Examining Solidarity Against AI-Enabled Surveillance at the Intersection of Workplace and Carceral Realities

2025-10-07

AI Summary

This study exposes the structural complicity between AI-driven workplace surveillance and carceral surveillance systems, revealing shared data infrastructures, algorithmic logics, and disciplinary objectives that collectively intensify oppressive governance over workers and incarcerated populations. Employing community-engaged action research, critical technical studies, and cross-case qualitative analysis, the study systematically identifies previously undocumented intersections—such as the repurposing of correctional monitoring technologies in labor contexts and the interoperability of labor-related datasets with law enforcement databases. It advances a novel, restorative justice–centered framework for cross-population solidarity, foregrounding the agency of surveilled subjects and pathways for coordinated resistance. By theorizing institutional convergence and proposing actionable strategies for coalition-building, the research provides both conceptual grounding and practical guidance for dismantling systemic surveillance silos and fostering anti-surveillance collective action. (149 words)

Technology Category

• Humans and AI: Crowd Sourcing and Human Computation
• Philosophy and Ethics of AI: AI & Jobs/Labor
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

As panoptical, AI-driven surveillance becomes a norm, everyone is impacted. In a reality where all people fall victim to these technologies, establishing links and solidarity is essential to fighting back. Two groups facing rising and targeted surveillance are workers and individuals impacted by the carceral system. Through preliminary data collection from a worker-surveillance lens, our findings reveal several cases of these surveillance infrastructures intersecting. Continuation of our work will involve collecting cases from a carceral-centered lens. Driven by a community-facing analysis of the overlap in the AI-driven surveillance experienced by workers and individuals impacted by the carceral system, we will facilitate discussions with restorative justice activists around cultivating solidarity and empowerment focused on the interconnected nature of workplace and carceral surveillance technologies.

Problem

• Analyzing AI surveillance intersections between workplace and carceral systems
• Establishing solidarity among workers and carceral-affected individuals
• Developing empowerment strategies against interconnected surveillance technologies

Innovation

• Community analysis of AI surveillance overlaps
• Facilitating discussions with restorative justice activists
• Cultivating solidarity against interconnected surveillance technologies