Performance or Principle: Resistance to Artificial Intelligence in the U.S. Labor Market

From genetically modified foods to autonomous vehicles, society often resists otherwise beneficial technologies. Resistance can arise from performance-based concerns, which fade as technology improves, or from principle-based objections, which persist regardless of capability. Using a large-scale U.S. survey quota-matched to census demographics and assessing 940 occupations (N = 23,570 occupation ratings), we disentangle these sources in the context of artificial intelligence (AI). Despite cultural anxiety about artificial intelligence displacing human workers, we find that Americans show surprising willingness to cede most occupations to machines. Given current AI capabilities, the public already supports automating 30% of occupations. When AI is described as outperforming humans at lower cost, support for automation nearly doubles to 58% of occupations. Yet a narrow subset (12%)—including caregiving, therapy, and spiritual leadership—remains categorically off-limits because such automation is seen as morally repugnant. This shift reveals that for most occupations, resistance to AI is rooted in performance concerns that fade as AI capabilities improve, rather than principled objections about what work must remain human. Occupations facing public resistance to the use of AI tend to provide higher wages and disproportionately employ White and female workers. Thus, public resistance to AI risks reinforcing economic and racial inequality even as it partially mitigates gender inequality. These findings clarify the “moral economy of work,” in which society shields certain roles not due to technical limits but to enduring beliefs about dignity, care, and meaning. By distinguishing performance- from principle-based objections, we provide a framework for anticipating and navigating resistance to technology adoption across domains.