By Claus D. Volko
When the Nobel Prizes were announced this year (2024), many people were initially shocked at seeing that the decision had been made to give the Nobel Prize in Physics to two researchers in Artificial Intelligence (AI), one of whom did not even have a physics degree. But the Nobel Prize in Chemistry that was announced a day later showed why that decision had been made: after all, AI methods had been employed by the winners of that prize to conduct their research about the structure of proteins. So it was in some way justified to give two of the researchers who had laid the foundations for modern AI recognition.
The big question is: Will we see more Nobel Laureates who worked with AI? Will it even perhaps soon be ordinary that Nobel Prize winning scientists have made their discoveries using AI? Is it even possible that every Nobel Prize will be given to people employing AI and maybe the Nobel Prize will be given to the AI systems themselves instead of human beings?
Is it the dawn of a new era, the era of AI in science?
Back in 2005 Ray Kurzweil published a seminal book, called “The Singularity Is Near”. Now, almost 20 years later, the sequel to this book has been released: “The Singularity Is Nearer”. The sequel summarizes the tremendous progress AI has made in the past decades. However, the singularity itself has not been reached yet, and it is a hot question in public debate whether we will reach it and, if so, when. The singularity would be reached once AI surpassed human-level intelligence because in that case, AI would be able to refine itself and become more and more powerful, and make many discoveries within a short time which would have taken man many years.
Even if the singularity has not been reached yet, AI tools have become very powerful utilities for scientific research. AlphaFold 3 has dramatically improved protein structure discovery, with an accuracy of about 70%. Its predecessor has beaten all of its competitors in the CASP 2020 challenge. The company DeepMind that created AlphaFold, a subsidiary of Google, has made a great achievement and only deserves to be honored with a Nobel Prize.
There are many applications of protein structure discovery and the reverse process, the prediction of the amino acid sequence from a given structure. In the latter case, for instance novel therapeutics could be designed that work at specific targets in the human cells and have the desired effects. As a matter of fact, the technology that has been awarded the Nobel Prize this year will lead to yet more discoveries that will be worthy Nobel Prize winners.
Now the question is: Will human intelligence still be needed for scientific progress?
I am not sure. Maybe the singularity will come indeed and then human brainpower will be obsolete, maybe except for conducting the experiments the AI systems devise to test their hypotheses. But there is also a chance that the singularity will in fact never, or at least not too soon, materialize and in that case, we will still need highly intelligent academics to work in research.