Years ago, Bill Gates warned that robots would “replace many jobs.” Elon Musk reiterates that AI could make work optional. It seemed like a conversation about billionaires, very far removed from real life. Then Giorgio Parisi, a Nobel laureate in physics, discreetly joined the chorus: not from a TED stage, but with equations about productivity and time. His conclusion is exciting and brutal at the same time.
According to the expert, society is heading towards a world where there will be more free hours than ever before. But many people, according to Parisi’s analysis, will no longer have a job.
Giorgio Parisi didn’t win the 2021 Nobel Prize for speaking about Elon Musk or Bill Gates. He won the prize for his work on complex systems: chaotic, disordered sets in which everything influences everything else. Then he took a bold step: He applied this thinking to business, work and the astonishing efficiency of AI.
When Parisi heard tech leaders predict a jobless future, he didn’t laugh. Contact their models. In his view, an economy is like a turbulent fluid: when one force becomes too powerful, it changes all currents. AI and automation are that force. Not only do they eliminate some jobs; You change the way you work.
What you describe is not science fiction. It is a mechanical change in the way value is created.
In one of the scenarios he examined, per capita productivity skyrockets thanks to machines and software. A small number of people operating massive AI systems could feed an entire society. Let’s imagine 10% of the workforce managing everything: logistics, healthcare, energy, administration, creative industries, powered by generative AI. The salaries of these people could be very high. For the remaining 90%, traditional employment would be reduced or eliminated.
It seems to be a luxury problem: more free time for everyone. But the question becomes simple: Who gets the money when machines do the work? Parisi’s warning is cold and technical. When the owners of the systems take almost all of the profits, the majority have time but no salary, status or bargaining power.
Here Musk and Gates unexpectedly meet a Nobel physicist. Not in emotions, but in the direction of the curve.
Parisi’s analysis is based on abstract graphs, lines separating productivity and employment, and “steady-state” simulations in which growth continues while work declines. Then apply this to a real city, a real family, or a twenty-something choosing a career. The characters become intimate. You get a future where a supermarket uses a single manager and end-to-end automation, a hospital does triage with AI, and a media company works with three editors and a content engine.
Elon Musk sees this as a path to a universal, high-income world. Bill Gates talks about taxing robots to fund social protection. Parisi does not predict the political reaction. It simply means that if the rules are not rewritten, mathematics leads to instability. Too much time, too little income.
If the traditional job disappears, the smartest decision today is almost contradictory: start looking at free time as your most important asset, not as your salary. This means that you now learn to live in shorter cycles of paid work and longer cycles of “productive downtime” where you can still grow, learn and socialize.
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