Abstract: Fueled with rapidly growing data sets and with breakthroughs in machine learning, algorithms are informing and often even making decisions that affect all aspects of life. All the way from which news articles we are exposed to and which ads we see to input to sentencing decisions and in the foreseeable future to the life-and-death emergency decisions of our cars.
The centrality of automatic classification brings great utility to individuals, companies and society as a whole. Nevertheless, to unleash the full potential of such algorithms we must address substantial challenges in terms of the privacy of individuals, the protection of individuals from discrimination and the accuracy of the classification algorithms under adversarial manipulations.
In this talk, we will discuss some of the insights we learn from recent research in computer science. Specifically, we will discuss surprising connections and differences between privacy, fairness and correctness. We will also discuss the challenges and opportunities in stronger collaborations between computer science and social sciences on these topics.
About the Speaker: Omer Reingold is a Professor of Computer Science at Stanford University. Past positions include Samsung Research America, the Weizmann Institute of Science, Microsoft Research, the Institute for Advanced Study in Princeton, NJ, and AT&T Labs. His research is in the Foundations of Computer Science and most notably in Computational Complexity and the Foundations of Cryptography with emphasis on randomness, derandomization and explicit combinatorial constructions. He is an ACM Fellow and among his distinctions are the 2005 Grace Murray Hopper Award and the 2009 Gödel Prize.