Calls for governments to push “pro-worker AI” sound appealing. The idea is simple: If policymakers deftly guide how the technology develops, they can make sure it helps workers instead of replacing them. What’s not to like?
Here’s your trouble: Technology almost never works that neatly. Its effects on jobs are usually messy, unpredictable, and shaped by millions of decisions from businesses and entrepreneurs—not by a policy plan designed in Washington.
That’s a core point in a recent critique by economist Joshua Gans of a proposal from Daron Acemoglu, David Autor, and Simon Johnson to steer AI toward worker-friendly uses. Gans says the idea runs into a basic contradiction. The proposal defines “pro-worker” technology as something that makes human capabilities and expertise more valuable. But those things are valuable partly because not everyone has them. If a new technology spreads skills more widely, it may help more workers overall—while at the same time reducing the pay advantage of those who once had rare skills.