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The Importance of Being Educable: A New Theory of Human Uniqueness
In the age of AI, why our future depends on better understanding what makes us humanWe are at a crossroads in history. If we hope to share our planet successfully with each other and the AI systems we are creating, we must reflect on who we are, how we got here, and where we are heading. The Importance of Being Educable puts forward a provocative new exploration of the extraordinary facility of humans to absorb and apply knowledge. The remarkable “educability” of the human brain can be understood as an information processing ability. It sets our species apart, enables the civilization we have, and gives us the power and potential to set our planet on a steady course. Yet it comes hand in hand with an insidious weakness. While we can readily absorb entire systems of thought about worlds of experience beyond our own, we struggle to judge correctly what information we should trust.In this visionary book, Leslie Valiant argues that understanding the nature of our own educability is crucial to safeguarding our future. After breaking down how we process information to learn and apply knowledge, and drawing comparisons with other animals and AI systems, he explains why education should be humankind’s central preoccupation.Will the unique capability that has been so foundational to our achievements and civilization continue to drive our progress, or will we fall victim to our vulnerabilities? If we want to play to our species’ great strength and protect our collective future, we must better understand and prioritize the vital importance of being educable. This book provides a road map.
262 pages, Kindle Edition
Published April 16, 2024
40 people are currently reading
542 people want to read
About the author
Leslie Valiant
9 books15 followersLeslie Valiant FRS is a British computer scientist and computational theorist. He is currently the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University, and was educated at King's College, Cambridge, Imperial College London, and University of Warwick where he received a PhD in computer science in 1974.
Valiant is world-renowned for his work in theoretical computer science. Among his many contributions to complexity theory, he introduced the notion of #P-completeness to explain why enumeration and reliability problems are intractable. He also introduced the "probably approximately correct" (PAC) model of machine learning that has helped the field of computational learning theory grow, and the concept of holographic algorithms. His earlier work in automata theory includes an algorithm for context-free parsing, which is (as of 2010) still the asymptotically fastest known. He also works in computational neuroscience focusing on understanding memory and learning.
Valiant's 2013 book is Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (Basic Books, ISBN 9780465032716). In it he argues, among other things, that evolutionary biology does not explain the rate at which evolution occurs, writing, for example, "The evidence for Darwin's general schema for evolution being essentially correct is convincing to the great majority of biologists. This author has been to enough natural history museums to be convinced himself. All this, however, does not mean the current theory of evolution is adequately explanatory. At present the theory of evolution can offer no account of the rate at which evolution progresses to develop complex mechanisms or to maintain them in changing environments."
Valiant is world-renowned for his work in theoretical computer science. Among his many contributions to complexity theory, he introduced the notion of #P-completeness to explain why enumeration and reliability problems are intractable. He also introduced the "probably approximately correct" (PAC) model of machine learning that has helped the field of computational learning theory grow, and the concept of holographic algorithms. His earlier work in automata theory includes an algorithm for context-free parsing, which is (as of 2010) still the asymptotically fastest known. He also works in computational neuroscience focusing on understanding memory and learning.
Valiant's 2013 book is Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (Basic Books, ISBN 9780465032716). In it he argues, among other things, that evolutionary biology does not explain the rate at which evolution occurs, writing, for example, "The evidence for Darwin's general schema for evolution being essentially correct is convincing to the great majority of biologists. This author has been to enough natural history museums to be convinced himself. All this, however, does not mean the current theory of evolution is adequately explanatory. At present the theory of evolution can offer no account of the rate at which evolution progresses to develop complex mechanisms or to maintain them in changing environments."
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Displaying 1 - 3 of 3 reviews
June 4, 2024
At certain moments, this was the book that I had been looking for. It seeks to create a computational framework around learning, one that can be generalized in much the same way that Turing generalized the notion of computation. As someone who has walked the tight rope between neuroscience and computer science, I found this endeavor enlightening and convincing. There were chapters that felt perfect.
Unfortunately, there were also chapters that I found both paradoxically too vague and too precise to be of much use (the chapters where Valiant explicitly lays out his computational framework). Perhaps this is because I am not an academic computer scientist, or maybe I just need to revisit it again with a clearer mind.
Unfortunately, there were also chapters that I found both paradoxically too vague and too precise to be of much use (the chapters where Valiant explicitly lays out his computational framework). Perhaps this is because I am not an academic computer scientist, or maybe I just need to revisit it again with a clearer mind.
September 19, 2025
Solid read. A lot that was enjoyable and some that was was belabored.
March 31, 2025
Full review and summary.
I always thought intelligence made humans unique and was enough to build civilization, but this book changed my perspective. Leslie Valiant argues that what truly matters is our ability to learn, adapt, and refine our thinking, which is the definition of educabilty.
I also found the idea of Robust Logic especially interesting. It explains how we handle uncertainty without needing everything to be perfectly consistent. It also made me reflect on how people react to new information, like during the pandemic when changing health guidelines led some to reject science instead of seeing it as part of learning.
The section on fearing on AI singularity was also worth reading, offering a more grounded perspective rather than fear-driven predictions.
Some parts were a bit too technical, but Valiant kept giving interesting reads that answered many lingering questions on my mind, so I kept going despite the challenge. This book gave me a lot to think about.
I always thought intelligence made humans unique and was enough to build civilization, but this book changed my perspective. Leslie Valiant argues that what truly matters is our ability to learn, adapt, and refine our thinking, which is the definition of educabilty.
I also found the idea of Robust Logic especially interesting. It explains how we handle uncertainty without needing everything to be perfectly consistent. It also made me reflect on how people react to new information, like during the pandemic when changing health guidelines led some to reject science instead of seeing it as part of learning.
The section on fearing on AI singularity was also worth reading, offering a more grounded perspective rather than fear-driven predictions.
Some parts were a bit too technical, but Valiant kept giving interesting reads that answered many lingering questions on my mind, so I kept going despite the challenge. This book gave me a lot to think about.
Displaying 1 - 3 of 3 reviews