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From the Editor's Desk

Bias isn't the only problem with credit scores -- and no, AI can't help

The biggest-ever study of real people's mortgage data shows that predictive tools used to approve or reject loans are less accurate for minorities.

We already knew that biased data and biased algorithms skew automated decision-making in a way that disadvantages low-income and minority groups. For example, software used by banks to predict whether or not someone will pay back credit-card debt typically favors wealthier white applicants. Many researchers and a slew of start-ups are trying to fix the problem by making these algorithms more fair.

But in the biggest ever study of real-world mortgage data, economists Laura Blattner at Stanford University and Scott Nelson at the University of Chicago show that differences in mortgage approval between minority and majority groups is not just down to bias, but to the fact that minority and low-income groups have less data in their credit histories.

Continued here

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