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Rich Caruna - Justice May Be Blind But It Shouldn’t Be Opaque: The Risk of Using Black-Box Models in Healthcare & Criminal Justice
Rich Caruana

Fri Dec 07 06:00 AM -- 06:30 AM (PST) @ None

In machine learning often a tradeoff must be made between accuracy and intelligibility. This tradeoff sometimes limits the accuracy of models that can be safely deployed in mission-critical applications such as healthcare and criminal justice where being able to understand, validate, edit, and ultimately trust a learned model is important. In this talk I’ll present a case study where intelligibility is critical to uncover surprising patterns in the data that would have made deploying a black-box model dangerous. I’ll also show how distillation with intelligible models can be used to detect bias inside black-box models.

Author Information

Rich Caruana (Microsoft)

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