40 Labor Groups Press Congress on AI Workplace Surveillance

WASHINGTON, D.C. — A coalition of 40 labor and advocacy organizations — led by the Economic Policy Institute (EPI), the AFL-CIO Tech Institute, We Build Progress, and Workshop — delivered a letter to members of Congress on April 28 urging federal legislation that centers workers in any national AI framework. The groups warn that employers' expanding use of AI-driven monitoring and "algorithmic management" threatens workers' rights, privacy, and economic security unless Congress sets clear guardrails.

The Five Demands

The coalition's letter lays out five specific demands for any federal AI legislation. First, transparency: workers must be told when automated systems evaluate them and how those systems work in practice. Second, meaningful challenge and remediation — employers should provide mechanisms for workers to appeal or reverse automated decisions that affect pay, hours, discipline, or termination.

The letter also calls for limits on secret surveillance, arguing that routine covert collection of productivity, biometric, or off-task data should be curtailed and disclosed. On discrimination, the groups demand that systems be tested for disparate impacts, documented, and subject to independent audits. Finally, the coalition calls for worker voice and collective bargaining: deployment decisions should be subject to worker input and bargaining where applicable.

Coalition and Political Context

The signatories include national unions and civil-rights and labor advocacy groups such as AFT, AFSCME, CWA, SEIU, the National Domestic Workers Alliance, the National Employment Law Project, and the Leadership Conference on Civil and Human Rights, among many others.

The letter frames the push as urgent because federal policymaking has lagged behind rapid AI adoption. The coalition also criticizes a recent Administration executive order and proposed federal framework that the groups say risk preempting stronger state-level protections already in effect or under development.

The Regulatory Gap

The letter and contemporaneous reporting cite rapid, widespread adoption of employee-monitoring tools that log keystrokes, webcam images, location data, break times, and algorithmically assign performance scores — often without explanation. Advocates point to gig and contractor populations who frequently lose hours or pay when opaque scoring systems change or malfunction, with little ability to appeal.

For workers in the AI training industry specifically — annotators, RLHF raters, and data labelers — this is particularly relevant. Many platforms already use automated quality scoring, activity monitoring, and output-rate tracking that can result in reduced assignments or deactivation without clear explanation.

"Worker-centered provisions would replace the current patchwork where platforms and employers have wide discretion."

Legislative Pathways

Congressional action could take several forms: workplace-centered provisions within broader AI legislation, with the Bipartisan Senate AI Working Group roadmap serving as a reference point; standalone workplace surveillance rules; or strengthened enforcement authority for agencies such as the EEOC and Department of Labor.

Key indicators to watch include whether the House Democratic Commission on AI and the Innovation Economy adopts worker-focused recommendations, whether upcoming committee drafts include enforceable notice, audit, and anti-surveillance clauses, and whether the White House revises preemption language in its current proposed framework.

Compliance Exposure

If enacted, transparency, auditability, and appeal requirements would increase documentation, compliance, and independent-audit obligations for employers and platform operators. They could also spur new technical standards for explainability, logging, and bias testing in the tools used to manage AI training workforces.

Labor advocates say stronger rules would rebalance employer-employee power imbalances that let surveillance expand with limited oversight. Industry groups have not yet formally responded to the coalition letter.

Immediate Action

For workers and unions, advocates recommend documenting incidents where automated decisions affected pay or assignments, requesting written explanations of such decisions, pushing for bargaining over monitoring policies where applicable, and contacting Congressional representatives to express support for worker-protective AI legislation.

For employers and platforms, the recommended steps include conducting bias and privacy impact assessments on automated management systems, creating human-review pathways for adverse automated decisions, publishing clear notices about monitoring practices, and beginning documentation practices now rather than waiting for legislation to compel it.

The coalition framed the letter as a prompt for Congress to act before AI adoption proceeds further without enforceable worker protections. Whether that political pressure translates into statute or regulatory change remains to be seen — but the coalition's size and breadth signals that organized labor intends to make this a sustained priority through the 2026 legislative session.

Related reading

Is AI training legit? — how to identify platforms with transparent contractor practices.

What is AI training? — how the work that's being regulated actually operates.

Running multiple platforms at once — how to reduce exposure to any single platform's labor practices.

Best AI training platforms compared — platforms ranked partly on contractor experience and transparency.