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Ingredients of intelligence: From classic debates to an engineering roadmap

Published online by Cambridge University Press:  10 November 2017

Brenden M. Lake
Affiliation:
Department of Psychology and Center for Data Science, New York University, New York, NY 10011. [email protected]://cims.nyu.edu/~brenden/
Tomer D. Ullman
Affiliation:
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139. [email protected]@mit.eduhttp://www.mit.edu/~tomeru/http://web.mit.edu/cocosci/josh.html The Center for Brains Minds and Machines, Cambridge, MA 02139
Joshua B. Tenenbaum
Affiliation:
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139. [email protected]@mit.eduhttp://www.mit.edu/~tomeru/http://web.mit.edu/cocosci/josh.html The Center for Brains Minds and Machines, Cambridge, MA 02139
Samuel J. Gershman
Affiliation:
The Center for Brains Minds and Machines, Cambridge, MA 02139 Department of Psychology and Center For Brain Science, Harvard University, Cambridge, MA 02138. [email protected]://gershmanlab.webfactional.com/index.html

Abstract

We were encouraged by the broad enthusiasm for building machines that learn and think in more human-like ways. Many commentators saw our set of key ingredients as helpful, but there was disagreement regarding the origin and structure of those ingredients. Our response covers three main dimensions of this disagreement: nature versus nurture, coherent theories versus theory fragments, and symbolic versus sub-symbolic representations. These dimensions align with classic debates in artificial intelligence and cognitive science, although, rather than embracing these debates, we emphasize ways of moving beyond them. Several commentators saw our set of key ingredients as incomplete and offered a wide range of additions. We agree that these additional ingredients are important in the long run and discuss prospects for incorporating them. Finally, we consider some of the ethical questions raised regarding the research program as a whole.

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Authors' Response
Copyright
Copyright © Cambridge University Press 2017 

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