Exploring the Potentials and Pitfalls of Artificial Intelligence-Driven Decision-Making

Authors

  • Zoltan Zakota Partium Christian University, Romania

DOI:

https://doi.org/10.54820/entrenova-2023-0009

Keywords:

artificial intelligence, decision-making, ethics of decision-making

Abstract

As artificial intelligence (AI) becomes more deeply implied in everyday life, it takes a more prominent role in decision-making in every industry. As Joseph Fuller, a professor of management practice at Harvard Business School, said: “Virtually every big company now has multiple AI systems and counts the deployment of AI as integral to their strategy.” Implicitly, decision-making capabilities are incorporated into their products; consequently, ethical concerns also gain importance. This paper presents some of the most critical issues of using AI in everyday decision-making. Starting from the three main concepts of AI, decision-making and ethics, it is a philosophical approach to the issues and biases raised by AI's overwhelming spread in everyday life.

Author Biography

Zoltan Zakota, Partium Christian University, Romania

Zoltan Zakota is an electrical and environmental engineer, as well as a lecturer at the Partium Christian University in Oradea, Romania. He currently teaches computer science and economics subjects. In addition, he teaches computer science and electrical engineering subjects at the Faculty of Engineering of the University of Debrecen, Hungary. Over the years, in addition to education, he also worked in the private and civil spheres. He participated in many domestic and international projects, mainly in the field of education and research. His main areas of interest are the information and knowledge-based society and the impact of ICT on society, economy and education. The author can be contacted by email at zzakota@gmail.com.

References

Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI Frontier: Modeling the Impact of AI on the World Economy. McKinsey & Company.

Chikán, A. (2008). Vállalatgazdaságtan /Business Economy/ (4th revised & expanded ed.). AULA.

Chui, M., Issler, M., Roger, R., & Yee, L. (2023, 07 20). Technology Trends Outlook 2023. Retrieved 08 04, 2023, from McKinsey Digital: https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/mckinsey%20technology%20trends%20outlook%202023/mckinsey-technology-trends-outlook-2023-v5.pdf

Forrester, J. W. (1965). Industrial Dynamics. Cambridge, Massachusetts: The M.I.T. Press.

Frankenfield, J. (2022, 06 06). Artificial Intelligence: What It Is and How It Is Used. https://www.investopedia.com/terms/a/artificial-intelligence-ai.asp

Futó, I. (1999). Előszó /Foreword/. In I. Futó (Ed.), Mesterséges intelligencia /Artificial Intelligence/. Budapest: Aula.

IBM. (2022, May). IBM Global AI Adoption Index 2022. https://www.ibm.com/downloads/cas/GVAGA3JP

IBM Cloud Education. (2021, 03 18). AI Ethics. IBM: https://www.ibm.com/cloud/learn/ai-ethics

IJSCP. (2023). Decision-making. (Longdom Publishing) Retrieved 02 18, 2023, from International Journal of School and Cognitive Psychology: https://www.longdom.org/peer-reviewed-journals/decisionmaking-27214.html

Kurzweil, R. (2005). The singularity is near: when humans trascend biology. Viking.

OECD. (2023). OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market. (A. Bassanini, & S. Broecke, Eds.) https://www.oecd-ilibrary.org/employment/oecd-employment-outlook-2023_08785bba-en

Oracle. (2022). What is AI? Learn about Artificial Intelligence. https://www.oracle.com/artificial-intelligence/what-is-ai/

Pazzanese, C. (2020, 10 26). Great promise but potential for peril. https://news.harvard.edu/gazette/story/2020/10/ethical-concerns-mount-as-ai-takes-bigger-decision-making-role/

Resnikoff, J. (2021). Labor’s end: how the promise of automation degraded work. Urbana, Chicago and Springfield: University of Illinois Press.

Russell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (Fourth ed.). Hoboken, NJ: Pearson Education, Inc.

Shanahan, M. (2015). The technological singularity. Massachusetts Institute of Technology.

Susskind, D. (2020). A World Without Work - Technology, Automation, and How We Should Respond. New York: Henry Holt and Co.

Ulam, S. (1958, May). John von Neumann 1903-1957. Bulletin of the American Mathematical Society, 64(3)

Winston, P. H. (1993). Artificial Intelligence (Third ed.). Addison-Wesley

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Published

2024-03-13

How to Cite

Zakota, Z. (2024). Exploring the Potentials and Pitfalls of Artificial Intelligence-Driven Decision-Making. ENTRENOVA - ENTerprise REsearch InNOVAtion, 9(1), 84–91. https://doi.org/10.54820/entrenova-2023-0009

Issue

Section

Microeconomics