Coping with Artificial Intelligence Ethical Dilemma and Ethical Position Choices?

Sylvie Gerbaix, Sylvie Michel and Marc Bidan ()
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Sylvie Gerbaix: MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier
Sylvie Michel: UMR 8638 - Equipe Pharmacognosie - COMETE - UMR 8638 - Chimie Organique, Médicinale et Extractive et Toxicologie Expérimentale - UPD5 - Université Paris Descartes - Paris 5 - INC-CNRS - Institut de Chimie - CNRS Chimie - CNRS - Centre National de la Recherche Scientifique
Marc Bidan: LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université

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Abstract: The aim of this conceptual article is to demonstrate that proposing measures, actions, and decisions to improve the ethics of Artificial Intelligence (AI) depends on the ethical theoretical position chosen. To achieve this, we proceeded in two stages. Firstly, we characterized and synthesized three different ethical issues posed by AI. Secondly, we selected two main ethical positions proposed by philosophical literature. Finally, we showed that the choice of an ethical theoretical position for each category of ethical issues of AI leads to different decisions. We demonstrated that for each category of ethical problems, the ethical decisions and their consequences differ depending on the ethical theory chosen. The value of this paper is to highlight that the literature on AI ethics often neglects the implications of choosing an ethical position. In order to attempt to solve ethical issues, it is necessary to reach agreements and have discussions that take into account the different ethical theoretical positions and their consequences in terms of decision-making.

Keywords: Artificial Intelligence (AI); Algorithmic System; Ethical Theory; Bias; Responsibility; Transparency (search for similar items in EconPapers)
Date: 2024-04-28
Note: View the original document on HAL open archive server: https://hal.science/hal-04785209v1
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Published in 26th International Conference on Enterprise Information Systems, ICEIS, Apr 2024, Angers, France. pp.382-388, ⟨10.5220/0012726000003690⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04785209

DOI: 10.5220/0012726000003690

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