In October 2025, Schor testified before the United States Senate on the policy implications of AI-driven productivity growth and labor displacement. Her central argument was that if AI produces the employment displacement that serious researchers forecast, the institutional response should include working-time reduction as a primary tool — a smaller reduction in hours for many workers rather than elimination of hours for some workers and intensification for others. The testimony framed reduced work hours not as a utopian preference but as a policy tool for managing displacement, distributing productivity gains, and maintaining social cohesion through technological transition. It remains the most visible policy-level application of Schor's career-long framework to the AI moment.
The testimony emerged in the context of growing policy attention to AI's labor market effects, particularly following research by Anthropic, the Center for AI Safety, and labor economists documenting early displacement patterns in specific occupational categories. The Senate hearing was one of multiple such sessions held in 2024 and 2025 as Congress began to engage with AI's economic implications.
Schor's testimony made three primary arguments. First, that AI-driven productivity growth creates an arithmetic surplus of labor hours whose allocation is a policy choice, not a technological inevitability. Second, that concentrating displacement on a minority of workers (through unemployment) is socially and economically worse than distributing reduced hours across the workforce, even if the aggregate hour reduction is the same. Third, that the institutional mechanisms required to distribute hour reductions — compensation restructuring, benefits portability, regulatory updates to overtime and working-time law — are available and empirically validated, drawing on the four-day-week pilot evidence and European policy precedents.
The testimony's specific policy recommendations included updating the Fair Labor Standards Act to reflect contemporary knowledge-work conditions, supporting collective bargaining for shorter work hours, piloting federal four-day-week programs in public employment, and decoupling benefits from full-time employment status. The recommendations were technical but they implied a substantial institutional transformation, one whose scale Schor acknowledged but argued was proportionate to the scale of the AI transition.
The testimony's reception was mixed. Some senators and commentators engaged substantively with the policy proposals; others dismissed them as insufficiently attentive to competitive dynamics and global trade pressures. The testimony's longer-term impact remains to be seen; its immediate effect was to establish working-time reduction as a legitimate policy option in congressional AI discourse, a shift from its previous status as primarily an advocacy or academic concern.
Delivered before the U.S. Senate (specific subcommittee varies by reporting) in October 2025, as part of ongoing congressional engagement with AI policy.
Drew on Schor's career-long research program, her UK four-day-week pilot findings, and her 2025 book Four Days a Week.
Distributed vs. concentrated displacement. Reduced hours for many workers is preferable to unemployment for some, with better social and economic consequences.
Arithmetic surplus. AI creates a surplus of labor hours whose allocation is a policy choice, not a technological inevitability.
Specific policy recommendations. FLSA updates, collective bargaining support, federal four-day pilots, benefits portability.
Empirical validation. Four-day-week pilots and European precedents demonstrate feasibility; the policy proposals are not speculative.
Legitimation of work-time reduction. The testimony established hour reduction as a legitimate congressional policy option for AI response.
Critics of Schor's testimony argued that distributed hour reductions face competitive disadvantage in global markets, that the European policy precedents she cited operate under different conditions (more centralized collective bargaining, stronger regulatory states) that may not translate to the American context, and that the specific magnitude of AI displacement remains uncertain enough that policy responses at the scale she proposed may be premature.