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Précis of The creative mind: Myths and mechanisms

Published online by Cambridge University Press:  04 February 2010

Margaret A. Boden
Margaret A. Boden
Affiliation:
School of Cognitive and Computing Sciences, University of Sussex, Falmer, Brighton BN1 9QH, England Electronic mail: [email protected]
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Abstract

What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves (positively valued) novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect to the particular conceptual space concerned – could not have been generated before. (They are made possible by some transformation of the space.) The more clearly conceptual spaces can be defined, the better we can identify creative ideas. Defining conceptual spaces is done by musicologists, literary critics, and historians of art and science. Humanist studies, rich in intuitive subtleties, can be complemented by the comparative rigour of a computational approach. Computational modelling can help to define a space, and to show how it may be mapped, explored, and transformed. Impossibilist creativity can be thought of in “classical” Al terms, whereas connectionism illuminates improbabilist creativity. Most Al models of creativity can only explore spaces, not transform them, because they have no self-reflexive maps enabling them to change their own rules. A few, however, can do so. A scientific understanding of creativity does not destroy our wonder at it, nor does it make creative ideas predictable. Demystification does not imply dehumanization.

Keywords

artificial intelligenceassociationcomputer artcomputer musiccreativitydiscoveryinductionintuitionrepresentationstory-writingTuring testunpredictability
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 17 , Issue 3 , September 1994 , pp. 519 - 531
Copyright
Copyright © Cambridge University Press 1994

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