#134: Students Developing Criteria for ML Models: Thinking Ethically about the Technical and Technically about the Ethical

We outline the conceptual framework and curricular approaches that guide our pilot work with students as they develop criteria for “good” or “good enough” machine learning (ML) models. These determinations require ethical and technical expertise and the ability to hold both lenses simultaneously. Not only do students need to learn to think technically and ethically about models, it is essential for them to think ethically about the technical and technically about the ethical—what we term an eth-tech syncretic lens. Our goal is for students to consider ethical questions about ML models in general and apply technical expertise to think carefully about the ethical questions that arise with different technical solutions. Extending research on epistemic criteria for scientific models, we offer a preliminary report on a curricular approach where students develop criteria for ML models that simultaneously addresses the ethical and technical as they tinker with intentionally-flawed starter projects.