AI and Society 36:939–953 (2021)
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Abstract |
In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students.
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DOI | 10.1007/s00146-020-01112-w |
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References found in this work BETA
The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - 2020 - Minds and Machines 30 (1):99-120.
A United Framework of Five Principles for AI in Society.Luciano Floridi & Josh Cowls - 2019 - Harvard Data Science Review 1 (1).
Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting.Shannon Vallor - 2016 - Oxford University Press USA.
View all 17 references / Add more references
Citations of this work BETA
Understanding Responsibility in Responsible AI. Dianoetic Virtues and the Hard Problem of Context.Mihaela Constantinescu, Cristina Voinea, Radu Uszkai & Constantin Vică - 2021 - Ethics and Information Technology 23 (4):803-814.
Cultivating Moral Attention: a Virtue-Oriented Approach to Responsible Data Science in Healthcare.Emanuele Ratti & Mark Graves - 2021 - Philosophy and Technology 34 (4):1819-1846.
Artificial intelligence ethics has a black box problem.Jean-Christophe Bélisle-Pipon, Erica Monteferrante, Marie-Christine Roy & Vincent Couture - forthcoming - AI and Society:1-16.
Embedded Ethics: A Proposal for Integrating Ethics Into the Development of Medical AI.Alena Buyx, Sami Haddadin, Ruth Müller, Daniel Tigard, Amelia Fiske & Stuart McLennan - 2022 - BMC Medical Ethics 23 (1):1-10.
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