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Conrad Shaw

Is Universal Basic Income Coming to Save Us From AI Layoffs?

A student interviewed Conrad Shaw recently for a school project and asked what he should study in college. Conrad didn't have a good answer. Whatever the student picks might not exist as a career by the time he graduates, and Conrad says that's not pessimism. That's just what he's watching happen across film, software, and most knowledge-work fields right now.

Conrad is a filmmaker, mechanical engineer, and Universal Basic Income (UBI) advocate known as the UBI Guy. He's spent a decade making the case for universal basic income on its merits, long before AI layoffs made it an urgent conversation. The argument was always that the current safety net is too broken and too punitive to catch the people who need it. AI displacement just raised the stakes on getting it right.

He joins Work Tech Weekly to argue that the objections to UBI don't hold up to the data, that the current system has no answer for what's coming, and that the funding mechanism may turn out to be the most straightforward part of the whole problem.

Is Universal Basic Income Coming to Save Us From AI Layoffs?
  32 min
Is Universal Basic Income Coming to Save Us From AI Layoffs?
Work Tech Weekly
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Why This Automation Wave Is Different

Every previous wave of automation replaced a specific task, and workers found the next thing. What AI is automating now is harder to route around. In past waves, you could at least point to where the new jobs were coming from. "They never tell you what they're going to be," Conrad says of the optimists. "They're like, oh, they'll magically appear out of nowhere."

The "just learn to code" answer already ran its course. The next version of that logic is to learn a trade—just pivot to the jobs AI can't touch yet. Conrad follows that thread out: workers flood into those fields, wages compress, and eventually there aren't enough jobs there either. At some point, the market can't absorb everyone who needs it. "Who's gonna hire a plumber when they don't have an income?" Conrad says. "They're just going to figure it out themselves."

What makes this cycle different from every previous one is that the thing being automated isn't a task. It's the capacity to learn a new one. That's what made retraining work before. Workers could move up the skill ladder because the ladder kept adding rungs. Conrad's concern is that AI is compressing the ladder faster than anyone can climb it, and the people who get left behind aren't going to have a good answer for what comes next.

The Laziness Argument Doesn't Survive the Data

The most common objection to UBI is that people will stop working if you give them money. Across hundreds of thousands of participants in pilots run globally, that's not what happens. People keep working. Where hours decline at all, it tends to be new mothers and students, and Conrad notes those are people we'd arguably want spending their time differently anyway.

The distinction he draws is between work and jobs. Work is everything: raising kids, building something, taking care of someone who can't take care of themselves. Jobs are the slice of that where someone pays you. "People will always work," he says. "The question is whether they'll job." When nobody is desperate enough to take a bad job cheap, the worst jobs have to pay more. The most meaningful ones can afford to pay less. The labor market reorganizes around what work is actually worth to the person doing it.

The current safety net was built on a different logic entirely. Conrad puts the number at roughly 80% of eligible people who never reach the benefits they're supposed to receive, lost to stigma, bureaucratic complexity, and eligibility rules designed to screen people out before helping them in. His way of putting it: a net has holes, and a floor doesn't.

The AI Dividend

Conrad's answer on funding is a question: where is all the money going? AI companies are generating revenue per employee at multiples that would have been hard to imagine five years ago. If jobs are how most people access the economy and those jobs are disappearing, the productivity gains have to land somewhere. "If all the money is flooding toward AI," Conrad says, "then that's where it should come back from."

He calls it the AI dividend — the idea that the technology doing the displacing should foot the bill for the floor that catches the workers. Whether that happens through taxation or regulation is a policy question, but Conrad's point is that the resources exist and the math works if anyone is willing to do it.

So is UBI coming? Conrad thinks so. His case is that the current system was built for a labor market that AI is dismantling, and that job retraining programs and political optimism aren't going to close the gap between what the economy produces and what workers can actually access.

At some point, he argues, UBI stops being a policy preference and becomes the only response that actually matches the scale of the problem.

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