This week, the 2024 Nobel Prize in Physics was awarded to Geoffrey Hinton and John Hopfield, who developed the foundation to Machine Learning (ML) based on artificial neural networks. In addition, the Nobel Prize in chemistry was awarded to Demis Hassabis and John Jumper, who used Artificial Intelligence (AI) to develop a model that predicts proteins’ structure based on a scientific training set. This is the opening of a future in which scientific discoveries are accelerated by ML/AI. The two awards made me wonder about the long-term challenge posed by ML/AI to Nobel Prize traditions.
In a WORLD.MINDS forum led by the brilliant Rolf Dobelli today, I had asked a member of the prestigious Nobel Prize Committee, Heiner Linke, whether he can see a future in which a machine with superhuman intelligence will make scientific breakthroughs and be recognized by the Nobel Prize Committee? If humans read the output from an autonomous machine that worked out the solution to a major scientific puzzle, why would the Nobel Committee limit prize nominations only to human recipients? Heiner replied that the language of the Nobel Prize restricts the award to be given only to human recipients.
This is understandable given that AI was not imagined when the Nobel Prize was established by Alfred Nobel in 1901. Even today, it is reasonable for humans to insist on recognizing each other because human bodies are made of biodegradable flesh and blood. Intelligent being made of silicon chips are not members of the human species. This follows the rationale of offering medals in Olympic Games only to humans and not to faster cars or robots.
However, the prestige of the Nobel Prize will fade once it will be widely known, several decades from now, that machines actually dominate the progress of scientific progress. Once machines will outperform human scientists, the Nobel Prize will become a `management recognition award’, not rewarding the machine-based players which actually made the discoveries but rather the human managers who coordinated and harvested the fruits of that effort.
In a more futuristic scenario, one could balance the picture by adding AI systems as members of the Nobel Prize committee. By allowing representation for AI/ML systems, the recognition of those who are actually responsible for future scientific discoveries might be adequately valued. Of course, as with humans, the AI/ML accomplishments will need to be vetted for proper scientific practice, both concerning the data being studied and the reliability of the results based on their examination by independent groups. Another strategy is to have two prizes: one for humans and the other for AI/ML systems. This would echo the spirit of splitting of the Olympic Games to the two subcategories of men and women.
Whereas AI/ML may quickly dominate theoretical analysis of large data sets, the gathering of experimental evidence will likely be led by human observers for the foreseeable future. This means that humans will play an important role in acquiring the evidence that guides theories for decades to come. No theorist trained on classical physics predicted quantum mechanics before it was discovered experimentally a century ago.
We still do not fully understand the interpretation of quantum physics at a fundamental level, nor do we have a predictive theory that unifies the quantum world with the description of gravity as the curvature of spacetime. The partnership between humans and machines is needed to collect the data that will guide such efforts and inspire the next revolution in our understanding of the physical reality.
All in all, the next century of modern science is likely to look very different from its first century. Irrespective of who gets recognized by prizes, here’s hoping the partnership between humans and ML/AI will usher a new era of prosperity and peace on Earth.
Our terrestrial ML/AI might be inspired by extraterrestrial ML/AI that represents our scientific future. We could accelerate our own progress dramatically by discovering alien intelligence.
Avi Loeb is the head of the Galileo Project, founding director of Harvard University’s – Black Hole Initiative, director of the Institute for Theory and Computation at the Harvard-Smithsonian Center for Astrophysics, and the former chair of the astronomy department at Harvard University (2011-2020). He is a former member of the President’s Council of Advisors on Science and Technology and a former chair of the Board on Physics and Astronomy of the National Academies. He is the bestselling author of “Extraterrestrial: The First Sign of Intelligent Life Beyond Earth” and a co-author of the textbook “Life in the Cosmos”, both published in 2021. The paperback edition of his new book, titled “Interstellar”, was published in August 2024.