Artificial intelligence has become the latest excuse for reviving one of the oldest bad ideas in economic policy: a universal basic income. Recent pieces in Newsweek, the LSE Business Review, and Fortune have all helped push the idea that AI may soon wipe out so many jobs that Washington will need to send everyone a check.

That makes for a catchy headline. It also makes for terrible economics.

The right question is not whether AI will disrupt work. Of course it will. The right question is this: after more than 100 local guaranteed-income experiments, what have we actually learned?

The answer is much less flattering to UBI than its promoters would like.

What 122 UBI-Style Pilots Show

A new AEI working paper by Kevin Corinth and Hannah Mayhew gives the best recent overview of the evidence. Per their study, there were 122 guaranteed basic income pilots across 33 states and the District of Columbia between 2017 and 2025. Those pilots allocated about $481.4 million in transfers to 40,921 recipients, with 61,664 total participants including control groups. The average recipient got about $11,765, the average pilot lasted 18.4 months, and the average monthly payment was $616.

That sounds like a mountain of evidence. It is not.

Of those 122 pilots, only 52 had published outcomes. Only 35 used randomized designs. Only 30 reported employment outcomes. So the case for UBI is not being built on some giant pile of clear, clean evidence. It is being built on a much smaller stack of studies, many of them weak, limited, or badly timed.

And here is the kicker. Among the 30 randomized pilots with published employment results, the average effect was a 0.8 percentage-point increase in employment. UBI fans will rush to wave that around. They should slow down.

AEI shows that the bigger and more credible studies tell a very different story. Among the four pilots with treatment groups of at least 500 participants, which together account for 55 percent of all treatment-group participants, the mean effect on employment was minus 3.2 percentage points. AEI also estimates a mean income elasticity of -0.18, which is consistent with standard labor-supply economics. 

In plain English, when people receive more unearned income, work tends to fall at the margin. Shocking, I know. Economics still works.