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Serena Wang: From Metric Selection to Metric Discovery in AI Evaluation | Stanford HAI
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eventSeminar

Serena Wang: From Metric Selection to Metric Discovery in AI Evaluation

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Friday, October 16, 2026 1:00 PM - 2:15 PM US/Pacific
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Evaluation metrics are a cornerstone of the AI ecosystem, driving the decisions of developers, consumers, and investors alike. From Metric Selection to Metric Discovery in AI Evaluation will address two challenges in evaluation that are exacerbated in the development of AI systems. First is a computational challenge: the explosion of metrics to measure complex and hard-to-define capabilities in AI systems has led to rapidly increasing computational costs to evaluation. To mitigate this, we'll discuss metric selection, with algorithms for efficient and provably representative selection of metrics based in social choice theory. Second is an informational challenge: evaluators continue to face a fundamental information problem of not knowing whether they could be missing some important metrics entirely. Thus, moving beyond selection, we'll then discuss metric discovery through an economic model of incentives for agents to reveal unknown unknown metrics under information asymmetry.

Speaker
Serena Wang
Serena Wang | Assistant Professor in Computer Science, University of British Columbia, and Canada CIFAR AI Chair