A British-Canadian researcher has been awarded the Nobel Prize in physics for his work on the foundations of machine learning and artificial intelligence.
Geoffrey Hinton of the University of Toronto received the award Tuesday morning, along with John Hopfield, a researcher at Princeton University.
“I’m stunned. I had no idea this would happen,” Mr. Hinton said when reached by the Nobel committee on Tuesday.
According to the Royal Swedish Academy of Sciences, the prize was awarded to MM. Hinton and Hopfield for their “fundamental discoveries and inventions that enable machine learning using artificial neural networks.”
Ellen Moons, a member of the Nobel committee at the Royal Swedish Academy of Sciences, explains that the two winners “used fundamental concepts from statistical physics to design artificial neural networks that function like associative memories and find patterns in large data sets.
She adds that these networks have been used to advance physics research and “are now part of our daily lives, for example for facial recognition and language translation.”
While the committee paid tribute to the science behind machine learning and artificial intelligence, Ms. Moons also mentioned its flip side, saying that “while machine learning has enormous benefits, its development rapid has also raised concerns about our future.
“Collectively, humans have a responsibility to use this new technology safely and ethically for the greatest benefit of humanity,” she said.
Mr. Hinton shares these concerns. He left his job at Google so he could speak more freely about the dangers of the technology he helped create.
Mr. Hinton warned that he continued to worry about “a number of possible negative consequences” of his work on machine learning, “particularly the threat of these things getting out of control,” but that he would do it again anyway.
The physics prize comes with a cash prize from a bequest from the prize’s creator, Swedish inventor Alfred Nobel.
