Despite breakthroughs in mathematics and coding benchmarks, general-purpose AI systems are not yet ready to deliver a step change in human productivity. This talk outlines three key challenges impeding their deployment: (1) encoding nuanced human intent, (2) managing feedback loops for alignment and debugging, and (3) ensuring privacy, compliance, and trustworthiness. We review recent efforts in these areas and close with strategic directions for AI research in the coming years.
Seong Joon Oh is a professor at the University of Tübingen, where he leads the Scalable Trustworthy AI (STAI) group. His research focuses on building reliable machine learning models—particularly explainable, robust, and probabilistic ones—and on developing cost-effective ways to incorporate human supervision. He also advises Parameter Lab. Before joining Tübingen, he worked as a research scientist at NAVER AI Lab. He earned his PhD in computer vision and machine learning from the Max Planck Institute for Informatics in 2018, working with Bernt Schiele and Mario Fritz on the privacy and security implications of machine learning. He holds both a Master of Mathematics with Distinction (2014) and a BA in Mathematics as a Wrangler (2013) from the University of Cambridge
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What? | Deploying General AI in the Private World |
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Who? | Seong Joon Oh, University of Tübingen |
When? | August 14th 2025 @ 5pm |
Where? | Zoom |
Registration | meetup event-site |