Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic Behaviors

A growing body of literature has proposed formal approaches to audit algorithmic systems for biased and harmful behaviors. While auditing have been greatly impactful, they often suffer major blindspots, with critical issues surfacing only in the context everyday use once are deployed. Recent years seen many cases which users detect raise awareness about behaviors that encounter course their interactions these systems. However, date little academic attention granted bottom-up, user-driven processes. In this paper, we propose explore concept algorithm auditing, a process detect, understand, interrogate problematic machine via day-to-day We argue powerful may elude detection more centrally-organized forms regardless users' knowledge underlying algorithms. analyze several real-world drawing lessons from design future platforms tools facilitate such Finally, discuss work lies ahead, toward bridging gaps between organic emerge