An Inconvenient Truth about Artificial Intelligence
An Inconvenient Truth about Artificial Intelligence

Abstract: 

Businesses and governments increasingly rely on Artificial Intelligence for critical decision making. Despite AI’s numerous success stories in controlled environments, a major concern is its lack of robustness in complex and noisy environments. In this talk, we first exhibit multiple vulnerabilities of AI in real world scenarios with either complex objectives, noisy data, or malicious users. We then demonstrate our robust AI solutions that are deployed to address these vulnerabilities, with an emphasis on applications in defense and finance industries.

Bio: 

Yaron Singer is an Associate Professor of Computer Science at Harvard University and CEO of Robust Intelligence. Yaron is known for breakthrough results in algorithms, machine learning, and market design, including his most recent work on exponentially faster algorithms for submodular optimization. Prior to Harvard, Yaron has worked for two years at Google AI Research in the Algorithms group. Yaron obtained his PhD from UC Berkeley and is the recipient of the NSF CAREER award, the Sloan fellowship, Facebook faculty award, Google faculty awards, 2012 Best Student Paper Award at the ACM conference on Web Search and Data Mining, the 2010 Facebook Graduate Fellowship, the 2009 Microsoft Research PhD Fellowship.