AI Weekly: Algorithmic discrimination highlights the need for regulation

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. This week, a piece from The Makeup uncovered biases in U.S. mortgage-approval algorithms that lead lenders to turn down people of color more often than white applicants. A decisioning model called Classic FICO didn't consider everyday payments -- like on-time rent and utility checks, among others -- and instead rewarded traditional credit, to which Black, Native American, Asian, and Latino Americans have less access than white Americans. The findings aren't revelatory: back in 2018, researchers at the University of California, Berkeley found that mortgage lenders charge higher interest rates to these borrowers compared to white borrowers with comparable credit scores. But they do point to the challenges in regulating companies that riskily embrace AI for decision-making, particularly in industries with the potential to inflict real-world harms.