- Anthropic article covers topics such as AI penetration and exposed professions
- Observed AI coverage falls well short of theoretical capacity, data shows
- Future research could explore how graduates access employment
Anthropic has released a new research paper explaining how it will collect real-world data on the impacts of AI on the job market – but that could be just the start.
Claude’s creator notes that the data could really play a role among researchers and policymakers, who might want to act on this information to protect the future workforce from major displacement.
The paper explores data such as theoretical and observed penetration of AI across job types, most exposed occupations, and differences in exposure levels.
Anthropic researches which jobs are threatened by AI
Rather than strictly being a job loss alert system, Anthropic says the research could help companies identify areas where workers need support to upskill.
However, while this all seems particularly damning towards AI, early data suggests that AI has not actually caused large-scale job losses despite the rapid adoption of chatbots and coding assistants. Anthropic says AI is more about augmenting human workers than completely replacing them.
One of the datasets presented in the Anthropic article reveals not only the theoretical coverage of AI in different professions, but also the actual coverage of AI. Management, business and finance, computer science and mathematics, life sciences and social sciences, law, arts and media, and office and administration are among the most likely to be affected, but the reality is that actual AI penetration levels are several times lower.
That being said, we’re starting to see some changes, with hiring slowing amid uncertainty about how AI can actually help businesses, particularly among entry-level workers.
Looking ahead, Anthropic suggests further research into how graduates are adapting to ever-changing hiring trends: more data and more context might suggest that they are finding opportunities elsewhere, despite a body of data showing, for example, that entry-level positions are slowing down.
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