounting were identified, which are: impartiality, privacy, transparency, accountability and reliability. By using the components of the Rest model for ethical decision-making as a stable framework for the discussed structure, the challenges and their relevance for future human-machine cooperation in various offices between humans and artificial intelligence can be discussed. Therefore, in addition to understanding the appropriate decision-making process in accounting based on artificial intelligence, it is suggested that independent and internal audit processes be adapted in terms of skills and knowledge to ensure ethical decision-making based on artificial intelligence
References:
فهرست منابع
احمدزاده، زاهد و احمد یعقوب نژاد، (1401)، "تأثیر درک حسابرسان از فرهنگ اخلاقی حاکم در مؤسسات بر ارزشهای حرفهای در مؤسسات حسابرسی"، پژوهشهای حسابداری مالی و حسابرسی، 14(55)، صص 23-40.
حسینزاده، امیر، رسول عبدی، عسگر پاک مرام و نادر رضایی، (1401)، "الگوی تصمیم‌گیری اخلاقی حسابداری"، اخلاق در علوم و فناوری، 17، صص 180-152.
خوشبخت، اسماعیل، امیرحسین تائبی نقندری و حدیث زینلی، (1401)، "دینداری، اخلاق حرفهای حسابداران و تقلب‌های گزارشگری مالی"، پژوهشهای حسابداری مالی و حسابرسی، 14(53)، صص 223-254.
کریمی، اکرم، رویا دارابی، محمدرضا پورفخاران و حسین مقدم، (1401)، "پیش‌بینی رتبه‌بندی کیفیت اطلاعات با رویکرد تحلیل عاملی و هوش مصنوعی"، پژوهشهای حسابداری مالی و حسابرسی، 14(54)، صص 101-140.
نوشفر، علیداد، عبدالرضا محسنی و مصطفی قاسمی، (1401)، "الگویی برای بهبود تصمیم‌گیری اخلاقی در حرفه حسابداری با رویکرد مبتنی بر نظریه داده بنیاد"، پژوهشهای تجربی حسابداری، 12(4)، صص 141-160.
_||_
Albu, O.B. and Flyverbom, M. (2016), “Organizational transparency: conceptualizations, conditions, and consequences”, Business and Society, Vol. 58 No. 2, pp. 268-297.
Baud, C., Brivot, M. and Himick, D. (2019), “Accounting ethics and the fragmentation of value”, Journal of Business Ethics, Vol. 168 No. 2, pp. 373-387.
Bebbington, J., Osterblom, H., Crona, B., Jouffray, J.-B., Larrinaga, C., Russell, S. and Scholtens, B. € (2019), “Accounting and accountability in the Anthropocene”, Accounting, Auditing and Accountability Journal Vol. 33 No. 1, pp. 152-177.
Boza, P. and Evgeniou, T. (2021), Implementing AI Principles: Frameworks, Processes, and Tools, INSEAD Fontainbleau, pp. 1-31.
Cooper, L.A., Holderness, D.K., Sorensen, T.L. and Wood, D.A. (2019), “Robotic process automation in public accounting”, Accounting Horizons, Vol. 33 No. 4, pp. 15-35.
Daugherty, P.R., Wilson, H.J. and Chowdhury, R. (2019), “Using artificial intelligence to promote diversityMIT Sloan Management Review, Vol. 60 No. 2, p. 1.
Dignum, V. (2018), “Ethics in artificial intelligence: introduction to the special issue”, Ethics and Information Technology, Vol. 20 No. 1, pp. 1-3.
Dillard, J. and Vinnari, E. (2019), “Critical dialogical accountability: from accounting-based accountability to accountability-based accounting”, Critical Perspectives on Accounting, Vol. 62, pp. 16-38.
Earley, C.E. (2015), “Data analytics in auditing: opportunities and challenges”, Business Horizons, Vol. 58 No. 5, pp. 493-500.
Gepp, A., Linnenluecke, M.K., O’Neill, T.J. and Smith, T. (2018), “Big data techniques in auditing research and practice: current trends and future opportunities”, Journal of Accounting Literature, Vol. 40, pp. 102-115.
Glikson, E. and Woolley, A.W. (2020), “Human trust in artificial intelligence: review of empirical researchAcademy of Management Annals, Vol. 14 No. 2, pp. 627-660..
Gong, J.J. (2016), “Ethics in accounting: a decision-making approach”, Journal of Business Ethics, Vol. 142 No. 3, pp. 621-623.
Gunz, S. and Thorne, L. (2020), “Thematic symposium: the impact of technology on ethics, professionalism and judgement in accounting”, Journal of Business Ethics, Vol. 167 No. 2, pp. 153-155.
Holt, T.P. and Loraas, T.M. (2021), “A potential unintended consequence of big data: does information structure lead to suboptimal auditor judgment and decision-making?”, Accounting Horizons, Vol. 35 No 3, pp. 161-186.
Jarrahi, M.H. (2018), “Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making”, Business Horizons, Vol. 61 No. 4, pp. 577-586.
Jeacle, I. and Carter, C. (2014), “Creative spaces in interdisciplinary accounting research”, Accounting Auditing and Accountability Journal, Vol. 27 No. 8, pp. 1233-1240.
Kellogg, K.C., Valentine, M.A. and Christin, A. (2020), “Algorithms at work: the new contested terrain of control”, Academy of Management Annals, Vol. 14 No. 1, pp. 366-410.
Kovacova, M., Kliestik, T., Pera, A., Grecu, I. and Grecu, G. (2019), “Big data governance of automated algorithmic decision-making processes”, Review of Contemporary Philosophy, Vol. 18, pp. 126-132.
Long, C.P. and Sitkin, S.B. (2018), “Control–trust dynamics in organizations: identifying shared perspectives and charting conceptual fault lines”, Academy of Management Annals, Vol. 12 No. 2, pp. 725-751.
Lehner, O., Forstenlechner, C., Leitner-Hanetseder, S. and Eisl, C. (2021), “Artificial intelligence driven accounting as nascent field: on significant, legitimation and domination”, American Accounting Association Annual Meeting (AAA).
Leyer, M. and Schneider, S. (2021), “Decision augmentation and automation with artificial intelligence: threat or opportunity for managers?”, Business Horizons, Vol. 64 No. 5, pp. 711-724.
Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I. and Kasper, G. (2019) “The challenges of algorithm-based HR decision-making for personal integrity”, Journal of Business Ethics, Vol. 160 No. 2, pp. 377-392.
Lindebaum, D., Vesa, M. and den Hond, F. (2020), “Insights from ‘the machine stops’ to better understand rational assumptions in algorithmic decision making and its implications for organizations”, Academy of Management Review, Vol. 45 No. 1, pp. 247-263.
Lombardi, D., Issa, H. and Brown-Liburd, H. (2015), “Behavioral implications of big data’s impact on audit judgment and decision making and future research directions”, Accounting Horizons, Vol. 29 No. 2, pp451-468.
Losbichler, H. and Lehner, O.M. (2021), “Limits of artificial intelligence in controlling and the ways forward a call for future accounting research”, Journal of Applied Accounting Research, Vol. 22 No. 2, pp. 365-382.
Manetti, G., Bellucci, M. and Oliva, S. (2021), “Unpacking dialogic accounting: a systematic literature review and research agenda”, Accounting, Auditing and Accountability Journal, Vol. 34 No. 9, pp. 250-283.
Martin, K. (2019), “Ethical implications and accountability of algorithms”, Journal of Business Ethics, Vol 160 No. 4, pp. 835-850.
McManus, J. (2018), “Hubris and unethical decision making: the tragedy of the uncommon”, Journal of Business Ethics, Vol. 149 No. 1, pp. 169-185.
Munoko, I., Brown-Liburd, H.L. and Vasarhelyi, M. (2020), “The ethical implications of using artificial intelligence in auditing”, Journal of Business Ethics, Vol. 167 No. 2, pp. 209-234.
Orlikowski, W.J. and Scott, S.V. (2008), “Sociomateriality: challenging the separation of technology, work and organization”, Academy of Management Annals, Vol. 2 No. 1, pp. 433-474.
Parker, L.D. and Northcott, D. (2016), “Qualitative generalising in accounting research: concepts and strategies”, Accounting, Auditing and Accountability Journal, Vol. 29 No. 6, pp. 1100-1131.
Raisch, S. and Krakowski, S. (2021), “Artificial intelligence and management: the automation– augmentation paradox”, Academy of Management Review, Vol. 46 No. 1, pp. 192-210.
Rest, J.R. (1986), Moral Development: Advances in Research and Theory, Praeger, New York, p. 224.
Rest, J.R. (1994), Moral Development in the Professions: Psychology and Applied Ethics, Psychology. PressHillsdale, NJ.
Silvola, H. and Vinnari, E. (2021), “The limits of institutional work: a field study on auditors’ efforts to promote sustainability assurance in a trust society”, Accounting, Auditing and Accountability Journal, Vol. 34, 1, pp. 1-3.
Snyder, H. (2019), “Literature review as a research methodology: an overview and guidelines”, Journal of Business Research, Vol. 104, pp. 333-339.
Sun, T. (2019), “Applying deep learning to audit procedures: an illustrative framework”, Accounting Horizons, Vol. 33 No. 3, pp. 89-109.
TerBogt, H.J. and Scapens, R.W. (2019), “Institutions, situated rationality and agency in management accounting”, Accounting, Auditing and Accountability Journal, Vol. 32 No. 6, pp. 1801-1825.
West, S.M. (2019), “Data capitalism: redefining the logics of surveillance and privacy”, Business and SocietyVol. 58 No. 1, pp. 20-41.
