It is widely accepted that we should make decisions based on the data. But that is not enough in itself: we must make good decisions. In this talk, we will consider some properties of good decisions, such as fairness and stability. We will then describe how to ensure that data driven decisions have these properties.

H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan in Ann Arbor, and Director of the Michigan Institute for Data Science. Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, NJ.
Professor Jagadish is well known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents. He is a fellow of the ACM, “The First Society in Computing,” (since 2003) and of AAAS (since 2018). He served on the board of the Computing Research Association (2009-2018). He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014), and Program Chair of the VLDB Conference (2014). Since 2016, he is Editor of the Morgan & Claypool “Synthesis” Lecture Series on Data Management. Among his many awards, he won the ACM SIGMOD Contributions Award in 2013 and the David E Liddle Research Excellence Award (at the University of Michigan) in 2008. His popular MOOC on Data Science Ethics is available on both EdX and Coursera.