The Algorithmic Collective Action Repository

We present the Algorithmic Collective Action Repository, a resource that maps how collectives understand, contest and shape AI systems. Algorithmic Collective Action (ACA) studies how collectives can strategically interact with algorithmic systems to steer them towards a common goal. Our contribution is twofold: a Tracker of ACA Cases, and a taxonomy describing the range of methods available to collectives. From this contribution, we draw insights on four key aspects of ACA: where actions take place in the AI life cycle, what infrastructure is used by collectives in their actions, who are the actors of the actions listed in the Tracker, and the factors explaining ACA’s success. The Tracker is publicly accessible at $\underline{\href{https://6a9086491cfd58072b08cd6f--dynamic-cranachan-b171b6.netlify.app/}{this URL}}$.