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Seminar: Recourse in Machine Learning

June 1 @ 2:00 pm - 3:30 pm

Headshot of Berk Ustun

Headshot of Berk Ustun

Please join us on Tuesday, June 1 @ 2:00 pm for a ZOOM talk by Berk Ustun. The talk will be about 45 minutes and will be followed by a 30 minute Q&A.

Title: Recourse in Machine Learning

Abstract: Machine learning models are often used to automate decisions that affect humans: whether to approve a loan, extend a job interview, or provide insurance. In such tasks, a person should have the ability to change the decision of the model. When a person is denied a loan by a model, for example, they should be able to alter its inputs in a way that guarantees approval. Otherwise, they will be denied the loan so long as the model is deployed, and – more importantly – lack control over a decision that affects their livelihood.

In this talk, I will discuss these issues in terms of a formal notion called recourse – i.e., the ability of a person to change the decision of a model by altering actionable input variables (e.g., income as opposed to age). I will describe how models may deny recourse to their decision subjects due to widespread practices in model development, and present a suite of methods to prevent this harm. I will end with a brief discussion on how recourse can facilitate meaningful protection in consumer-facing applications of machine learning.

Zoom Meeting: https://ucsd.zoom.us/j/96929564293

Meeting ID: 969 2956 4293

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Meeting ID: 969 2956 4293
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June 1
2:00 pm - 3:30 pm