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Computing the creativeness of amusing advertisements: A Bayesian model of Burma-Shave's muse

Published online by Cambridge University Press:  02 December 2014

Kevin Burns
Kevin Burns*
Affiliation:
MITRE Corporation, Bedford, Massachusetts, USA
*
Reprint requests to: Kevin Burns, MITRE Corporation, 202 Burlington Road, Bedford, MA 01730-1420, USA. E-mail: kburns@mitre.org
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Abstract

How do humans judge the creativeness of an artwork or other artifact? This article suggests that such judgments are based on the pleasures of an aesthetic experience, which can be modeled as a mathematical product of psychological arousal and appraisal. The arousal stems from surprise, and is computed as a marginal entropy using information theory. The appraisal assigns meaning, by which the surprise is resolved, and is computed as a posterior probability using Bayesian theory. This model is tested by obtaining human ratings of surprise, meaning, and creativeness for artifacts in a domain of advertising design. The empirical results show that humans do judge creativeness as a product of surprise and meaning, consistent with the computational model of arousal and appraisal. Implications of the model are discussed with respect to advancing artificial intelligence in the arts as well as improving the computational evaluation of creativity in engineering and design.

Keywords

AestheticsBayesianCreativityInformationSemantics
Type
Regular Articles
Information
AI EDAM , Volume 29 , Issue 1 , February 2015 , pp. 109 - 128
Copyright
Copyright © Cambridge University Press 2014 

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