According to Fortune, OpenAI co-founder Andrej Karpathy used AI to analyze the U.S. labor market, assigning a 0-to-10 exposure score to various occupations based on data from the U.S. Bureau of Labor Statistics. The results showed that white-collar roles such as software development, data science, financial analysis, law, and writing received scores as high as 9, while high-paying professions earning over $100,000 annually averaged a score of 6.7; in contrast, manual and service-oriented jobs like construction workers, caregivers, and barbers scored only 1 to 2. The data sparked widespread attention but was quickly deleted by Karpathy after being widely misinterpreted. A recent report from Anthropic reached similar conclusions; however, Citadel Securities countered that evidence of AI actually replacing jobs remains limited, with demand for software engineers projected to increase by 11% year-over-year by 2026.
OpenAI Co-founder Analyzes AI Exposure in the U.S. Labor Market, with High-Salary Jobs Most Affected
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Summary
OpenAI co-founder Andrej Karpathy analyzed U.S. labor market data using AI, rating job exposure on a 0–10 scale. High-salary roles such as software development and legal work scored 9, while physical jobs scored 1–2. The data sparked controversy but was later removed. Anthropic’s report echoed similar findings, while Citadel Securities pushed back, citing a projected 11% increase in demand for software engineers by 2026. Meanwhile, MiCA and CFT regulations continue to shape the global tech and finance sectors.
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