Contemporary Polymaths – Who is Michael Polanyi?
We were recently sent an article … ‘Michael Polanyi: Unknown and Untapped’ (link below) which hit all the Polymath Mind high notes. It describes Polanyi as a “polymathic genius” and a “brilliant amateur” raised in an interdisciplinary, environment. It further describes him as someone who never hesitated to cross disciplinary boundaries. That really was enough to pique our interest and put Michael Polanyi forward for our Polymath ‘Hall of Fame’.
You’ll find Michael Polanyi in chemistry textbooks, in essays on economics, in management research, in philosophy of science, in debates about expertise, and — if you’re working at the messy intersection of humans and AI — you’ll feel echoes of him there too.
Polanyi was born in Budapest in 1891 (and died in Northampton in 1976). His mother, Cecília Polányi, had established a salon for Budapest’s intellectuals to discuss the issues of the day, which probably shaped Michael’s inter-disciplinary approach to research. He graduated from a teacher-training college in 1908, before going on to study medicine at the University of Budapest. He was then given a scholarship to study chemistry in Germany. During WW1 he served as a medical officer in the Austro-Hungarian army and wrote his PhD thesis during a period of sick leave in 1916. Polanyi emigrated to Karlsruhe in Germany and was invited by Fritz Haber to join the Kaiser Wilhelm Institute in Berlin. With the rise of the Nazi’s in 1933 Polanyi accepted a chair in physical chemistry at the University of Manchester and was elected to membership of the Manchester Literary and Philosophical Society in 1934. Polanyi was among the 2,300 names of prominent persons listed on the Nazis’ Special Search List, people who were to be arrested on the invasion of Great Britain and turned over to the Gestapo. After the war and because of his growing interest in the social sciences, Manchester University created a new chair in Social Science for him. In 1944 Polanyi was elected a member of the Royal Society, and on his retirement from the University of Manchester in 1958 he was elected a senior research fellow at Merton College, Oxford. In 1962 he was elected a foreign honorary member of the American Academy of Arts and Sciences.
Polanyi wasn’t just clever across multiple fields. He genuinely shaped them. And it’s this combination — depth, breadth, and the ability to integrate — that gives him a special place in any discussion of polymathy. But Polanyi also gives us something else: a set of ideas about how knowledge really works that feel uncannily relevant to the world we’re building now.
“The process of philosophic and scientific enlightenment has shaken the stability of beliefs held explicitly as articles of faith.” Michael Polanyi
Polanyi wasn’t someone who set out to be a multi-hyphenate intellectual. If anything, his life looks like a series of pivots driven by curiosity and circumstance — which is, in its own way, the essence of polymathic growth.
Polanyi began life firmly in the world of physical chemistry. He published foundational work on reaction kinetics, adsorption, and the behavior of molecules. This wasn’t dabbling. He earned a Fellowship of the Royal Society — one of the highest honors in British science. Behind the technical work, though, something else was brewing: a deep interest in how scientists actually think and discover. Polanyi noticed that scientific breakthroughs didn’t arise from purely logical, step-by-step reasoning. They came from intuition, hunches, and a kind of trained perception that scientists themselves often struggled to articulate. In other words: they came from tacit knowledge. But that revelation would take a while to mature.
The rise of totalitarian regimes in the 1930s pushed Polanyi into debates about planning, freedom, and the structure of economic life. His contributions in this period influenced early complexity thinking and challenged the idea that economic systems could be fully centralized or engineered from above. Here again, his chemistry background fed into his economics: he saw societies as complex, interdependent systems in which order emerged from the bottom up. Not designed. Not controlled, but emergent.
It’s striking how often polymaths see the same underlying patterns in totally different domains.
In mid-career, Polanyi finally turned toward the question that had haunted him since his laboratory days: how do humans truly know things? This led to his two most famous ideas:
Tacit knowledge – “we know more than we can tell”
Personal knowledge – all knowing involves personal judgment, commitment, and embodied engagement
“I shall reconsider human knowledge by starting from the fact that we can know more than we can tell.” Michael Polanyi
Polanyi argued that knowledge is not located in textbooks or models or data. It sits inside people — in their practiced capabilities, their perception, their attunement to context, their intuition. Expertise is something lived, not just learned. This makes him one of the earliest thinkers to place human cognition, not information, at the center of real-world decision-making. And it’s what makes him so relevant right now. Polanyi wasn’t trying to be poetic when he said “we know more than we can tell.” He meant it literally. He meant that:
We recognize a friend’s face instantly, but struggle to describe the features.
A surgeon “feels” when something is wrong before she can articulate why.
A strategist senses a weak assumption before they can map it out in a slide.
A parent spots danger in a child’s expression long before a rulebook would.
This tacit layer is where most of expertise lives.
“While tacit knowledge can be possessed by itself, explicit knowledge must rely on being tacitly understood and applied. Hence all knowledge is either tacit or rooted in tacit knowledge. A wholly explicit knowledge is unthinkable.” Michael Polanyi
For Polanyi, tacit knowledge isn’t a second-class citizen — it’s foundational. It’s the soil from which explicit knowledge grows. Skills, perceptions, intuitions, and subtle judgments form the bulk of what makes someone an expert. Now think about the AI-shaped workplace. We are automating the explicit layer — the bit that can be written down, formalized, and modelled. But the tacit layer remains stubbornly human. It’s embodied, contextual, and relational. It’s about pattern-recognition that isn’t always explainable. Polanyi helps us name this. And he helps us see why the future of work is not “AI replaces humans,” but “AI transforms the value of human tacit capability.”
Polanyi argued that knowing is participatory. A scientist does not approach evidence as a machine feeding facts into a logic engine. They bring training; values; personal purpose; a sense of what matters and lived experience. This “personal coefficient” doesn’t undermine objectivity. It makes objectivity possible. Without commitment, there is no discovery. Again, this is extremely relevant today.
The whole debate about “AI hallucinations” versus “AI creativity” misses Polanyi’s point. You cannot have knowledge without judgment. And judgment is, by definition, personal. The risk is not that AI makes mistakes. The risk is that humans stop using their personal judgment because the machine provides an answer too quickly. Polanyi would call that an epistemic disaster.
Another of Polanyi’s contributions is the idea that knowledge is socially distributed. No one individual can master everything; what matters is the network of overlapping intelligences — a collective apprenticeship. This anticipates modern ideas of collective intelligence, interdisciplinary work, organizational learning and communities of practice.
So, What Can the Rest of Us Learn? (Polanyi for non-academics)
You don’t need a professorship or a career in three disciplines to learn from Polanyi. In fact, he’s arguably at his most useful when applied to the everyday reality of knowledge work.
1. Treat intuition as a skill, not a flaw
Polanyi’s central idea is that intuition is not magically unreliable — it’s distilled experience. Modern workplaces often privilege the rational, the explicit, the documented. But genuine insight usually arrives before we can express it. It begins as a feeling. So, don’t apologize for intuition. Test it. When something “feels off,” pause and ask: what is my tacit knowledge trying to tell me? In strategy work, start with the hunch and work backward to structure.
In the AI era, this becomes even more important. AI gives you the explicit answer. Your tacit layer tells you whether it’s any good.
2. Build your expertise through embodied practice
Polanyi believed you learn with your whole body — not just your brain. That means practicing the craft, observing closely, reflect often, engage emotionally and cultivate attention. A person who spends time “doing the thing” will always outrun someone who only reads about it. If you want to develop genuine expertise … then do more. Write, analyze, coach, reflect etc. AI tools accelerate learning, but they don’t replace embodied experience. You still have to live the knowledge.
3. Surround yourself with a community of judgment
Polanyi’s distributed knowledge concept is a reminder: we grow through others. Build a small circle of people who challenge how you think. Share ideas early, even when they’re messy and engage across disciplines — the chemist became an economist because he stepped into a new conversation. Don’t let expertise isolate you
Polymathy isn’t about mastering everything. It’s about moving through multiple conversations.
4. Protect the tacit layer in your team
If you lead people, you can apply Polanyi directly. Create environments where tacit knowing can surface. Encourage storytelling ask people to explain how they noticed something. Value apprenticeship … shadowing, pairing, demoing and give space for reflection, not just action. Don’t try to standardize everything; some things need craft
The worst mistake a leader can make in the AI era is treating human judgment as a noisy variable. It’s actually your greatest strategic advantage.
Polanyi offers one of the clearest lenses for understanding the human–AI workplace. Tasks that can be documented, codified, or formalized migrate to machines. Tasks requiring perception, context, abstraction, judgment, and ethical reasoning remain human — and become more valuable.
This sets up a simple equation … As AI grows, tacit knowledge becomes the center of expertise. Polanyi helps us articulate that shift. He gives us the language for a future in which the most valuable professionals are sense-makers; intuition is recognized as a cognitive asset; knowledge is increasingly social and collective; expertise is lived, not automated and leaders design environments, not control systems
In many ways, Polanyi gives us the philosophical foundation for the polymathic workplace we argue for in The Polymath Mind: a place where value comes from integration, perception, synthesis, and judgment — not from producing more explicit information.
https://comment.org/michael-polanyi-unknown-and-untapped/