GoKawiilWhen crunching the numbers economy-wide, the researchers found little to no difference in relative overall employment between the jobs judged most and least affected by AI on these metrics. When separating out workers aged 22 to 25, though, the researchers found that, since 2022, employment in the top 40 percent of “AI-impacted” jobs had fallen by about 11 percent. In the 60 percent of jobs with the least AI impact, by contrast, total employment for those young workers grew by 10 percent over the same period.
Brynjolfsson et al Across the entire economy, relative employment effects in more heavily AI-impacted fields are relatively muted. Across the entire economy, relative employment effects in more heavily AI-impacted fields are relatively muted. Brynjolfsson et al Brynjolfsson et al For entry-level workers, though, there is a large and widening gap between employment in fields that are or are not impacted by AI. For entry-level workers, though, there is a large and widening gap between employment in fields that are or are not impacted by AI. Brynjolfsson et al Across the entire economy, relative employment effects in more heavily AI-impacted fields are relatively muted. Brynjolfsson et al For entry-level workers, though, there is a large and widening gap between employment in fields that are or are not impacted by AI. Brynjolfsson et al
Digging deeper into the data, the researchers found that this phenomenon is mainly manifesting itself through lower hiring rates for entry-level workers in AI-impacted fields, rather than increased firings or employees quitting. They also found that the labor market effects among this age group were mostly seen in lower overall employment, rather than reduced pay rates.
But not all jobs that show potential for AI “disruption” are created equal, the researchers found. In its Economic Index, Anthropic differentiates between queries related to tasks that are “automative” (i.e., fully replacing work previously done by a human) or “augmentative” (i.e., helping human workers be more effective at tasks they are still needed for). By this measure, jobs like “accountants and auditors” and “receptionists and information clerks” were among those judged most susceptible to AI automation, while jobs like “chief executive” and “registered nurse” were among those using AI augmentation most often.
Unsurprisingly, jobs where AI automation is prevalent are the ones showing the worst relative employment levels for entry-level workers these days. “The findings are consistent with automation-oriented uses of AI substituting for labor while complementary uses are associated with flat or rising employment,” the researchers write.