Andrej Karpathy, co-founder of OpenAI and former Tesla AI director, released an interactive “AI Job Exposure Map” on March 15 that quickly went viral across the internet. The project analyzed 342 occupations from the U.S. Bureau of Labor Statistics Occupational Outlook Handbook, feeding job descriptions into a large language model to assign each role an exposure score from 0 to 10 — measuring how much AI could theoretically reshape that work. The map covered approximately 143 million U.S. jobs and displayed results in a colorful treemap visualization at karpathy.ai/jobs, where rectangle size reflected employment numbers and color represented exposure levels (green for minimal disruption, deep red for extensive automation).
Key Data: 42% of Jobs Highly Exposed, Average Score 4.9
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 the averages hide a dramatic reality: roughly 42% of American jobs — about 59.9 million workers earning an estimated $3.7 trillion in annual wages — scored 7 or higher on the exposure scale. Breaking the numbers down further, about 6.2 million jobs fell into the minimal exposure category, 47.2 million as low, 29.7 million as moderate, 34.7 million as high, and 25.2 million as very high.
The analysis also produced a counterintuitive twist about pay. Lower-income jobs averaging under $35,000 annually scored around 3.4 on exposure, while occupations paying more than $100,000 averaged 6.7. In other words, the higher the paycheck, the more likely the job involved tasks that artificial intelligence systems can replicate or assist with today. Education levels showed a similar pattern: workers without college degrees averaged roughly 4.1, those with bachelor's degrees topped the chart at about 6.7, and advanced degree holders landed around 5.7.
Which Occupations Face Highest Risk? Which Are Safest?
Looking at individual occupations paints an even sharper picture. Medical transcriptionists scored a perfect 10, reflecting how speech recognition and automated documentation systems already perform many of those tasks. Lawyers, accountants, financial analysts and management consultants often scored around 9, largely because their work revolves around structured information, documents and research. Ironically, software developers — the people building many AI tools — also ranked high, often scoring between 8 and 9. Roles such as administrative assistants, bookkeeping clerks and customer service representatives showed similarly elevated exposure levels due to their reliance on digital workflows.
On the opposite end of the spectrum, jobs that happen in the physical world rather than on a computer screen fared far better. Plumbers, electricians and construction laborers typically scored between 0 and 2, highlighting the persistent difficulty of automating unpredictable, hands-on tasks.
Elon Musk Responds: 'All Jobs Will Be Optional'
The map's rapid spread online triggered commentary across the technology world, including a brief response from Tesla and SpaceX CEO Elon Musk. Replying to a thread about the visualization, Musk wrote: “All jobs will be optional. There will be universal high income.” The comment echoed Musk's long-standing argument that advanced artificial intelligence and robotics could eventually produce enough economic abundance to reduce reliance on traditional employment.
Despite the attention, Karpathy quickly removed the original website and its GitHub repository, explaining in a follow-up post that the project was a quick experiment — what he described as a two-hour “vibe-coded” exploration inspired by a book he was reading. He noted that the project's exploratory nature was widely misunderstood despite clear disclaimers. Taking the site down did little to slow its spread, however: archived copies appeared almost immediately on the Wayback Machine, and the code repository was forked numerous times by developers who replicated the dataset, scoring rubric, and visualization tools.
The episode illustrates two realities of the modern internet: AI research can ignite global debates overnight, and once data escapes into the open web, it rarely disappears. For now, Karpathy's experiment remains less a prophecy of job losses than a snapshot of how current AI systems overlap with human work. The takeaway is refreshingly straightforward: if your entire job happens on a screen, artificial intelligence may soon become your co-worker — or your fiercest competitor.