STOCKHOLM — Two pioneers of artificial intelligence — John Hopfield and Geoffrey Hinton — won the Nobel Prize in physics Tuesday for helping create the building blocks of machine learning that is revolutionizing the way we work and live but also creates new threats for humanity.

Hinton, known as the godfather of artificial intelligence, is a citizen of Canada and Britain who works at the University of Toronto, and Hopfield is an American working at Princeton.

“These two gentlemen were really the pioneers,” said Nobel physics committee member Mark Pearce.

The artificial neural networks — interconnected computer nodes inspired by neurons in the human brain — the researchers pioneered are used throughout science and medicine and “have also become part of our daily lives,” said Ellen Moons of the Nobel committee at the Royal Swedish Academy of Sciences.

Hopfield, whose 1982 work laid the groundwork for Hinton’s, told The Associated Press, “I continue to be amazed by the impact it has had.”

Hinton predicted that AI will have a “huge influence” on civilization, bringing improvements in productivity and health care.

“It would be comparable with the Industrial Revolution,” he said in an open call with reporters and officials of the Royal Swedish Academy of Sciences.

“Instead of exceeding people in physical strength, it’s going to exceed people in intellectual ability. We have no experience of what it’s like to have things smarter than us. And it’s going to be wonderful in many respects,” Hinton said. “But we also have to worry about a number of possible bad consequences, particularly the threat of these things getting out of control.”

The Nobel committee also mentioned fears about AI’s possible drawbacks.

Moons said that while it has “enormous benefits, its rapid development has also raised concerns about our future. Collectively, humans carry the responsibility for using this new technology in a safe and ethical way for the greatest benefit of humankind.”

Hinton, who quit a role at Google so he could speak more freely about the dangers of the technology, shares those concerns.

“I am worried that the overall consequence of this might be systems more intelligent than us that eventually take control,” Hinton said.

For his part, Hopfield, who signed early petitions by researchers calling for strong control of the technology, compared the risks and benefits to work on viruses and nuclear energy, capable of helping and harming society.

Hinton, 76, helped develop a technique in the 1980s known as backpropagation, instrumental in training machines how to “learn” by fine-tuning errors until they disappear. It’s similar to the way a student learns, with an initial solution graded and flaws identified and returned to be fixed and repaired.

Hinton’s team at the University of Toronto wowed peers by using a neural network to win the prestigious ImageNet computer vision competition in 2012. That spawned a flurry of copycats and was “a very, very significant moment in hindsight and in the course of AI history,” said Stanford University computer scientist and ImageNet creator Fei-Fei Li.

“Many people consider that the birth of modern AI,” she said.

Hopfield, 91, created an associative memory that can store and reconstruct images and other types of patterns in data, the Nobel committee said.

“What fascinates me most is still this question of how mind comes from machine,” Hopfield said in a video posted online by the Franklin Institute after it awarded him a physics prize in 2019.

Hinton used Hopfield’s network as the foundation for a new network that uses a different method, known as the Boltzmann machine, that the committee said can learn to recognize characteristic elements in a given type of data.