AI Ethics’ Institutional Turn

Over the last few years, various public, private, and NGO entities have adopted a staggering number of non-binding ethical codes to guide the development of artificial intelligence. However, this seemingly failed to drive better ethical practices within AI organizations. In light of this observation, this paper aims to reevaluate the roles the ethics of AI can play to have a meaningful impact on the development and implementation of AI systems. In doing so, we challenge the notion that AI ethics should focus primarily on instilling ethical principles in practitioners within AI organizations, as well as the claim that AI ethics can only lead to ethics washing. We propose a two-pronged institutionalist approach to AI ethics, focusing on shaping organizational decision-making processes and emphasizing the necessity of binding legal regulations. First, we argue that AI ethics should give priority to institutional design over the internalization of ethical principles by individual practitioners. We then contend that legally binding rules are needed to this end, both as a motivation for organizations and to contribute to the semantic determination of high-level ethical principles. We then show that promising proposals to operationalize ethical principles require the backing of binding legal norms to be effective. We conclude by highlighting the potential of AI ethics to contribute meaningfully to legislative innovation in AI governance.

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Publication Details

Journal
Digital Society
Published
2025-03-12
DOI
https://doi.org/10.1007/s44206-025-00174-x
Citations
6
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
14.19
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article

AI Ethics’ Institutional Turn

Jocelyn Maclure, Alexis Morin-Martel
6 citations
Digital Society
Ethics and Social Impacts of AI
14.19
article

AI Ethics’ Institutional Turn

Jocelyn Maclure, Alexis Morin-Martel
article en
6 citations

Abstract

Over the last few years, various public, private, and NGO entities have adopted a staggering number of non-binding ethical codes to guide the development of artificial intelligence. However, this seemingly failed to drive better ethical practices within AI organizations. In light of this observation, this paper aims to reevaluate the roles the ethics of AI can play to have a meaningful impact on the development and implementation of AI systems. In doing so, we challenge the notion that AI ethics should focus primarily on instilling ethical principles in practitioners within AI organizations, as well as the claim that AI ethics can only lead to ethics washing. We propose a two-pronged institutionalist approach to AI ethics, focusing on shaping organizational decision-making processes and emphasizing the necessity of binding legal regulations. First, we argue that AI ethics should give priority to institutional design over the internalization of ethical principles by individual practitioners. We then contend that legally binding rules are needed to this end, both as a motivation for organizations and to contribute to the semantic determination of high-level ethical principles. We then show that promising proposals to operationalize ethical principles require the backing of binding legal norms to be effective. We conclude by highlighting the potential of AI ethics to contribute meaningfully to legislative innovation in AI governance.

Digital SocietyVol. 4(1)
McGill University (CA)
Openalex Percentile: Top 1%
Ethics and Social Impacts of AI
14.19
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