Marissa Gerchick is a data scientist and researcher focused on the intersection of technology and consumer protection issues, especially related to machine learning and algorithmic decision-making systems. Marissa has worked on technology policy problems in civil society, in government, at machine learning startups, and at interdisciplinary research labs. Previously, Marissa was a Technology Fellow in the U.S. Senate through the TechCongress program, working on the staff of the Senate Judiciary Committee’s Antitrust Subcommittee. Marissa has also worked at Hugging Face, where she worked on improving the documentation of machine learning models with model cards, and at the Stanford Computational Policy Lab, where she used statistical tools to analyze policy decisions. Marissa holds a B.S. in Mathematical and Computational Science and an M.S. in Management Science and Engineering (focused on Computational Social Science), both from Stanford University.
Assembly Fellowship Project:
Dozens of tech bills are introduced to Congress each year, often using different terms to refer to the same entities, or using the same terms but defining them in different ways. Marissa Gerchick’s term tabs helps staffers, area experts, and the general public sift through this dense web by organizing the terms and definitions used in proposed and enacted bills. Users can view the cleaned data on the Term Tabs site, or download it for themselves to study emerging consensuses on certain term definitions, the differences between definitions in Republican, Democratic, and bipartisan bills, or any other relevant research question.