{"id":1147724,"date":"2025-08-11T12:29:31","date_gmt":"2025-08-11T19:29:31","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=1147724"},"modified":"2025-08-11T12:42:50","modified_gmt":"2025-08-11T19:42:50","slug":"learning-from-other-domains-to-advance-ai-evaluation-and-testing","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/learning-from-other-domains-to-advance-ai-evaluation-and-testing\/","title":{"rendered":"Learning from other domains to advance AI evaluation and testing"},"content":{"rendered":"<p>Drawing on our analysis of eight case studies prepared by independent academic and industry experts, this white paper proposes next steps to address AI evaluation and testing challenges and opportunities by:<\/p>\n<ul>\n<li>Synthesizing insights from the eight case studies, also published separately, and<br \/>\nextracting lessons relevant to AI (Part 1);<\/li>\n<li>Surveying key multistakeholder initiatives that are driving AI evaluation science and<br \/>\npractice forward (Part 2); and<\/li>\n<li>Presenting recommendations for policymakers aiming to advance the AI evaluation and<br \/>\ntesting ecosystem and strengthen AI governance (Part 3)<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Drawing on our analysis of eight case studies prepared by independent academic and industry experts, this white paper proposes next steps to address AI evaluation and testing challenges and opportunities by: Synthesizing insights from the eight case studies, also published separately, and extracting lessons relevant to AI (Part 1); Surveying key multistakeholder initiatives that are 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