- Anthropic’s paper covers things like AI penetration and at-risk occupations
- Observed AI coverage is far below its theoretical capacity, the data shows
- Future research could examine how graduates navigate employment
Anthropic has released a new research paper discussing how it will collect real-world data on AI’s impact on the labor market — but this may just be the beginning.
Claude-maker notes that where the data could really come into play is among researchers and policymakers who may want to act on these insights to protect future workforces from greater displacement.
The paper explores data such as theoretical versus observed AI penetration across job types, the most exposed occupations, and differences in exposure levels.
Anthropic researches which jobs are at risk from AI
Rather than being a warning system about job losses, Anthropic says the research can help companies identify areas where workers need upskilling support.
But while all of this sounds particularly damning of AI, early data suggests that AI hasn’t actually caused any major job losses despite the rapid adoption of chatbots and coding assistants. Anthropic says AI is more about augmenting human workers rather than fully replacing them.
One of the datasets shown in Anthropic’s post reveals not only the theoretical AI coverage across different professions, but also the actual AI coverage. Management, business and finance, computing and mathematics, life and social sciences, law, arts and media, and office and admin are among the most likely to be affected, but the reality is that the actual levels of AI penetration are several times lower.
That said, we’re starting to see some changes, with hiring slowing amid uncertainty about how AI can actually help businesses, especially among startups.
Looking ahead, Anthropic suggests further research into how candidates are navigating changing hiring trends – more data and more context could suggest they’re finding opportunities elsewhere despite a set of data showing that entry-level roles, for example, are slower.
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