Practical Approaches to Evaluating AI for Public Benefit

Comparing Humans, AI, and Human-AI Teams

DateSeptember 22, 2026, 2:00 PM ET
Duration60 minutes

The most important question is often not whether AI performs well in isolation, but whether it improves performance relative to current practice. This session explores methods for comparing human-only, AI-only, and human-plus-AI workflows and identifying where AI adds value, where it creates risks, and where hybrid approaches perform best.

 

By the end of this workshop, participants will be able to:

  • Compare the performance of human-only, AI-only, and human-plus-AI approaches across real-world government tasks and workflows.
  • Identify where AI can improve current practices, where it may introduce new risks, and where human judgment and oversight remain essential.
  • Evaluate when hybrid human-AI approaches can deliver better performance, reliability, and public outcomes than either humans or AI working alone.
Vera Liao

Vera Liao

Associate Professor, University of Michigan

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Amy Perez

Amy Perez

Nonresident Policy Fellow at Stanford's Regulation, Evaluation, and Governance Lab (RegLab)

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This workshop is part of the Practical Approaches to Evaluating AI for Public Benefit