Bipartisan bill seeks to curb recommendation algorithms

A bipartisan group of House lawmakers has introduced legislation that would give people more control over the algorithms that shape their online experience. If passed, the Filter Bubble Transparency Act would require companies like Meta to offer a version of their platforms that runs on an "input-transparent" algorithm that doesn't pull on user data to generate recommendations. The bill would not do away with "opaque" recommendation algorithms altogether but would make it a requirement to include a toggle that allows people to switch that functionality off. Additionally, platforms that continue to use recommendation algorithms need to have a notification that informs people those recommendations are based on inferences generated by their personal data. The prompt can be a one-time notice, but it would need to be presented in a "clear, conspicuous manner," according to the proposed bill. The legislation was introduced by Representatives Ken Buck (R-CO), David Cicilline (D-RI), Lori Trahan (D-MA) and Burgess Owens (R-UT).