Designing and Evaluating AI Algorithms in Human-Centered Environments

Speaker: Ms. YANG Kunhe
Ph.D. Candidate, Department of Electrical Engineering and Computer Science
University of California, Berkeley

Title:
Designing and Evaluating AI Algorithms in Human-Centered Environments

Abstract:
As AI models are increasingly deployed in real-world settings, they must operate in environments shaped by complex human behaviors, calling for new algorithmic principles for designing AI pipelines that account for human values and incentives. In this talk, I will present my research on the theoretical foundations of designing and evaluating AI algorithms in human-centered strategic environments, leveraging tools from algorithmic economics and learning theory.
I will highlight two representative lines of work. First, I will focus on incentive-aware evaluation, where evaluation metrics themselves become targets of optimization. In the context of sequential probability forecasting, I will present a framework for the truthfulness of calibration measures and introduce algorithmic principles for designing calibration metrics that automatically incentivize truthful reporting. Second, I will discuss how aligning AI with human preferences must account for preference heterogeneity, and introduce a framework called the distortion of AI alignment that characterizes information-theoretic limits of learning from heterogeneous human feedback and motivates robust, game-theoretic approaches to policy optimization. I conclude by discussing future directions and a broader vision for integrating these algorithmic principles into the design of trustworthy, human-centric AI.

Biography:
Kunhe Yang is a fifth-year PhD candidate in Electrical Engineering and Computer Sciences at the University of California, Berkeley, where she is advised by Professor Nika Haghtalab. Her research focuses on the theoretical foundations of AI in human-centered environments by drawing on tools from machine learning theory and algorithmic economics. Her work has been recognized by several awards, including EECS Rising Star, invited speaker at the Cornell Young Researchers workshop, finalist for the Meta Research PhD Fellowship in the Economics and Computation track, and a SIGMETRICS best paper award. Previously, she received her bachelor’s degree from Yao Class at Tsinghua University.

Enquiries:
Ms. FUNG Wing Chi Mary (maryfung@cse.cuhk.edu.hk)
Mr. WONG O Bong (obong@cse.cuhk.edu.hk)