Data and Ethics
This course provides an introduction to critical and ethical issues surrounding data and society. It blends social and historical perspectives on data with ethics, policy, and case examples to help students develop a workable understanding of current ethical issues in data science. Ethical and policy-related concepts addressed include: research ethics; privacy and surveillance; data and discrimination; and the “black box” of algorithms. Importantly, these issues will be addressed throughout the lifecycle of data — from collection to storage to analysis and application. Course assignments will emphasize researcher and practitioner reflexivity, allowing students to explore their own social and ethical commitments.
Student Learning Outcomes: Upon completion of the course, students will be able to critically assess their own work and education in the area of data science; to identify and articulate basic ethical and policy-based frameworks; and to understand the relationship between data, ethics, and society
Signing Up for I School Classes
Instructions for Berkeley undergrads, graduate students, and community members