Anthropic Refines AI Risk by Profession, 30% Less Exposed

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Anthropic details a method that combines theory and observed uses of its products to estimate the exposure of professions to automation. The company anticipates more gradual effects than shocks like COVID and immediately identifies a large share of jobs that are less affected.
Anthropic anticipates a gradual evolution of jobs in the face of AI
Anthropic believes that the effects of AI usage on employment will not be as abrupt as those related to COVID, and may instead resemble the transformations brought about by the Internet or trade with China. At the same time, the company identifies jobs with low exposure, representing 30% of workers. It explains this lower exposure by the rarity of these activities in the data used. Examples cited include cooks, motorcycle mechanics, lifeguards, and bartenders.
A measure based on usage and application limits
Anthropic emphasizes that there may be gaps between what AI could theoretically do and what is actually implemented. The company highlights several barriers: model limitations that prevent the exploitation of certain capabilities, legal constraints, specific software requirements, and human verification steps that may slow down automation. Its new method thus aggregates the theoretical capacity to automate tasks and the actual usage data of its products, derived from the analysis of interactions with Claude and its API.
Anthropic publishes its method and identifies the most at-risk professions
The details of this methodology were published in March. By applying it, Anthropic has compiled a list of the professions most exposed to automation, which notably includes computer programmers and customer service representatives at the top. The list of the 10 most exposed jobs is available. Anthropic indicates that it aims to identify potential future economic disruptions in advance and clarifies that its analysis is expected to evolve. This initiative comes as artificial intelligence spreads across many sectors and raises concerns about employment.
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