Polymath, deriving its origin from the Greek word polymathēs ( meaning “having learned much”), is often used to refer to an individual who has knowledge that spans diverse subjects. Perhaps the most celebrated polymath is Leonardo da Vinci, an Italian icon of the High Renaissance period, whose expertise spanned from art to science. From pioneering paintings like Mona Lisa and The Last Supper to studying the human proportions through the Vitruvian Man, there weren’t many areas without da Vinci’s mystical touch in it. He even produced a design for a flying machine with a sophisticated flight control system but wasn’t successfully created. However, it’s not just the breadth nor the depth of knowledge that led to his contributions. It’s rather the ability to find relationships and patterns between versatile knowledge bases and the insights from it that helped Leonardo to produce his remarkable body of work. Therefore, it’s better to tweak the definition of Polymath as follows:
The Hungarian Mathematician John von Neumann is often referred to as the Last Great Polymath. This is partly due to his significant contributions to mathematics, physics, computer science, and economics. If there was a person who could win Fields Medal, Turing Award, and Nobel Prize: it was him. Unfortunately, he couldn’t win any of these due to various factors. The Turing award was first given out in 1966 – 9 years after his death. Similarly, the Nobel Prize in Economics which he would have been more than eligible for was given out in 1969 – 12 years after his death. And as far as the Fields Medal goes, his major contributions in mathematics came after 40, the age limit for Fields Medalists. It’s quite clear that Von Neumann was a genius like no other. Hans Bethe, the Nobel-winning physicist, joking remarked that Von Neumann’s brain indicated a brain superior to that of mankind. The reason why is called the Last Great Polymath is simply that there haven’t been any notable people who had neither the breadth nor the depth of contributions in multiple fields.
This is apparent in the current academic climate. People are leaning towards specializing in one narrow region in their respective fields. Even people with broad knowledge inside a specific field, say mathematics, are extremely rare. One might wonder whether this might be related to the lack of significant breakthroughs in science. The last great breakthrough in science is probably the foundation of Artificial Intelligence, approximately 20 years ago. Before that, it was the rise of information theory, around 75 years ago. However, this is where things get interesting. Before the 1950s, there was a stimulating rush of contributions to science, especially in physics, chemistry, and mathematics. It saw the rise of quantum mechanics, the inception of relativity, and the birth of modern mathematics. We are in a, for the lack of a better word, boring predicament as far as academia is concerned. One could make a good argument that this lack of breakthrough is due to the ever-increasing complexity of the natural and social sciences. All though that is a valid point, I don’t think humans have such a limited ceiling. With the increase in collective knowledge, it should only increase our ability to contribute to more complex areas of knowledge.
One can also notice a trend in such polymathy in exceptional scientists. For instance, it is found that Nobel laureates are more than 25 times more likely to perform in performing arts respect to the average scientist as mentioned in Range: Why Generalists Triumph in a Specialized World. There are many examples in history of this phenomenon – Planck with the piano, Einstein with the violin, and Feynman with his comedic bongos.
Furthermore, there is also the practicality of pursuing multiple interests. In his famous book, Deep Work, the computer scientists Cal Newport introduces the concept of the same name
He notes that even the most productive and determined person can only engage in 3-4 hours of deep work. This makes sense. It is quite hard to focus on the same thing for a long period of time while engaging in it completely. However, the emphasis is on the concept of the same. A way to enhance this inherent limitation is to spread the work throughout different fields. The reason why we get saturated is because of the lack of novelty that arises from working on a specific topic.
It is becoming eminently clear that there is a great need for polymaths in recent times. The stagnation of physics in the unification of quantum mechanics and relativity, and the saturation in artificial intelligence, and theoretical computer science all point to this. It almost seems like the end of science, and the search for knowledge – not because we don’t have questions but rather because we are incapable of answering them. But slowly but surely the winds are turning. It may be my hopeful optimism, but there is a new renaissance around the corner. The age of new polymaths. It may not be much time before we see the next da Vinci, the next Leibniz, or the next Neumann.