Reports  |  ,   |  April 1, 2021

Teaching Data Ethics: Foundations and Possibilities from Engineering and Computer Science Ethics Education

Report by Anna Lauren Hoffmann and Katherine Alejandra Cross, The Information School of the University of Washington and the UW DataLab. 39 pages.

Table of Contents

  • Insights for Teaching Data Ethics from Engineering and Computer Science Ethics Education
    • Introduction
    • Methods and Limitations
    • Justifying Ethics Education: History, Foundations, and Overviews
    • In The Classroom: Approaches, Designs, and Evaluation
    • Teaching Strategies: Case Studies, Games, and Role-Playing
    • Studying Ethics Education: Assessment In and Beyond the Classroom
    • From Ethics to Virtue and Justice: Critical Interventions
  • Towards Data Science Ethics Education: Ethics Within and Beyond the “Integration” Debate


Ethical, social, and other considerations have been acknowledged as important for data science education. However, research is only beginning to emerge on how such considerations are being incorporated into data science curricula. The NSF project “Emerging Cultures of Data Science Ethics in the Academy and Industry” has been examining the state, structure, and substance of “data ethics” education in both higher education and industry.

Our work joins other projects discussing the nature and scope of “tech ethics” syllabi (many of them relevant to data science), illuminated the challenges and perspectives of “ethics owners” in corporate contexts, and that have proposed experimental or speculative redesigns of tertiary-level ethics classes. We are motivated by the conversations these and other projects have sparked. They are integral to cultivating curricular interventions that enhance the critical and ethical sensibilities of students and practitioners in data science and technology.

Unfortunately, our initial project plans were upended by covid-19. We are hardly alone in this regard; the pandemic has slowed research, interrupted teaching, and complicated many scholars’ careers for more than a year now. The impact has had a disproportionate impact on certain groups, including (but not limited to) those with young children or other caretaking responsibilities. This has been true for many of us on this project. Nonetheless, our work continues. If anything, the pandemic response’s reliance on numbers, statistics, and data dashboards has made critical and ethical education in data science more urgent.

As an early output of this project, this document reflects an attempt to systematically trace connections and disjunctions between data science ethics education and its precursors in engineering and computer science ethics education. We developed this document to make our work open and accessible beyond the confines of a single project. We hope this work will be valuable to others engaging engineering and computer science ethics education as a departure point for designing data science ethics programming. We hope our framing of relevant issues, frameworks, and strategies will be useful for moving beyond past limitations, uncovering new possibilities, and charting a path for future work.

-Anna & Katherine

About the Authors

  • Anna Lauren Hoffmann is an assistant professor at The Information School of the University of Washington and affiliate faculty with the UW DataLab. She is a PI on the NSF-funded project “Emerging Cultures of Data Science Ethics in the Academy and Industry.” Her writing on data, technology, and ethics has been published in New Media & Society, Information, Communication, & Society, The Library Quarterly, and the Journal of the Association for Information Science and Technology. Her public scholarship has appeared in various places, including The Guardian, Slate, and The Los Angeles Review of Books. She has been teaching on the social and ethical information of data, information, and technology since 2010.
  • Katherine Cross is a PhD student at The Information School of the University of Washington. She served as a research assistant on the NSF-funded project “Emerging Cultures of Data Science Ethics in the Academy and Industry.” Her research on ethics, games, and online culture has been published in the NSF-funded project “Diversifying Barbie and Mortal Kombat,” as well as Women’s Studies Quarterly, and Human Technology. Her social and cultural criticism has also been published in venues like Rolling Stone, Slate, The Verge, and The Guardian.