Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Serena Wang: From Metric Selection to Metric Discovery in AI Evaluation | Stanford HAI

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Research Programs
    • Grants
    • Marlowe (opens in new tab)
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Your browser does not support the video tag.
eventSeminar

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

Status
Past
Date
Friday, October 16, 2026 1:00 PM - 2:15 PM US/Pacific
Attend Virtually
Share
Link copied to clipboard!

Related Events

Confronting Our AI Future: Hope, Fear, and the Choices Ahead
ConferenceOct 28, 20269:00 AM - 6:45 PM
October
28
2026

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

Conference

Confronting Our AI Future: Hope, Fear, and the Choices Ahead

Oct 28, 20269:00 AM - 6:45 PM

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

Marlowe | AI + Data for Science with Dan Yamins
SeminarOct 28, 2026
October
28
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Event

Marlowe | AI + Data for Science with Dan Yamins

Oct 28, 2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Olawale (Wale) Salaudeen | On Construct Validity in AI: The Scientific Work We Have Yet to Do
SeminarOct 30, 20261:00 PM - 2:15 PM
October
30
2026

An AI Measurement Science (AIMS) Seminar Series

Event

Olawale (Wale) Salaudeen | On Construct Validity in AI: The Scientific Work We Have Yet to Do

Oct 30, 20261:00 PM - 2:15 PM

An AI Measurement Science (AIMS) Seminar Series

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