Fairness, safety, reliability, explainability, robustness, accountability-it's hard to argue with these as goals for building trust in AI.
These dimensions must be measurable & able to be communicated to show meaningful progress. Much like standardized nutrition labels helped drive more informed consumer choices being able to clearly articulate & compare AI offerings is a big win for all consumers as well as businesses that can differentiate through trust.
Join us to explore an open source & research driven initiative tackling this important issue & leave ready with a framework you can measure your own company's initiatives with.
Our previous well received event, Ethical AI, raised very clear concerns about AI & data privacy as well as a toolkit for data trust & user experience. This event, Pillars of Trusted AI, focuses more on machine learning aspects & practices & is complementary.
6:00 PMNetworking & Food, Beer6:30 PMKickoff & Sponsors (IBM, Betaworks Studios)6:35 PM David Piorkowski, IBM - Pillars of Trusted AI7:20 PM Second Speaker - TBD8:00 PMExtended Q&A followed by networking
Talk 1 -David Piorkowski, IBM Pillars of Trusted AIThis talk will discuss IBM's vision for Trusted AI framed through five pillars: fairness, explainability, robustness, assurance & the AI lifecycle. Attendees will learn about each of pillars, the challenges unique to each pillar & recent work addressing those challenges & framing communication & clarity around them.
Talk 2 - TBD
David Piorkowski is a Researcher at IBM Research AI. His research interests are at the intersection of AI, Software Engineering & HCI. He is particularly interested in understanding how data scientists & developers reason about AI during development, especially regarding building & communicating trust.
This event is made possible with the support ofIBMandBetaworks Studios.