Towards Steerable AI Systems, SIGIR 2024 Keynote Speaker - Thorsten Joachims

Abstract: AI systems ranging from personal assistants to large internet platforms are taking an ever increasing role in acting on our behalf. This requires that we can steer these systems to take actions that match our expectations and that are beneficial in the long run. This talk will explore machine learning methods for steerable control from the perspective of different stakeholders, including the end-users as well as the platform. I argue that we need models that can reason about goals at multiple scales, enabling well-founded approaches for trading off short-term and long-term metrics. The talk will illustrate such methods and models using applications ranging from search ranking to writing assistance.

Bio: Thorsten Joachims is a Professor at Cornell University in the Departments of Computer Science and Information Science, and he is an Amazon Scholar. His research interests center on a synthesis of theory and system building in machine learning from human interaction, with applications in information access, language technology, and recommendation. His research focuses on counterfactual and causal inference, policy learning, learning to rank, structured output prediction, and learning from implicit feedback. He is an ACM Fellow, AAAI Fellow, KDD Innovations Award recipient, and member of the ACM SIGIR Academy.