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Causal generative models are just a start

Published online by Cambridge University Press:  10 November 2017

Ernest Davis  and
Gary Marcus
Ernest Davis
Affiliation:
Department of Computer Science, New York University, New York, NY 10012. [email protected]://www.cs.nyu.edu/faculty/davise
Gary Marcus
Affiliation:
Uber AI Labs, San Francisco, CA 94103 Department of Psychology, New York University, New York, NY 10012. [email protected]://garymarcus.com/
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Abstract

Human reasoning is richer than Lake et al. acknowledge, and the emphasis on theories of how images and scenes are synthesized is misleading. For example, the world knowledge used in vision presumably involves a combination of geometric, physical, and other knowledge, rather than just a causal theory of how the image was produced. In physical reasoning, a model can be a set of constraints rather than a physics engine. In intuitive psychology, many inferences proceed without detailed causal generative models. How humans reliably perform such inferences, often in the face of radically incomplete information, remains a mystery.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e262
Copyright
Copyright © Cambridge University Press 2017 

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