Sep 2026· Computer Science & IT Research Journal· Vol 7, pp. 451-468· 0 citations
TL;DR
This research asserts that reduced working hours are a contingent institutional accomplishment rather than an inevitable technological outcome, moving beyond discussions of technical competence and offering a pragmatic yet critical perspective for assessing the viability of a reduced workweek in the era of artificial intelligence.
Abstract
This article contests the deterministic narrative of artificial intelligence (AI) and the future of labor, oscillating between utopian projections of a four-day workweek and nightmarish predictions of widespread displacement. The primary question is why the swift adoption of Artificial Intelligence (AI) has not led to a significant reduction in the workweek, despite its evident productivity benefits. This research asserts that reduced working hours are a contingent institutional accomplishment rather than an inevitable technological outcome, moving beyond discussions of technical competence. A novel tripartite framework is proposed, arguing that systemic workweek compression necessitates the concurrent presence and coordination of three institutional prerequisites: a mechanism to capture and redirect productivity gains, a system for coordinating labor supply across redefined roles, and an infrastructure to decouple income from hourly wages. This contingency theory elucidates the present stagnation, illustrated by the "Zoomification" of knowledge work, while delineating the circumstances under which AI could enable authentic temporal emancipation, as demonstrated by advanced logistics companies employing real-time diagnostic tools. The discourse shifts the academic and policy focus from predicting technological change to examining power dynamics, design, and political decision-making, offering a pragmatic yet critical perspective for assessing the viability of a reduced workweek in the era of artificial intelligence.
Keywords: Artificial Intelligence, Workweek Compression, Institutional Theory, Productivity, Labor Coordination, Algorithmic Management, Technological Change.
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