Machine learning and artificial intelligence already powers a deceptively wide sweep of crucial processes and tools like facial recognition, self-driving cars, ad targeting, customer service, content moderation, policing, hiring, and even war. It’s a huge list, and sometimes it’s fun to sit back and marvel at how different all those uses are.
Exactly how those decisions are made and whether or not they’re fair, however, is often opaque or unknowable. That problem has led lawmakers to this attempt to pry open the “black box.”
The new bill would task the Federal Trade Commission with crafting regulations making companies conduct “impact assessments” of automated decision systems to assess the decision making systems and training data “for impacts on accuracy, fairness, bias, discrimination, privacy and security.”