This project [by Jessica Dai], in collaboration with Deb Raji, explores designing a framework for the general public to report and contest large-scale harms from algorithmic decision making systems (ADS).

Jessica Dai is a PhD student in EECS at UC Berkeley advised by Ben Recht and Nika Haghtalab. This project, in collaboration with Deb Raji, explores designing a framework for the general public to report and contest large-scale harms from algorithmic decision making systems (ADS). Most individuals have little control over when ADS are used, much less any ability to affect the design and oversight of its use. The work is particularly focused on ways to empower users to identify systematic patterns of mistakes made by an algorithm on groups of people that may not have been identified a priori, and that emerge only after a period of deployment.