Evidence-based Evaluation for Responsible AI

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Microsoft Research
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Published on ● Video Link: https://www.youtube.com/watch?v=JhX1CXFzInA


Duration: 30:51
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7

Research Talk
Jonathan Zhu, City University of Hong Kong

Current efforts on responsible AI have focused on why AI should be socially responsible and how to produce responsible AI. An equally important question that hasn’t been adequately addressed is how responsible the deployed AI products are. The question is ignored most of the time, occasionally answered by anecdotal evidence or casual evaluation. We need to understand that good evaluations are not easy, quick, or cheap to carry out. On the contrary, good evaluations rely on evidence that are systematically collected based on proven methods, completely independent from the process, data, and even research staff responsible for the relevant AI products. The evidence-based medicine practice over the last two decades has provided a relevant and informative role model for the AI industry to follow.

Learn more about the Responsible AI Workshop: https://www.microsoft.com/en-us/research/event/responsible-ai-an-interdisciplinary-approach-workshop/

This workshop was part of the Microsoft Research Summit 2022: https://www.microsoft.com/en-us/research/event/microsoft-research-summit-2022/



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