What does it mean to embed ethics in data science? An integrative approach based on microethics and virtues
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What does it mean to embed ethics in data science? An integrative approach based on the microethics and virtues Louise Bezuidenhout1 · Emanuele Ratti2 Received: 2 July 2020 / Accepted: 4 November 2020 © The Author(s) 2020
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 (and draws from) 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. Keywords Data science · Microethics · Virtue ethics · Teaching ethics · Embedded ethics
1 Introduction As our world becomes increasingly digital, we are starting to ask questions about how we, as a society, construct, utilize and live in a digital world. In addition to emerging patterns of online social behavior, it is recognized that the design of digital infrastructures and algorithms, and the use of data pose can pose serious ethical challenges (Williams et al. 2018; Zliobaite 2017; Dressel and Farid 2018). These ethical discussions have coalesced under the loose heading “digital/data ethics”. In recent years, a wide range of Louise Bezuidenhout and Emanuele Ratti have contributed equally. * Emanuele Ratti [email protected] 1
Institute for Science, Innovation, and Society, University of Oxford, Oxford, UK
Institute of Philosophy and Scientific Method, Johannes Kepler University Linz, Linz, Austria
2
courses have been developed to educate researchers, as well as the public, about the ethics of AI, machine learning, algorithm design, and digital behavior.1 Many of these courses focus on the broader challenges of accountability, privacy, and fairness posed by the emerging digital landscape. The dominance of a “big picture” focus in digital
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