This seminar will explore in depth the many ways in which modern computing systems — including the data they ingest, the decisions made by the folks who develop them, and their myriad and nearly ubiquitous applications — may enable, encourage, or prevent societal
discrimination and surveillance capitalism of various types. Students will learn how algorithms and artificial intelligence (“AI”) systems work, how such algorithms and systems may provide differential treatment and/or outcomes for different populations, and how they may invade privacy and cause other harms to people. Students will also consider the potential legal/regulatory, technical, and social/policy interventions that could ameliorate the harms caused by such algorithms and systems and will weigh the advantages and disadvantaged of each.
At the end of the seminar, students should be able to (i) discuss with colleagues and others the positive and negative consequences of various current AI innovations, and (ii) suggest different approaches to address systemic bias and surveillance capitalism — including legal/regulatory or social/policy changes, as well as technical solutions — and explain why certain of these approaches might or might not work in specific circumstances.