70% of jobs will change by 2030. But AI won’t mean less work.
By Sander SaarPublished Updated Length
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70% of jobs will change by 2030. But AI won’t mean less work.
This video examines how artificial intelligence is set to reshape work by 2030, arguing that technological efficiency increases overall demand rather than reducing jobs. The presenter illustrates Jevons paradox through historical shifts such as Uber, ATMs, and modern radiology. In addition, the presentation covers how emerging technologies generate brand-new careers, including LinkedIn's Full Stack Builder role.
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Why AI means more work, not less
Tomer Cohen and the presenter argue that although skills will change by 2030, AI will increase overall work rather than reduce it.
Jevons paradox and historical examples
The presenter explains Jevons paradox using historical analogies: Uber expanding the ride market, fuel-efficient cars increasing driving, electric lighting multiplying energy consumption, and ATMs leading to more bank tellers.
The AI rebound in radiology and knowledge work
The presenter reviews how AI impacts medicine, highlighting Geoffrey Hinton's corrected prediction about radiologists and the resulting demand surge.
New jobs and emerging roles like the Full Stack Builder
The discussion covers how each technological shift creates previously unimaginable careers, highlighting new titles like LinkedIn's Full Stack Builder.
Transcript
When we look at like the skills required to do your job, by 2030, they will change by 70%.
AI won't mean less work, it will mean more. Look at Uber. It didn't kill taxis, it doubled the use of ride services in 10 years, from 175 million rides in New York City to 300 million rides last year. That's what happens when something gets cheaper and easier, and AI is about to do that to everything. Economists call this Jevons paradox or the rebound effect. When something gets cheaper, we don't use less, we use way more. Cars are the classic example. When fuel economy was cut in half, people didn't just pocket the savings, they started driving more.
Electrical lights is even crazier. Moving from gas lamps to electrical bulbs should mean less energy, right? No. In the UK, lighting consumption grew by 34,000 times since the 1800s. Cheaper lights means we're gonna light everything all night. When ATMs were introduced, everyone said bank tellers are finished. But ATMs meant branches cheaper to run, so banks opened more of them, from 100,000 to 400,000 branches, and teller jobs still grew. The work stayed, the job, however, changed from cash handler to sales advisor.
Now with AI. AI makes thinking and intelligence cheaper. Analysis, drafts, images, content. So that market won't want less, it will want more. Geoffrey Hinton, the godfather of AI, said people should stop training radiologists now.
It's just completely obvious that within 5 years, um, deep learning is going to do better than radiologists.
He recently admitted he was wrong. The future, he said, is AI plus radiologists, more efficient, more accurate. And today, 76% of the FDA-approved devices are AI in radiology. Radiologists' pay has increased, and there's the biggest radiologist shortage in history. Now, not every job grows, but the pattern is clear. The job you have today might not exist in 5 years, but the work there will be more of it than ever. Think about it. How would you explain today's kid's dream job to your grandfather? I want to become a YouTuber, an influencer, a life coach.
He would say, you do what? Every technology shift creates jobs that seem ridiculous for a generation earlier. AI will be no different. So stop asking, will AI replace me? And start asking, where is AI about to make something so cheap and accessible that the demand explodes? What if AI agents can make you 10x more impactful in an organization?
And agents are also starting to scale people's impact. Up by 10x in some cases, so they have more time to invent more.
LinkedIn just created a new role called Full Stack Builder. People who take products from an idea to actually launching it with AI.
We call it the Full Stack Builder model. The goal itself is to empower great builders to take their idea and to take it to market regardless of their role in the stack and which team they're on. It's really a fluid interaction between human and machine.
And that job didn't exist a year ago.