Elon Musk Weighs In After Andrej Karpathy’s AI Job Exposure Map Goes Viral

The latest viral AI experiment didn’t come from a think tank or government task force—it came from a weekend coding sprint by AI researcher Andrej Karpathy that mapped how vulnerable every major U.S. occupation might be to automation.

Nearly 60 Million U.S. Jobs Flagged as Highly Exposed in Karpathy’s AI Automation Map

Andrej Karpathy, a co-founder of OpenAI and former Tesla artificial intelligence (AI) director, released an interactive “AI Job Exposure Map” on March 15, analyzing 342 occupations drawn from the U.S. Bureau of Labor Statistics (BLS) Occupational Outlook Handbook.

The project evaluated roughly 143 million U.S. jobs by feeding job descriptions into a large language model and assigning each role an exposure score from zero to 10, measuring how much AI could theoretically reshape that work.

The results were displayed in a colorful treemap visualization hosted at karpathy.ai/jobs, where rectangle size reflected employment numbers and color represented exposure levels, ranging from green for minimal disruption to deep red for roles that could see extensive automation. In short: the bigger and redder the box, the more attention it demanded.

Across the entire U.S. workforce, the weighted average exposure landed around 4.9 out of 10, suggesting moderate potential for AI influence overall. But averages hide a lot of drama. Roughly 42% of American jobs—about 59.9 million workers earning an estimated $3.7 trillion in annual wages—scored seven or higher on the exposure scale.

Breaking the numbers down further, about 6.2 million jobs fell into the minimal exposure category, while 47.2 million were classified as low. Another 29.7 million landed in the moderate range. The more striking figures appeared at the top of the scale: roughly 34.7 million jobs ranked high, and 25.2 million fell into the very high exposure bracket.

Karpathy’s analysis also produced a counterintuitive twist about pay. Lower-income jobs averaging under $35,000 annually scored around 3.4.