Attacking discrimination with smarter machine learning

Some exciting research going on at the Big Picture research group at Google:


As machine learning is increasingly used to make important decisions across core social domains, the work of ensuring that these decisions aren’t discriminatory becomes crucial.

Here we discuss “threshold classifiers,” a part of some machine learning systems that is critical to issues of discrimination. A threshold classifier essentially makes a yes/no decision, putting things in one category or another. We look at how these classifiers work, ways they can potentially be unfair, and how you might turn an unfair classifier into a fairer one. As an illustrative example, we focus on loan granting scenarios where a bank may grant or deny a loan based on a single, automatically computed number such as a credit score…

Read more about it here.

Source: research.google.com

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