If AI Must Pay Taxes, How Much Should It Owe?

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Hello, subscriber. This is Oswarld’s Knowledge Talking.

Two weeks ago, Block, the fintech company led by Jack Dorsey, laid off 40% of its workforce — about 4,000 people. Dorsey explained it this way: “AI tools have changed the very way we build and run the company.” What’s striking is how the market reacted. The stock jumped 24%. That’s roughly $6 billion added to market capitalization in a single day — about $1.5 million in added corporate value for every employee let go.

The same week, Andrew Yang — former U.S. presidential candidate and entrepreneur — said in a CNBC interview: “We should stop taxing labor and start taxing AI agents.” This isn’t just political rhetoric. As Block’s case shows, when AI displaces human jobs, the very foundation of government tax revenue starts to wobble. Today I want to unpack this structural problem. (Personally, Yang is one of the Korean-Taiwanese-American politicians I follow with particular interest.)

The Quiet Revolution: Downsizing Without Layoffs

AI’s shock to the labor market is showing up first not as mass layoffs, but as a disappearance of new hiring. Dario Amodei, CEO of Anthropic, warned in a May 2025 Axios interview that “up to 50% of entry-level white-collar jobs could be automated within the next one to five years.” He also projected that unemployment could spike to 10-20%. What makes this warning notable is that it came from the CEO of the very company building the automation technology in question.

Let’s look at the numbers. According to Federal Reserve Bank of New York data, the U.S. unemployment rate for recent college graduates (ages 22-27) stood at 5.7% in Q4 2025 — above the overall unemployment rate of roughly 4%. For the first time in history, the unemployment rate for college graduates has exceeded the overall rate. The underemployment rate¹ hit 42.5%, the highest level since 2020.

Goldman Sachs Research dug into the cause: in the industries where college graduates typically find work — information technology, finance, and professional services — average monthly job growth between 2023 and 2025 came in at -9,000. Over the same period, industries dominated by non-college-graduate workers averaged +12,000 jobs per month. In other words, new hiring is freezing up first in precisely the industries where AI adoption is most aggressive.

Andrew Yang put it bluntly: “The easiest person to fire is the person you haven’t hired yet.”