Language Models’ Impact on Jobs The occupations likely to be most affected by language models

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Language Models’ Impact on Jobs: The occupations likely to be most affected by language models

Telemarketers and college professors are most likely to find their jobs changing due to advances in language modeling, according to a new study.

What’s new: A team led by Ed Felten, a computer scientist at Princeton University and former deputy CTO of the United States, projected the jobs and industries in the U.S. likely to be most affected by language models.

How it works: The authors calculated an “exposure” score for each of 774 occupations and 115 industries by comparing human skills to AI application areas. For the purpose of the study, exposure is neither positive nor negative; it’s a measure of how likely a job or industry would change in response to developments in language processing.

  • The authors used a U.S. Department of Labor database that describes each occupation in terms of 52 human abilities. Such abilities include dynamic strength, hearing sensitivity, mathematical reasoning, and written expression, and they’re weighted according to their importance to a given occupation.
  • Crowdsourced workers scored the relevance of language modeling to each ability. For instance, language modeling has little relevance to dynamic strength but great relevance to written expression.
  • The authors used the scores as weighted variables in an equation that aggregated the relevance of language modeling to the human abilities involved in each occupation and industry.

Results: The authors concluded that telemarketing was most exposed to impact by language models. Among the 20 occupations with the greatest exposure, 14 were post-secondary teaching roles including university-level teachers of language, history, law, and philosophy. The top 20 also included sociologists, political scientists, arbitrators, judges, and psychologists. Among industries, the authors found that legal services were most exposed. Of the 20 industries with the greatest exposure, 11 involved finance including securities, insurance, and accounting.

Behind the news: The authors adapted their method from a 2021 study that scored each occupation’s and each industry’s exposure to AI areas defined by the Electronic Frontier Foundation, including game playing, computer vision, image generation, translation, and music recognition. The previous study found that the most exposed jobs were genetic counselors, financial examiners, and actuaries. The most exposed industries were financial securities, accounting, and insurance.

Why it matters: It seems clear that emerging AI technologies will have a significant impact on human labor, but where and how is not yet clear (and may not be even as the effects become more pervasive). This study can serve as a heads-up to some professionals that it’s time to prepare — and a signal to AI builders what sorts of models are likely to have an impact.

We’re thinking: As the authors note, an occupation’s exposure to AI does not necessarily put jobs at risk. History suggests the opposite can happen. A 2022 study found that occupations exposed to automation saw increases in employment between 2008 and 2018. Several other studies found that countries with high levels of automation also tend to have high overall levels of employment.


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