On the Morality of Artificial Intelligence
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Abstract (arXiv)
Much of the existing research on the social and ethical impact of Artificial Intelligence has been focused on defining ethical principles and guidelines surrounding Machine Learning (ML) and other Artificial Intelligence (AI) algorithms [IEEE, 2017, Jobin et al., 2019]. While this is extremely useful for helping define the appropriate social norms of AI, we believe that it is equally important to discuss both the potential and risks of ML and to inspire the community to use ML for beneficial objectives. In the present article, which is specifically aimed at ML practitioners, we thus focus more on the latter, carrying out an overview of existing high-level ethical frameworks and guidelines, but above all proposing both conceptual and practical principles and guidelines for ML research and deployment, insisting on concrete actions that can be taken by practitioners to pursue a more ethical and moral practice of ML aimed at using AI for social good.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 1.
4 papers.
- 2022Metaethical Perspectives on 'Benchmarking' AI Ethicscited by 11
- 2021Est-ce que vous compute? Code-switching, cultural identity, and AIcited by 6
- 2022Moral Dilemmas for Moral Machinescited by 6
- 2025Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solverscited by 2
- 2025Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers18 May 2025
- 2022Metaethical Perspectives on 'Benchmarking' AI Ethics11 Apr 2022
- 2022Moral Dilemmas for Moral Machines11 Mar 2022
- 2021Est-ce que vous compute? Code-switching, cultural identity, and AI15 Dec 2021