STSCI 3600 - Integrated Ethics in Data Science

Fall or Spring. 2 credits. Student option grading (no audit).

Co-meets with STSCI 5600.

M.E. Karns.

Integrated Ethics in Data Science examines your responsibilities in data analysis. Our investigation starts with the aggregated impacts of data science on fairness, privacy, and justice outcomes for groups and individuals. Use of supplied data and applications are analyzed using agency, moral imagination, and virtue ethics. Responsible practices in data science, codes of conduct, and current regulations will be applied. Evaluation of the act of speaking up, supporting others and working with an ethics committee will develop professional skills. Case studies from legal issues, policy concerns, and industry practices provide problems to evaluate the individual choices that led to the results. Course success depends on your frequent written work, engagement in small group discussions, and planning for professional practice.

Outcome 1: Identify ethical conflicts in data science practices.

Outcome 2: Analyze the connection between individual ethical choices and aggregated outcome impacts.

Outcome 3: Create a plan for individual moral awareness, habits, and virtue development.