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A plea for choosing ex ante an ethical theorical position for a relevant response to ethical issues posed by algorithmic systems

Author

Listed:
  • Sylvie Michel

    (IRGO - Institut de Recherche en Gestion des Organisations - UB - Université de Bordeaux - Institut d'Administration des Entreprises (IAE) - Bordeaux)

  • Sylvie Gerbaix

    (UM - Université de Montpellier)

  • 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)

Abstract

The aim of this conceptual article is to show that one cannot propose measures, actions, and decisions to improve algorithmic systems ethics of without first choosing an ethical theoretical position. In this perspective, we proceeded in two stages. First, we identify the main ethical theorical positions proposed in the philosophical literature. Secondly, we characterize and synthetize three different ethical issues posed by algorithmic systems, and we show that the repercussions of the choice of an ethical theorical position for each category of ethical issues of algorithmic systems lead to different decisions. We show that for each category of ethical problems, the ethical decisions and their repercussions differ according to the ethical theory chosen. The value of this paper is to show that the literature on algorithmic systems ethics does not take into account the implications of choosing an ethical position. Indeed, before trying to solve ethical issues, agreements, discussions, are needed to take into account the different ethical theorical positions and their repercussions in terms of decision.

Suggested Citation

  • Sylvie Michel & Sylvie Gerbaix & Marc Bidan, 2022. "A plea for choosing ex ante an ethical theorical position for a relevant response to ethical issues posed by algorithmic systems," Post-Print hal-03953936, HAL.
    • Handle: RePEc:hal:journl:hal-03953936
    DOI: 10.1109/NextComp55567.2022.9932235
    as

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