 The workload paradox: Will AI reduce academic labor?Jonas Grafström ()
No 385, Ratio Working Papers from The Ratio Institute Abstract: Artificial intelligence is reshaping academia, but instead of liberating scholars, AI might keep them running faster just to stay in place. This paper theoretically explores how AI increases institutional expectations rather than reducing workload. Using a formal workload model, the study examines how automation affects academic tasks, revealing that while AI streamlines some processes, it also creates new responsibilities in research, publishing, and administration. A case study illustrates how scholars experience rising pressures to verify AI-generated work, adapt to changing publication norms, and meet intensifying institutional demands. The findings suggest that AI’s role in academia is not one only of simplification, but acceleration—a race where efficiency gains are quickly absorbed, where the pursuit of academic excellence becomes ever more demanding, and where scholars must continuously push forward, not to advance, but merely to avoid falling behind. Keywords: AI; academic workload; task-biased technological change; automation; labor economics; productivity function. (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hhs:ratioi:0385 Access Statistics for this paper More papers in Ratio Working Papers from The Ratio Institute The Ratio Institute, P.O. Box 5095, SE-102 42 Stockholm, Sweden. Contact information at EDIRC. |
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