In the age of AI, why our future depends on better understanding what makes us human

We are at a crossroads in history. If we hope to share our planet successfully with one another 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.

Author: Leslie Valiant
Binding Type: Hardcover
Publisher: Princeton University Press
Published: 04/16/2024
Pages: 272
Weight: 1.15lbs
Size: 8.58h x 5.67w x 1.18d
ISBN: 9780691230566


Review Citation(s):
Library Journal 03/01/2024 pg. 119

About the Author
Leslie Valiant is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University. Recipient of the Turing Award and the Nevanlinna Prize for his foundational contributions to machine learning and computer science, he is the author of Probably Approximately Correct and Circuits of the Mind.