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Computational ethics

Awad, Edmond, Levine, Sydney, Anderson, Michael, Anderson, Susan Leigh, Conitzer, Vincent, Crockett, M. J., Everett, Jim A.C., Evgeniou, Theodoros, Gopnik, Alison, Jamison, Julian C., Kim, Tae Wan, Liao, S. Matthew, Meyer, Michelle N., Mikhail, John, Opoku-Agyemang, Kweku, Borg, Jana Schaich, Schroeder, Juliana, Sinnott-Armstrong, Walter, Slavkovik, Marija and Tenenbaum, Josh B. (2022) Computational ethics. Trends in Cognitive Sciences, 26 (5). pp. 388-405. ISSN 1364-6613

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Identification Number: 10.1016/j.tics.2022.02.009

Abstract

Technological advances are enabling roles for machines that present novel ethical challenges. The study of 'AI ethics' has emerged to confront these challenges, and connects perspectives from philosophy, computer science, law, and economics. Less represented in these interdisciplinary efforts is the perspective of cognitive science. We propose a framework – computational ethics – that specifies how the ethical challenges of AI can be partially addressed by incorporating the study of human moral decision-making. The driver of this framework is a computational version of reflective equilibrium (RE), an approach that seeks coherence between considered judgments and governing principles. The framework has two goals: (i) to inform the engineering of ethical AI systems, and (ii) to characterize human moral judgment and decision-making in computational terms. Working jointly towards these two goals will create the opportunity to integrate diverse research questions, bring together multiple academic communities, uncover new interdisciplinary research topics, and shed light on centuries-old philosophical questions.

Item Type: Article
Additional Information: © 2022 The Author(s)
Divisions: LSE
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Date Deposited: 02 Jul 2024 09:33
Last Modified: 13 Jul 2024 06:30
URI: http://eprints.lse.ac.uk/id/eprint/124076

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