{
  "title": "The Labor Market Impact of Artificial Intelligence: Evidence from US Regions",
  "publication": "IMF Working Papers, September 13, 2024",
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  "summary": "This paper empirically investigates the impact of Artificial Intelligence (AI) on employment. Exploiting variation in AI adoption across US commuting zones using a shift-share approach, I find that during 2010-2021, commuting zones with higher AI adoption have experienced a stronger decline in the e",
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    {
      "heading": "Summary findings",
      "content": "- The paper empirically investigates the impact of Artificial Intelligence (AI) on employment using variation in AI adoption across US commuting zones.\n- During 2010-2021, commuting zones with higher AI adoption experienced a stronger decline in the employment-to-population ratio.\n- The negative employment effect is primarily borne by:\n  - the manufacturing and low-skill services sectors,\n  - middle-skill workers,\n  - non-STEM occupations,\n  - individuals at the two ends of the age distribution.\n- The adverse impact is more pronounced on men than women."
    },
    {
      "heading": "Methodology",
      "content": "- Empirical strategy exploits variation in AI adoption across US commuting zones using a shift-share approach."
    },
    {
      "heading": "Subject matter and keywords",
      "content": "- Subject: Artificial intelligence; Employment; Employment rate; Labor; Labor markets; Population and demographics; Technology\n- Keywords: AI adoption data; AI production; Artificial intelligence; classification scheme; Employment; employment effect; employment impact; employment outcome; Employment rate; employment share; Global; impact of artificial intelligence; industry AI adoption; industry classification; labor; labor market impact; Labor markets; local labor markets; low-skill services sectors; middle-skill worker; robot penetration; shift share; technology\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2024/09/13/the-labor-market-impact-of-artificial-intelligence-evidence-from-us-regions-554845"
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    "Authors: Yueling Huang",
    "Published: September 13, 2024",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798400288555.001",
    "The paper empirically investigates the impact of Artificial Intelligence (AI) on employment using variation in AI adoption across US commuting zones.",
    "During 2010-2021, commuting zones with higher AI adoption experienced a stronger decline in the employment-to-population ratio.",
    "The negative employment effect is primarily borne by:",
    "The adverse impact is more pronounced on men than women.",
    "Empirical strategy exploits variation in AI adoption across US commuting zones using a shift-share approach.",
    "Subject: Artificial intelligence; Employment; Employment rate; Labor; Labor markets; Population and demographics; Technology",
    "Keywords: AI adoption data; AI production; Artificial intelligence; classification scheme; Employment; employment effect; employment impact; employment outcome; Employment rate; employment share; Global; impact of artificial intelligence; industry AI adoption; industry classification; labor; labor market impact; Labor markets; local labor markets; low-skill services sectors; middle-skill worker; robot penetration; shift share; technology",
    "**Working Paper**"
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