Anthropic’s latest research suggests that while AI is rapidly changing the way work is done, it is not eliminating jobs in any meaningful way. At least not yet. But while the labor market, which Peter McCrory, Anthropic’s head of economics, said “remains healthy”, early signs point to an uneven impact on young workers, particularly those entering the workforce.
In an interview on the sidelines of the Axios AI Summit in Washington, McCrory said the company’s latest economic impact report has so far found little evidence of widespread job losses.
There is “no significant difference in unemployment rates” between workers who use Claude for “the most central tasks of their jobs in automated ways,” such as technical writers, data entry clerks, and software engineers, and workers whose jobs require “physical interaction with the real world and dexterity” and have less contact with AI.
However, things could change quickly as AI adoption spreads across industries. If Anthropic CEO Dario Amodei is to be believed, AI could eliminate half of all entry-level white-collar jobs within the next five years, pushing unemployment up to 20%.
“The effects of displacement can materialize very quickly, so we want to establish a monitoring framework to understand it before it materializes, to be able to catch it when it’s happening and, ideally, identify appropriate policy responses,” McCrory told TechCrunch.
Staying ahead of these trends is why tracking the growth, adoption and proliferation of AI is so important, he said.
“What a computer can do, in principle, can also be done by Claude and other large language models. [do]”What we’re actually seeing is that people and companies are actually bringing a very small subset of tasks into the model,” McCrory said.
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He said Anthropic looked at tasks that AI is particularly good at, tasks that are already automated, and tasks that are tied to real-world workplace use cases – areas where replacement is most likely to occur.
Anthropic’s fifth economic impact report, released on Tuesday, also found that the skills gap between long-time Claude adopters and new entrants is widening, even in areas where displacement has not yet been as high.
Early adopters are more likely to use the model for work-related tasks rather than casual or one-off purposes, and to get significantly more value from the model in more sophisticated ways, such as as a “thought partner” for iteration and feedback.
“This points to the next direction [AI] “This is a skills-biased technology that could intensify differences and outcomes among those with higher skills in extracting value from these tools, potentially having an uneven impact on the labor market,” McCrory said.
He noted that workers who understand how to use AI to augment their work will be in higher demand in the labor market, further widening the gap.
The report also found that “Claude is used more intensively in high-income countries, in locations with large knowledge workers in the United States, and in a relatively small number of specialized jobs and occupations.”
In other words, despite the promise of AI as an equalizer, adoption may already be tilted toward the wealthy, and its benefits may be further amplified as power users move further along.
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