2 citations · 6 across the 6 of their papers we have counts for
6 papers
ASSERT: A Measurement Pipeline for GenAI Audits
Riccardo Fogliato, Abhinav Palia, Xiawei Wang +11
Audits of generative AI (GenAI) systems often summarize behavior as a reported rate: how often the audited system complies with policy. Researchers and stakeholders use that rate t…
Taxonomizing Representational Harms using Speech Act Theory
Emily Corvi, Hannah Washington, Stefanie Reed +9
Representational harms are widely recognized among fairness-related harms caused by generative language systems. However, their definitions are commonly under-specified. We make a…
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, A. Feder Cooper +17
The measurement tasks involved in evaluating generative AI (GenAI) systems lack sufficient scientific rigor, leading to what has been described as "a tangle of sloppy tests [and] a…
A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts
Alexandra Chouldechova, Chad Atalla, Solon Barocas +11
The valid measurement of generative AI (GenAI) systems' capabilities, risks, and impacts forms the bedrock of our ability to evaluate these systems. We introduce a shared standard…
Dimensions of Generative AI Evaluation Design
P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas +3
There are few principles or guidelines to ensure evaluations of generative AI (GenAI) models and systems are effective. To help address this gap, we propose a set of general dimens…
Evaluating Generative AI Systems is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, Nicholas Pangakis +17
Across academia, industry, and government, there is an increasing awareness that the measurement tasks involved in evaluating generative AI (GenAI) systems are especially difficult…