Unveiling AI-Driven Collective Action for a Worker-Centric Future

Collective action by gig knowledge workers is a potent method for enhancing labor conditions on platforms like Upwork, Amazon Mechanical Turk, and Toloka. However, this type of collective action is still rare today. Existing systems for supporting collective action are inadequate for workers to identify and understand their different workplace problems, plan effective solutions, and put the solutions into action. This talk will discuss how with my research lab we are creating worker-centric AI enhanced technologies that enable collective action among gig knowledge workers. Building solid AI enhanced technologies to enable gig worker collective action will pave the way for a fair and ethical gig economy-one with fair wages, humane working conditions, and increased job security. I will discuss how my proposed approach involves first integrating ''sousveillance,'' a concept by Foucault, into the technologies. Sousveillance involves individuals or groups using surveillance tools to monitor and record those in positions of power. In this case, the technologies enable gig workers to monitor their workplace and their algorithmic bosses, giving them access to their own workplace data for the first time. This facilitates the first stage of collective action: problem identification. I will then discuss how we combine this data with Large-Language-Models (LLMs) and social theories to create intelligent assistants that guide workers to complete collective action via sensemaking and solution implementation.