Study: AI Impacts 80 Percent of Workers’ Jobs

A new study that analyzes the impact of artificial intelligence on the workforce, finds that 80% of workers will have their jobs impacted by GPTs (Generative Pretrained Transformer) language models like ChatGPT.

AI will improve the labor force to make it more efficient, but the evolution of GPTs will have an increasing impact in the future.

“These technologies can have pervasive impacts across a wide swath of occupations in the U.S.,” OpenAI and the University of Pennsylvania researchers wrote, adding “additional advancements supported by GPTs, mainly through software and digital tools, can have significant effects on a range of economic activities.

“However, while the technical capacity for GPTs to make human labor more efficient appears evident, it is important to recognize that social, economic, regulatory, and other factors will influence actual labor productivity outcomes. As capabilities continue to evolve, the impact of GPTs on the economy will likely persist and increase, posing challenges for policymakers in predicting and regulating their trajectory.”

The study suggests 80% of workers might have at least 10% of those work tasks impacted by the invention of ChatGPT, while 19% of workers might have half or more of their work impacted by it.

The study, notably, does not distinguish “between labor-augmenting or labor-displacing effects,” but it does note higher-income jobs have a great “exposure” to AI language tools.

The study defines exposure by reducing the human time to complete a task by at least 50%.

It suggests GPT tech will be helping workers become more efficient more than replacing workers like “mathematicians, interpreters, accountants, legal secretaries, writers and authors,” the New York Post reported.

Blue-collar workers are less likely to be impacted by AI language tools.

“Today’s GPTs can do a lot,” OpenAI researcher Pamela Mishkin tweeted. “Over the past few years we’ve seen them get better and better at solving more and more complex tasks with fewer and fewer examples of less and less related tasks.

“The paper examines this trend not any particular model available today.”

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