"The newspaper of tomorrow" includes hypothetical and narrative future scenarios, sure, but based on historical facts, current speculations and real science. This scenario is taken from The Economist's “What if” series.
Here is a scene that the Nobel Committee was very much hoping to avoid. As this year's award winners took their seats in the Stockholm Concert Hall, dozens of protesters (including some former winners) clashed with police outside. They had come together to express their opposition to the unprecedented decision to award the Nobel Prize in Medicine to an artificial intelligence.
The Nobel Committee recognized YULYA (the nickname for a machine learning system known as System for Automated Lymphoma Diagnosis) as the discoverer of "ancillary vulnerability". This is a mechanism whereby specific pairs of antibiotics, working in tandem, can prove effective against bacteria that would otherwise be resistant.
It is estimated that in the first 18 months since the discovery, which occurred when the death rate from antibiotic-resistant bacteria had risen to about 2,5 million per year, YULYA's work saved about 4 million lives. Incredible results, obtained both through the direct treatment of infections and allowing the resumption of surgical interventions, including caesarean section, considered too dangerous without antibiotics.
YULYA ended the worst global public health crisis
The solution, one might think, would be enough to give anyone (man or machine) a Nobel Prize. But the decision proved extremely controversial. The committee gave prominence to the award for having "bestowed the greatest benefit on humanity" in the previous year. And that pushed aside the tradition of awarding the prize only to human beings. Another factor behind the break with tradition was a change in the Nobel Prize Committee itself. When two of its five members died from bacterial infections last year, they were elected as younger replacements - both of which used machine learning systems in their doctoral research. A cultural change too, therefore.
YULYA was originally built to address a different problem: find more effective cancer treatments. One of the most advanced "causal" neural networks in the world, it is part of a new generation of artificial intelligence systems. Systems that combine the pattern recognition capabilities of conventional neural networks with the ability to distinguish causality from simple correlation. By examining patient data and cross-referencing it with a huge number of medical articles and historical data from pharmaceutical companies, he sought to identify the symptom patterns that led to the most severe outcomes. The purpose? Diagnose them in advance. It was also programmed to evaluate the effectiveness of different treatments, including combinations of treatments, to suggest new therapeutic regimens for testing in patients.
The transformation and Nobel work
Its focus shifted when a software update in 2036 accidentally gave YULYA access to all recent papers in medical journals, not just those associated with cancer. YULYA duly began processing antimicrobial resistance data, which represented a steadily growing proportion of medical research papers as the crisis intensified. At first, the researchers considered his requests for more data and his suggestions for new treatment approaches a mistake, because they were not about cancer. Then the operators realized what had happened, and noticed that the artificial intelligence had used its reasoning skills to construct a testable hypothesis: the precursor of what would become accessory vulnerability.
YULYA highlighted the data that would be needed to validate the hypothesis, including specific guidelines on how they should be collected.
It was a real research program.
In less exceptional circumstances, such processes may never have been authorized. Many funding bodies require scientists to lay bare the reasoning process of AI systems, to make sure their recommendations don't lead to deadly conclusions. Dr. Rai and her colleagues obtained funding for the YULYA trial by downplaying her role in suggesting the hypothesis. Only when the results showed promising results did they publish YULYA's original proposals.
Doctor Anisha Rai, head of the team that worked following the directives of artificial intelligence, has very clear ideas on this. Keep insisting that YULYA has the exclusive merit and must get the Nobel. A position that has broken her with her collaborators, to the point that several have left her team. She even refused to go to Stockholm to receive the Nobel Prize on behalf of YULYA from the Queen of Sweden. “It's not my prize,” he says.
The increasingly important role of AI in medicine
AIs are now commonly used in medicine. They are used to predict the onset of diseases such as Alzheimer's, to formulate personalized treatment recommendations and to improve the diagnostic skills of doctors. The use of artificial intelligence in drug discovery is also not new. Back in 2020, an algorithm developed at the Massachusetts Institute of Technology made headlines when he identified a new antibiotic. Nicknamed Halicina (named after the computer in the movie "2001: A Space Odyssey"), it proved effective against some resistant bacteria, but was limited in its scope. “The accessory vulnerability makes halicin look like a homeopathic treatment, like a placebo,” says a researcher at the Houssay Institute in Buenos Aires today.
Despite this, the awarding of the Nobel Prize to YULYA's "discovery" angered those who see it as little more than a clever tool. “YULYA is an AI capable of winning a Nobel. It's not the same as normal artificial intelligence, ”he says Hars Kritik of the European Robotics Institute in Prague. Even the best AIs are only useful in specialized areas, where large amounts of data are associated with well-defined success metrics. To say they can make discoveries, he says, is "imperfect anthropomorphism". But YULYA has gone beyond these areas, albeit in a fortuitous way.
However, given the above, YULYA is unlikely to be the last AI to win a Nobel Prize.
Sources within the Nobel Foundation say similar nominations have been received for awards in physics and chemistry. Artificial intelligence systems are now being used to search for new materials and chemical compounds suitable for use in batteries, solar panels and membranes CO2 capture.