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    Home»Big Tech & AI»Yale Finds No Proof AI Is Killing Jobs, Calls Labor Market Panic Premature

    Yale Finds No Proof AI Is Killing Jobs, Calls Labor Market Panic Premature

    By Henry KanapiOctober 4, 20253 Mins Read
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    A new Yale study finds no evidence that AI has caused job losses across the US economy, countering widespread fears of mass displacement.

    Researchers at Yale’s Budget Lab analyzed labor-market data collected since ChatGPT’s release in November 2022 and concluded that the mix of occupations has changed no faster than in previous waves of technological change.

    “Our metrics indicate that the broader labor market has not experienced a discernible disruption since ChatGPT’s release 33 months ago, undercutting fears that AI automation is currently eroding the demand for cognitive labor across the economy.”

    The team compared the pace of occupational turnover during the AI boom with earlier transitions triggered by computers and the internet. The result: changes in job composition are only about one percentage point higher than in the late 1990s, when offices were adopting the web. Even industries with high AI exposure — information, finance, and professional services — saw most of their recent shifts begin before ChatGPT’s launch.

    “The job mix for AI appears to be changing faster than it has in the past, although not markedly so.”

    Yale also examined how AI might be affecting younger workers entering the labor force. Comparing recent college graduates aged 20–24 with older graduates aged 25–34, researchers found only a slight increase in the difference between their job distributions. The dissimilarity index between the two groups has generally stayed within 30%–33% since 2021, suggesting that early-career workers are not yet being displaced by AI in measurable numbers.

    The authors cautioned that this trend could reflect a slowing job market rather than automation itself, noting that sample sizes for younger workers are smaller and noisier.

    “While some slight upward momentum is visible, it remains consistent with prior patterns and does not provide clear evidence of AI-driven change.”

    The findings challenge the narrative that generative AI is rapidly automating white-collar work. Yale notes that technological disruption historically unfolds slowly: computers took nearly a decade after release to become standard in offices, and even longer to reshape workflows.

    Yale researchers plan to track employment monthly to detect any structural changes.

    “The picture of AI’s impact on the labor market that emerges from our data is one that largely reflects stability, not major disruption at an economy-wide level. While generative AI looks likely to join the ranks of transformative, general-purpose technologies, it is too soon to tell how disruptive the technology will be to jobs.”

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