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David Lewis, executive vice president for AI research, development and Ethics at Reveal-Brainspace will discuss manual reviews of large text collections and streams that increasingly leverage supervised learning, particularly active learning of text classifiers. Applications include electronic discovery (eDiscovery) in the law, systematic review in medicine, and content moderation of social media. These human-in-the-loop workflows must achieve high effectiveness while minimizing the cost of (and sometimes harm to) human reviewers. Lewis presents a new analytic framework and visualization tool for understanding these tradeoffs.  



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