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.

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Published

2023-09-30

Issue

Section

Microeconomics

How to Cite

Exploring the Potentials and Pitfalls of Artificial Intelligence-Driven Decision-Making. (2023). ENTRENOVA - ENTerprise REsearch InNOVAtion, 9(1), 93-100. https://doi.org/10.54820/entrenova-2023-0009