“Godfather of AI” resigns from Google: What happens when artificial intelligence gets more intelligent than us?

Renowned as the “godfather of AI,” Geoffrey Hinton has resigned from Google, at the same time expressing concerns about how artificial intelligence may contribute to the proliferation of misinformation, potentially disrupt job markets, and uncertainty towards the existential threat posed by the creation of true digital intelligence.

Artificial intelligence – abstract artistic interpretation. Image credit: geralt via Pixabay, free license

Hinton, known for developing a neural network with his students in 2012 at the University of Toronto, decided to leave Google to freely discuss the dangers associated with the use and future advances of artificial intelligence.

The specialist has expressed regrets about his contributions to the field. Hired by Google a decade ago to aid in the development of AI technology, he paved the way for current systems like ChatGPT.

According to the New York Times, Hinton believed Google had responsibly handled the artificial intelligence technology until last year. However, his understanding of the present situation changed when Microsoft incorporated a chatbot into its Bing search engine, and Google became concerned about the risk it posed to its search business.

Geoffrey Hinton. Photo credit: Eviatar Bach via Wikimedia, CC BY-SA 3.0

Hinton described certain dangers associated with AI chatbots as “quite scary.” He cautioned that these bots could surpass human intelligence and at the same time could be exploited for malicious purposes. The ability of chatbots to automatically generate large volumes of text could facilitate the creation of highly effective spambots, while also providing capabilities of manipulating public opinion.

“I’ve come to the conclusion that the kind of intelligence we’re developing is very different from the intelligence we have. So it’s as if you had 10,000 people and whenever one person learned something, everybody automatically knew it. And that’s how these chatbots can know so much more than any one person,” explained Hinton.

Hinton’s concerns align with those of other prominent figures in artificial intelligence research. Elon Musk, for example, recently expressed his disagreement with Google’s co-founder Larry Page, accusing him of not taking AI safety seriously enough. At that time, Musk emphasized the urgency of addressing AI safety before pursuing the development of “digital superintelligence.”

Valérie Pisano, CEO of Mila (the Quebec Artificial Intelligence Institute), criticized the dismissive approach to safety in AI systems. She said that such an attitude would not be acceptable in any other industry, while also underlining the need for responsible practices rather than relying on trial-and-error adjustments as AI interacts with society over time.

People already struggle to discern truth amidst the influx of AI-generated photos, videos, and text flooding the internet, says Hinton.

Furthermore, he also expressed concerns about artificial intelligence gradually replacing jobs traditionally performed by paralegals, personal assistants, and other occupations involving repetitive tasks, with the potential for broader job displacement in the future.

Artificial Intelligence Researcher Geoffrey Hinton: Brief Biography

Geoffrey Hinton is a prominent figure in the field of artificial intelligence (AI) and machine learning. He is widely regarded as one of the pioneers of neural networks and deep learning. Born on December 6, 1947, in the United Kingdom, Hinton is a computer scientist and cognitive psychologist.

In 2012, he gained widespread recognition for his work on deep learning when he co-authored a paper that demonstrated the effectiveness of deep neural networks in image recognition tasks. This breakthrough had a transformative impact on the field and laid the foundation for the deep learning revolution.

Throughout his career, Hinton has made numerous fundamental contributions to AI and neural networks, including the development of the backpropagation algorithm, which is a key technique used to train deep neural networks. His work has influenced various areas of machine learning, such as computer vision, natural language processing, and speech recognition.

Hinton has held academic positions at several institutions, including the University of Toronto, where he is an Emeritus Distinguished Professor. He has also been affiliated with Google for quite a long time.

Today, he remains an influential figure in the AI community and is recognized as one of the key architects of the modern AI landscape.

Written by Alius Noreika