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In this chapter, we propose a non-traditional RCR training in data sciencethat is grounded into a virtue theory framework. First, we delineate theapproach in more theoretical detail, by discussing how the goal of RCR trainingis to foster the cultivation of certain moral abilities. We specify the natureof these abilities: while the ideal is the cultivation of virtues, the limitedspace allowed by RCR modules can only facilitate the cultivation of superficialabilities or proto-virtues, which help students to familiarize with moral andpolitical issues in the data science environment. Third, we operationalize ourapproach by stressing that (proto-)virtue acquisition (like skill acquisition)occurs through the technical and social tasks of daily data science activities,where these repetitive tasks provide the opportunities to develop(proto-)virtue capacity and to support the development of ethically robust datasystems. Finally, we discuss a concrete example of how this approach has beenimplemented. In particular, we describe how this method is applied to teachdata ethics to students participating in the CODATA-RDA Data Science SummerSchools.

Character comes from practice: longitudinal practice-based ethics training in data science