I had the pleasure of presenting my paper on ethics and data mining at the Rocky Mountain Association for Institutional Research Conference today. First off, my thanks go out to the conference organizers for putting on an excellent conference. And then my thanks go to all of the people who had kind words and/or challenging questions about it.
The paper looks at the ethical side of a growing force in institutional research and higher education management. Data mining and predictive analytics are increasingly used in higher education to classify students and predict student behavior. But while the potential benefits of such techniques are significant, realizing them presents a range of ethical and social challenges. The immediate challenge considers the extent to which data mining’s outcomes are themselves ethical with respect to both individuals and institutions. A deep challenge, not readily apparent to institutional researchers or administrators, considers the implications of uncritical understanding of the scientific basis of data mining. These challenges can be met by understanding data mining as part of a value-laden nexus of problems, models, and interventions; by protecting the contextual integrity of information flows; and by ensuring both the scientific and normative validity of data mining applications.
I'll be posting highlights of the paper in blog-sized chunks over the next week or two. For those who can't wait, the full paper is posted at SSRN with the rest of my papers, and the PowerPoint presentation is available through
Google Docs (update: it turns out Google Drive doesn't support animations) YouTube If I get really ambitious I'll record the narrations from to the slides and you can get, essentially, the whole presentation.