Share:


Ethical concerns associated with artificial intelligence in the accounting profession: a curse or a blessing?

    Melinda Timea Fülöp   Affiliation
    ; Dan Ioan Topor Affiliation
    ; Constantin Aurelian Ionescu   Affiliation
    ; Javier Cifuentes-Faura   Affiliation
    ; Nicolae Măgdaș Affiliation

Abstract

Due to the progress of digitization and the associated use of artificial intelligence in the economic and especially the accounting field, the cooperation between man and machine is becoming increasingly prominent in society. The objective of this research to address the ethics of using artificial intelligence in the accounting firms by looking at the novel challenges that it brings to the field. The research adopted a deductive approach, starting with the basic concepts and then conducting an empirical study based on an interview. The results of the interview were processed with the Nvivo12 application, through which a thematic analysis was carried out in order to present the results. The research results indicate that most of the accountants involved in the study have a basic knowledge of artificial intelligence but that few of them fully understand the phenomenon. However, they all believe that the ethics of artificial intelligence is vital and that the involvement of regulatory bodies in ethical legislation regarding artificial intelligence is indispensable. The results obtained can serve as an X-ray of the current situation and can be used to derive practical and managerial implications.

Keyword : artificial intelligence, accounting, ethics, digitization, business environmental, accounting profession

How to Cite
Fülöp, M. T., Topor, D. I., Ionescu, C. A., Cifuentes-Faura, J. ., & Măgdaș, N. (2023). Ethical concerns associated with artificial intelligence in the accounting profession: a curse or a blessing?. Journal of Business Economics and Management, 24(2), 387–404. https://doi.org/10.3846/jbem.2023.19251
Published in Issue
Jun 20, 2023
Abstract Views
2475
PDF Downloads
2116
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Anica-Popa, I., Anica-Popa, L., Rădulescu, C., & Vrîncianu, M. (2021). The integration of Artificial Intelligence in retail: Benefits, challenges and a dedicated conceptual framework. Amfiteatru Economic, 23(56), 120–136. https://doi.org/10.24818/EA/2021/56/120

Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022). Ethical framework for Artificial Intelligence and digital technologies. International Journal of Information Management, 62, 102433. https://doi.org/10.1016/j.ijinfomgt.2021.102433

Bakarich, K. M., & O’Brien, P. E. (2021). The robots are coming… but aren’t here yet: The use of artificial intelligence technologies in the public accounting profession. Journal of Emerging Technologies in Accounting, 18(1), 27–43. https://doi.org/10.2308/JETA-19-11-20-47

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Braun, V., & Clarke, V. (2012). Thematic analysis. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology, Vol. 2: Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 57–71). American Psychological Association. https://doi.org/10.1037/13620-004

Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. Sage.

Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806

Braun, V., Clarke, V., & Weate, P. (2016). Using thematic analysis in sport and exercise research. In B. Smith & A. C. Sparkes (Eds.), Routledge handbook of qualitative research in sport and exercise (pp. 191–205). Routledge.

Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239–257. https://doi.org/10.1017/jmo.2016.55

Cedervall, Y., & Åberg, A. C. (2010). Physical activity and implications on well-being in mild Alzheimer’s disease: A qualitative case study on two men with dementia and their spouses. Physiotherapy Theory and Practice, 26, 226–239. https://doi.org/10.3109/09593980903423012

Cho, S., Vasarhelyi, M. A., Sun, T., & Zhang, C. (2020). Learning from machine learning in accounting and assurance. Journal of Emerging Technologies in Accounting, 17(1), 1–10. https://doi.org/10.2308/jeta-10718

Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283–314. https://doi.org/10.1016/j.jbusres.2020.08.019

Guşe, G. R., & Mangiuc, M. D. (2022). Digital transformation in Romanian accounting practice and education: Impact and perspectives. Amfiteatru Economic, 24(59), 252–267. https://doi.org/10.24818/EA/2022/59/252

Ionaşcu, I., Ionaşcu, M., Nechita, E., Săcărin, M., & Minu, M. (2022a). Digital transformation, financial performance and sustainability: Evidence for European Union listed companies. Amfiteatru Economic, 24(59), 94–109. https://doi.org/10.24818/EA/2022/59/94

Ionescu, A. M., Clipa, A. M., Turnea, E. S., Clipa, C. I., Bedrule-Grigoruță, M. V., & Roth, S. (2022b). The impact of innovation framework conditions on corporate digital technology integration: Institutions as facilitators for sustainable digital transformation. Journal of Business Economics and Management, 23(5), 1037–1059. https://doi.org/10.3846/jbem.2022.17039

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2

Kot, S., Hussain, H. I., Bilan, S., Haseeb, M., & Mihardjo, L. W. (2021). The role of artificial intelligence recruitment and quality to explain the phenomenon of employer reputation. Journal of Business Economics and Management, 22(4), 867–883. https://doi.org/10.3846/jbem.2021.14606

Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: Actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201

Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911–926. https://doi.org/10.1016/j.jbusres.2020.11.001

Luo, J., Meng, Q., & Cai, Y. (2018). Analysis of the impact of artificial intelligence application on the development of accounting industry. Open Journal of Business and Management, 6(4), 850–856. https://doi.org/10.4236/ojbm.2018.64063

Mayring, P. (2015). Qualitative content analysis: Theoretical background and procedures. In Approaches to qualitative research in mathematics education (pp. 365–380). Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9181-6_13

Mayring, P., & Fenzl, T. (2019). Qualitative inhaltsanalyse. In N. Baur & J. Blasius (Hrsg.), Handbuch Methoden der empirischen Sozialforschung (2. Auflage, Band 1, S. 633–648). Springer VS. https://doi.org/10.1007/978-3-658-21308-4_42

Miller, A. (2019). The intrinsically linked future for human and Artificial Intelligence interaction. Journal of Big Data, 6(1), 1–9. https://doi.org/10.1186/s40537-019-0202-7

Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using artificial intelligence in auditing. Journal of Business Ethics, 167(2), 209–234. https://doi.org/10.1007/s10551-019-04407-1

O’Kane, P., Smith, A., & Lerman, M. P. (2021). Building transparency and trustworthiness in inductive research through computer-aided qualitative data analysis software. Organizational Research Methods, 24(1), 104–139. https://doi.org/10.1177/1094428119865016

Pazarskis, M., Giovanis, N., Koutoupis, A., & Chasiotou, A. (2022). Merger decisions, accounting information and performance stability inside and outside of economic crisis periods: Evidence from Greece. Journal of Business Economics and Management, 23(5), 1170–1193. https://doi.org/10.3846/jbem.2022.17697

Pazarskis, M., Vogiatzoglou, M., Koutoupis, A., & Drogalas, G. (2021). Corporate mergers and accounting performance during a period of economic crisis: Evidence from Greece. Journal of Business Economics and Management, 22(3), 577–595. https://doi.org/10.3846/jbem.2021.13911

Ruiz-Real, J. L., Uribe-Toril, J., Torres, J. A., & De Pablo, J. (2021). Artificial intelligence in business and economics research: Trends and future. Journal of Business Economics and Management, 22(1), 98–117. https://doi.org/10.3846/jbem.2020.13641

Sena, V., & Nocker, M. (2021). AI and business models: The good, the bad and the ugly. Foundations and Trends in Technology, Information and Operations Management, 14(4), 324–397. https://doi.org/10.1561/0200000100

Smuha, N. A. (2019). The EU approach to ethics guidelines for trustworthy artificial intelligence. Computer Law Review International, 20(4), 97–106. https://doi.org/10.9785/cri-2019-200402

Smuha, N. A. (2021). From a ‘race to AI’ to a ‘race to AI regulation’: regulatory competition for artificial intelligence. Law, Innovation and Technology, 13(1), 57–84. https://doi.org/10.1080/17579961.2021.1898300

Spiekermann, S. (2015). Ethical IT innovation: A value-based system design approach. Auerbach Publications. https://doi.org/10.1201/b19060

Stahl, B., Andreou, A., Brey, P., Hatzakis, T., Kirichenko, A., Macnish, K., Laulhé Shaelou, S., Patel, A., Ryan, M., & Wright, D. (2021). Artificial intelligence for human flourishing: Beyond principles for machine learning. Journal of Business Research, 124, 374–388. https://doi.org/10.1016/j.jbusres.2020.11.030

Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K., & Jiya, T. (2022). Organisational responses to the ethical issues of artificial intelligence. AI & Society, 37, 23–37. https://doi.org/10.1007/s00146-021-01148-6

Zirnig, C., Jungtäubl, M., & Ruiner, C. (2021). Menschengerechte Gestaltung von KI bei Dienstleistungsarbeit. In M. Bruhn & K. Hadwich (Eds.), Künstliche Intelligenz im Dienstleistungsmanagement. Forum Dienstleistungsmanagement. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34324-8_10