Today: Feb 12, 2025

Nobel Prize controversy: How AI breakthroughs are challenging traditional science awards

4 months ago

Every October, the Nobel Prize committees in Sweden and Norway announce the laureates for six prestigious awards, celebrating exceptional achievements in science, literature, economics, and peace. 

This year’s prizes have highlighted groundbreaking research, particularly in the field of artificial intelligence (AI), sparking debates about how AI fits into conventional Nobel Prize categories.

The categories include physiology or medicine, physics, chemistry, literature, peace, and economic sciences. This year, 286 candidates—197 individuals and 89 organizations—are in the running for the Peace Prize.

The physics award went to John J. Hopfield and Geoffrey E. Hinton for advancements that helped shape AI, specifically through machine learning models mimicking brain functions.

The chemistry prize honored Demis Hassabis and John Jumper of Google DeepMind, and David Baker, for using AI to predict and design millions of protein structures, a major scientific breakthrough.

Nobel Prize controversy

Critics, including experts like Professor Dame Wendy Hall and Noah Giansiracusa, question the Nobel Committee’s decision to award AI researchers within traditional categories like Physics and Chemistry.

They argue that the lack of a Nobel Prize for mathematics or computer science has forced the Committee to stretch definitions to accommodate AI contributions, creating a mismatch between the awarded field and the research conducted.

Concerns about diversity in Nobel Prize winners persist. The Nobel Committee continues to overlook underrepresented groups, particularly women and Black scientists, prompting calls for reforms in how scientific recognition is awarded.

Professor Dame Wendy Hall, the AI advisor to the United Nations speaking to Reuters, criticized the Nobel Committee for stretching categories to accommodate AI research.

She believes that the lack of a Nobel Prize for fields like mathematics or computer science distorts how AI contributions are recognized. Despite this, she acknowledges that the recipients deserve recognition for their scientific work.

Hall emphasizes the limitations of the Nobel Prize system in recognizing emerging fields like AI and calls for a more appropriate framework for acknowledging advancements in computer science and technology.

Does the Nobel prize overlook diversity in science?

Science Writer Alexandra Thompson from the New Scientist  brings attention to the issue of diversity in Nobel Prize awards, calling for changes to ensure that a wider array of contributors is celebrated, especially from underrepresented groups.

Thompson critiques the Nobel Committee’s historical tendency to overlook women and Black scientists, pointing out the lack of diversity among this year’s laureates.

She uses Rosalind Lee’s case, where her significant contributions to prize-winning research were unrecognized, as an example of this broader problem.

Nello Cristianini, Professor of AI from the University of Bath points out that AI tools are becoming so central to research that it may become difficult to distinguish human contributions from machine-generated insights. He also raises the possibility that AI tools themselves might one day be recognized with prestigious awards like the Nobel Prize.

The attribution of credit between human scientists and their AI tools has become a point of contention, raising broader questions about the future of scientific discovery.

Some experts suggest that as AI becomes more integral to research, traditional Nobel Prize categories may need to evolve, or even introduce new categories to recognize contributions from AI-driven discoveries.

Noah Giansiracusa (Associate Professor of Mathematics, Bentley University), highlights the growing disparity between Big Tech’s dominance in AI research and the more limited resources available to traditional academic institutions.

Giansiracusa stresses the need for greater public investment in research to counterbalance the influence of profit-driven companies like Google and to ensure that scientific breakthroughs remain rooted in academic rigor rather than corporate interests.

Blurring lines: Should AI achievements be recognized in physics?

Giansiracusa challenges the classification of Hinton’s work as physics, arguing that while it is innovative and influential, it does not fit the traditional definitions of physics.

“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.” Giansiracusa told Reuters

Dr. Geoffrey Hinton, a 75-year-old British-born academic, has dedicated his career to advancing artificial intelligence (AI) based on his personal convictions.

His journey began in 1972 as a graduate student at the University of Edinburgh, where he embraced the concept of neural networks—a mathematical system that learns by analyzing data. At the time, the idea had little support in the scientific community, but it became the foundation of his life’s work.

In the 1980s, while a professor at Carnegie Mellon University, Hinton left the U.S. for Canada, citing his reluctance to accept funding from the Pentagon, which was a major source of AI research funding in the U.S. Hinton has long opposed the military use of AI, particularly what he refers to as “robot soldiers.”

His pioneering work culminated in 2012, when he and his students, Ilya Sutskever and Alex Krishevsky, built a neural network capable of analyzing thousands of photos and teaching itself to identify objects like flowers, dogs, and cars—an achievement that revolutionized the field.

The bottom line

The evolving nature of scientific contributions and the role of artificial intelligence in traditional fields like physics and chemistry prove an increasing and essential need to address the concerns surrounding the classification of such achievements.

According to experts, to maintain the credibility and relevance of the Nobel Prize, a pathway forward could involve the establishment of new categories that specifically recognize innovations in AI and technology.

Commentators note the need for diversification in the nominations and award recipients is paramount.  Ensuring that voices from various backgrounds—including women, minorities, and underrepresented groups—are recognized will enrich the scientific community and foster a more inclusive environment.

By adapting to the changing landscape of research and innovation while promoting diversity, the Nobel Prize can uphold its esteemed legacy and continue to inspire future generations of scientists and thinkers.

Fabrice Iranzi

Journalist and Project Leader at LionHerald, strong passion in tech and new ideas, serving Digital Company Builders in UK and beyond
E-mail: iranzi@lionherald.com

Leave a Reply

Your email address will not be published.