Inventive Minds: Marvin Minsky on Education

MIT Press
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Six essays by artificial intelligence pioneer Marvin Minsky on how education can foster inventiveness, paired with commentary by Minsky's former colleagues and students.

Marvin Minsky was a pioneering researcher in artificial intelligence whose work led to both theoretical and practical advances. His work was motivated not only by technological advancement but also by the desire to understand the workings of our own minds. Minsky's insights about the mind provide fresh perspectives on education and how children learn. This book collects for the first time six essays by Minsky on children, learning, and the potential of computers in school to enrich children's development. In these essays Minsky discusses the shortcomings of conventional education (particularly in mathematics) and considers alternative approaches; reflects on the role of mentors; describes higher-level strategies for thinking across domains; and suggests projects for children to pursue. Each essay is paired with commentary by one of Minsky's former colleagues or students, which identifies Minsky's key ideas and connects his writings to current research. Minsky once observed that in traditional teaching, “instead of promoting inventiveness, we focus on preventing mistakes.” These essays offer Minsky's unique insights into how education can foster inventiveness.

Commentary by Hal Abelson, Walter Bender, Alan Kay, Margaret Minsky, Brian Silverman, Gary Stager, Mike Travers, Patrick Henry Winston

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About the author

Marvin Minsky (1927–2016) was Toshiba Professor of Media Arts and Sciences and Donner Professor of Electrical Engineering and Computer Science at MIT. He was a cofounder of the MIT Media Lab and a consultant for the One Laptop Per Child project.

Cynthia Solomon worked with Marvin Minsky at the MIT AI Lab and at the Atari Cambridge Research Lab. She is the author of Computer Environments for Children (MIT Press).

Xiao Xiao worked with Marvin Minsky at the MIT Media Lab. She is a computer scientist, artist, pianist, thereminist, and Research Affiliate with the Tangible Media Group at the MIT Media Lab.

Hal Abelson is Class of 1922 Professor of Computer Science and Engineering at Massachusetts Institute of Technology and a fellow of the IEEE. He is a founding director of Creative Commons, Public Knowledge, and theFree Software Foundation. Additionally, he serves as co-chair for the MIT Council on Educational Technology.

Patrick H. Winston is Professor of Electrical Engineering and Computer Science and Director of the Artificial Intelligence Laboratory at MIT.

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Additional Information

MIT Press
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Published on
Mar 29, 2019
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Education / General
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In-depth guidance for using and developing effective questions.
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Scripts of teacher questions and student responses.
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Support material for teachers, including evaluation checklists and forms.

Esther Fusco is an associate professor and Chair of the Department of Teaching, Literacy and Leadership at Hofstra University, Hempstead, New York.

The first systematic study of parallelism in computation by two pioneers in the field.

Reissue of the 1988 Expanded Edition with a new foreword by Léon Bottou

In 1969, ten years after the discovery of the perceptron—which showed that a machine could be taught to perform certain tasks using examples—Marvin Minsky and Seymour Papert published Perceptrons, their analysis of the computational capabilities of perceptrons for specific tasks. As Léon Bottou writes in his foreword to this edition, “Their rigorous work and brilliant technique does not make the perceptron look very good.” Perhaps as a result, research turned away from the perceptron. Then the pendulum swung back, and machine learning became the fastest-growing field in computer science. Minsky and Papert's insistence on its theoretical foundations is newly relevant.

Perceptrons—the first systematic study of parallelism in computation—marked a historic turn in artificial intelligence, returning to the idea that intelligence might emerge from the activity of networks of neuron-like entities. Minsky and Papert provided mathematical analysis that showed the limitations of a class of computing machines that could be considered as models of the brain. Minsky and Papert added a new chapter in 1987 in which they discuss the state of parallel computers, and note a central theoretical challenge: reaching a deeper understanding of how “objects” or “agents” with individuality can emerge in a network. Progress in this area would link connectionism with what the authors have called “society theories of mind.”

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