Google's Nobel prize winners stir debate over AI research

The award this week of Nobel prizes in chemistry and physics to a small number of artificial intelligence pioneers affiliated with Google has stirred debate over the company's research dominance and how breakthroughs in computer science ought to be recognized.

Google has been at the forefront of AI research, but has been forced on the defensive as it tackles competitive pressure from Microsoft-backed OpenAI and mounting regulatory scrutiny from the U.S Department of Justice.

Google played a pivotal role in the development of modern AI through its research on the "transformer architecture" for artificial intelligence models. In 2017, Google researchers published the seminal paper "Attention is All You Need," which introduced the transformer architecture. This breakthrough allowed for more efficient processing of sequential data and became the foundation for many subsequent AI models.

The transformer's ability to handle long-range dependencies in data led to significant advancements in natural language processing and beyond. One notable application was DeepMind's AlphaFold, which leveraged transformer-based techniques to revolutionize protein structure prediction, demonstrating the far-reaching impact of Google's initial research.

On Wednesday, Demis Hassabis – co-founder of Google's AI unit DeepMind – and colleague John Jumper were awarded the Nobel prize in chemistry, alongside U.S. biochemist David Baker, for their work decoding the structures of microscopic proteins using AlphaFold.

Former Google researcher Geoffrey Hinton, meanwhile, won the Nobel prize for physics on Tuesday, alongside U.S. scientist John Hopfield, for earlier discoveries in machine learning that paved the way for the AI boom.

Professor Dame Wendy Hall, a computer scientist and advisor on AI to the United Nations, told Reuters that, while the recipients’ work deserved recognition, the lack of a Nobel prize for mathematics or computer science had distorted the outcome.

"The Nobel prize committee doesn't want to miss out on this AI stuff, so it's very creative of them to push Geoffrey through the physics route," she said. "I would argue both are dubious, but nonetheless worthy of a Nobel prize in terms of the science they’ve done. So how else are you going to reward them?"

Noah Giansiracusa, an associate maths professor at Bentley University and author of "How Algorithms Create and Prevent Fake News", also argued that Hinton’s win was questionable.

"What he did was phenomenal, but was it physics? I don't think so. Even if there's inspiration from physics, they're not developing a new theory in physics or solving a longstanding problem in physics."

The Nobel prize categories for achievements in medicine or physiology, physics, chemistry, literature and peace were laid down in the will of Swedish inventor Alfred Nobel, who died in 1895. The prize for economics is a later addition established with an endowment from the Swedish central bank in 1968.

Google dominates AI research

Regulators in the U.S. are currently circling Google for a potential break-up, which could force it to divest parts of its business, such as its Chrome browser and Android operating system, which some argue allow it to maintain an illegal monopoly in online search.

The profits derived from its leading position have allowed Google and other Big Tech companies to outpace traditional academia in publishing groundbreaking AI research.

Hinton himself has expressed some regrets about his life's work, quitting Google last year so that he could speak freely about the dangers of AI, and warning that computers could become smarter than people far sooner than previously expected.

Speaking at a press conference Tuesday, he said: "I wish I had a sort of simple recipe that if you do this, everything's going to be okay, but I don't, in particular with respect to the existential threat of these things getting out of control and taking over.”

When he quit Google in 2023 over his AI concerns, Hinton said the company itself acted very responsibly.

For some, this week’s Nobel prize wins underscore how hard it is becoming for traditional academia to compete. Giansiracusa told Reuters there was a need for greater public investment in research.

"So much of Big Tech is not oriented towards the next deep-learning breakthrough, but making money by pushing chatbots or putting ads all over the internet," he said. "There are pockets of innovation, but much of it is very unscientific."