Eliminating AI Risk, One Model Failure at a Time скачать в хорошем качестве

Eliminating AI Risk, One Model Failure at a Time

Speaker: Yaron Singer CEO & Co-Founder, Robust Intelligence Yaron Singer is the CEO and co-founder of Robust Intelligence, and the Gordon McKay Professor of Computer Science and Applied Mathematics at Harvard University. Before Harvard he was a researcher at Google and obtained his PhD from UC Berkeley. He is the recipient of the NSF CAREER award, the Sloan fellowship, Facebook faculty award, Google faculty award, 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. Abstract: As organizations adopt AI they inherent AI risk. AI risk often manifests itself in AI models that produce erroneous predictions that go undetected and result in serious consequences for the organization and individuals affected by the decisions. In this talk we will discuss root causes for AI models going haywire, and present a rigorous framework for eliminating risk from AI. We will show how this methodology can be used as building blocks for building an AI firewall that can prevent and model AI model failures.