Abstract
in this chapter, we propose a non-traditional RCR training in data science that is grounded in a virtue theory framework. First, we delineate the approach in more theoretical detail by discussing how the goal of RCR training is to foster the cultivation of certain moral abilities. We specify the nature of these ‘abilities’: while the ideal is the cultivation of virtues, the limited space allowed by RCR modules can only facilitate the cultivation of superficial abilities or proto-virtues, which help students to familiarize themselves with moral and political issues in the data science environment. Third, we operationalize our approach 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 data systems. Finally, we discuss a concrete example of implementing this approach. In particular, we describe how this method is applied to teach data ethics to students participating in the CODATA-RDA Data Science Summer Schools.
Original language | English |
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Title of host publication | Building Inclusive Ethical Cultures in STEM |
Editors | E. Hildt, K. Laas, E. Brey, C. Z. Miller |
Publisher | Springer |
Pages | 181-201 |
Number of pages | 21 |
ISBN (Electronic) | 978-3-031-51560-6 |
ISBN (Print) | 978-3-031-51559-0 |
DOIs | |
Publication status | Published - 23 Feb 2024 |
Publication series
Name | International Library of Ethics, Law and Technology |
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Volume | 42 |
ISSN (Print) | 1875-0044 |
ISSN (Electronic) | 1875-0036 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- data ethics
- AI ethics