arXiv: cs.AI preprintsInternational5 November 2026
Dull, Dirty, Dangerous? Working Conditions and the Limits of Occupational AI Exposure
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arXiv:2611.06888v1 Announce Type: new Abstract: Automation is often justified as relief from dull, dirty, and dangerous work. I examine how these conditions relate to occupational AI exposure using 21 O*NET items across 754 US occupations. Higher exposure is associated with lower condition scores under a large language model (LLM) measure and AI Occupational Exposure (AIOE), with equal occupation weights and employment weights. Adjustment for physical demands, required education, training and experience, and wages reduces the composite association. The adjusted confidence intervals include zer
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