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The value of information in model assisted decision-making

Jessica Hullman, Northwestern University
E18-304

Abstract: The widespread adoption of AI and machine learning models in in society has brought increased attention to how model predictions impact decision processes in a variety of domains. I will describe tools that apply statistical decision theory and information economics to address pressing question at the human-AI interface. These include: how to evaluate when a decision-maker appropriately relies on model predictions, when a human or AI agent could better exploit available contextual information, and how to evaluate (and design)…

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MIT Statistics + Data Science Center
Massachusetts Institute of Technology
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