Geoffrey Hinton, AI pioneer, shares his concerns about the future: “There’s a longer-term problem of these things taking over”

Generative artificial intelligence systems have been advancing at breakneck speeds over the past few years. Many have cautioned that they will cause tremendous disruption in the labor market, replacing millions of human workers in just about every field.

This is one of the short-term risks that the ‘Godfather of AI’, Geoffrey Hinton, envisions which he says is “bad for society” and that “we need to figure out what to do about that, although it’s not clear what to do.” However, the 2024 Nobel physics laureate, awarded to Hinton for his pioneering work developing foundational techniques that are a part of modern AI, has some ideas about how we can tackle longer-term risks.

How humans can stay in control of AI when it becomes smarter than us

While many may think that AI systems becoming smarter than humans is just science fiction, Hinton doesn’t see it that way. “My guess is, in between five and 20 years from now, there’s a good chance – a 50% chance – we’ll get AI smarter than us,” he said in an interview.

So for him that posits the question then, “What’s going to happen when we’ve created beings that are more intelligent than us?”

“There’s a longer-term problem of these things taking over,” he explained. He suggested it would “make a lot of sense” for us to “do a lot of basic research now on whether we can stay in control,” before AI systems become smarter than us.

Part of the difficulty will come from the fact that these systems are not programmed and “we don’t know exactly how it’s going to work.” The generative AI models are given an algorithm which they use to train themselves on mountains of data that “at the end [the AI] has extracted its structure from the data.”

Teach the machines to behave like we teach children to behave

Hinton feels that “making these systems behave in a reasonable way is much like making a child behave in a reasonable way.”

“You can reinforce, you can reward it for good behavior, punish it for bad behavior, but the main control you have is demonstrating good behavior, training it on good behavior,” he explained. “So that’s what it observes, and that’s what it mimics. And it’s the same for these systems.”

“So it’s very important we train them on the kind of behavior that we would like to see in them,” Hinton added.

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