‘Godfather of AI’ Quits Google to Warn About ‘Scary’ Technology

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A groundbreaking innovator in the field of artificial intelligence (AI) is sounding the alarm over the dangers imposed by the technology for which his work laid the foundation.

Geoffrey Hinton, the British computer scientist who has been called the “Godfather of AI,” recently left his position as a vice president and engineering fellow at Google so he could join the dozens of other experts in the field speaking out about the threats and risks of AI.

“It is hard to see how you can prevent the bad actors from using it for bad things,” Hinton, 75, told The New York Times in an interview.

Following the launch of OpenAI’s latest version of its GPT chatbot in March, other AI professionals signed an open letter, written by the nonprofit Future of Life Institute, warning that the technology poses “profound risks to society and humanity.”

Hinton, like the letter’s signatories, said he finds the recent advancements in AI to be “scary” and worries about what they might mean for the future—particularly now that Microsoft has incorporated the technology into its Bing search engine.

With Google now rushing to do the same, Hinton noted that the race between Big Tech companies to develop more powerful AI could easily spin out of control.

One particular facet of AI technology that concerns the computer scientist is its ability to create false images, photos, and text to the point where the average person will “not be able to know what is true anymore.”

He also warned that, in the future, AI could potentially replace humans in the workplace and be used to create fully autonomous weapons.

“The idea that this stuff could actually get smarter than people—a few people believed that,” Hinton said. “But most people thought it was way off. And I thought it was way off. I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that.”

Hinton’s Departure

Hinton is primarily known for his role in the development of deep learning, a form of machine learning that trains computers to process data like the human brain.

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