The 2025 Nobel Prizes in Economics and Physics, awarded for research on institutions and machine learning, respectively, highlight the critical role of information and data in shaping economic and scientific advancements.”
The Nobel Prize in Economics (officially the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel) and the Nobel Prize in Physics are distinct awards, and their connection to “information” is obvious.
In 2025, the Nobel Prize in Economics was awarded to Daron Acemoglu, Simon Johnson, and James A. Robinson for their work on institutions and economic development, which indirectly relates to information through the role of governance and data in shaping economic outcomes. For instance, their research touches on how information about institutional frameworks influences prosperity, but it’s not directly about information theory or data science.
The Nobel Prize in Physics in 2025 went to John J. Hopfield and Geoffrey E. Hinton for foundational discoveries in machine learning, specifically neural networks, which are directly tied to information processing and artificial intelligence. Their work revolutionized how data is analyzed and utilized in computational models, highlighting the critical role of information in modern science.
Quantum physics, as a field, often intersects with information theory, particularly in areas like quantum computing and quantum information science, which deal with how information is stored, processed, and transmitted at the quantum level. However, the 2025 Physics Prize focused on machine learning, not quantum physics per se, though neural networks have applications in quantum research.
Saying these prizes are “related indirectly somewhat to the field of information” is fair . The Economics prize has a tangential link through institutional data and decision-making, while the Physics prize is more directly tied to information via machine learning. The statement correctly underscores the growing importance of data and information in today’s world, as both fields leverage vast datasets and computational tools to advance knowledge.
