Ethics & Policy of Data Analytics
We live in an increasingly data-intensive and algorithmic society, and so we must consider the ethical, societal, and personal impacts of these technologies. This course will explore ethical and policy aspects of data analytics, including issues of privacy, bias, trust, and more. We will consider both ethical questions about what we ought to do with data analytics, and also policy questions about what we are permitted or required to do by law and regulation (in both US and non-US contexts). This course will thus provide an important complement to more statistics/technology-centric courses that emphasize what we can do.
At the end of this course, students will be able to:
● Understand the key concepts of privacy, fairness, bias, explainability, and trust
● Determine the ethical impacts (along these dimensions) of various standard data analysis practices, methods, and products
● Derive relevant, key policy and legal constraints on data analytic practices and products
● Apply both ethical and policy considerations to an analysis of the permissibility and/or legitimacy of different data analytics
No specific course pre-requistes, but we will assume familiarity with the basic data analytics pipeline, so students should have taken a course that talked about data analytics (or be prepared to do outside reading).