Character Comes from Practice: Longitudinal Practice-Based Ethics Training in Data Science

Emanuele Ratti, Louise Bezuidenhout

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

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 languageEnglish
Title of host publicationBuilding Inclusive Ethical Cultures in STEM
EditorsE. Hildt, K. Laas, E. Brey, C. Z. Miller
PublisherSpringer
Pages181-201
Number of pages21
ISBN (Electronic)978-3-031-51560-6
ISBN (Print)978-3-031-51559-0
DOIs
Publication statusPublished - 23 Feb 2024

Publication series

NameInternational Library of Ethics, Law and Technology
Volume42
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

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