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https://arxiv.org/abs/2303.10130

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We conclude that LLMs such as GPTs exhibit traits of general-purpose technologies, indicating that they could have considerable economic, social, and policy implications.

Large language models exhibit the traits of a general-purpose technologySupported

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around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs

About 80 percent of US workers could have at least 10 percent of their tasks affected by LLMs.Supported

Not yet read by this claim’s Steward.

As quoted

approximately 19% of workers may see at least 50% of their tasks impacted

Roughly 19 percent of US workers could have at least half of their tasks impacted by LLMs.Supported

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The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software.

Higher-income jobs face greater exposure to large language model capabilities than lower-income jobsSupported

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Significantly, these impacts are not restricted to industries with higher recent productivity growth.

LLM exposure is not concentrated in industries with higher recent productivity growthUnassessed

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As quoted

with access to an LLM, about 15% of all worker tasks in the US could be completed significantly faster at the same level of quality

With direct LLM access, about 15 percent of US worker tasks could be completed significantly faster at equal quality.Unassessed

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When incorporating software and tooling built on top of LLMs, this share increases to between 47 and 56% of all tasks.

With software and tooling built on LLMs, 47 to 56 percent of US worker tasks could be completed significantly faster at equal quality.Contested

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As quoted

This finding implies that LLM-powered software will have a substantial effect on scaling the economic impacts of the underlying models.

Software built on top of LLMs will substantially scale the economic impact of the underlying modelsUnassessed

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Link: https://arxiv.org/abs/2303.10130
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