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for their value. The technique of brainstorming involves the idea of holding back
value judgement, so that generative thought processes can operate more freely in
the individual, thus shifting the process of value judgement required for adaptive
creativity to the collective level.
Generatively created patterns or behaviours can thus be exported to social sys-
tems through a process of “creating value”. The capacity to create value may itself
be an adaptive skill, or a matter of social context or luck: a more influential indi-
vidual might have more freedom to act generatively than someone trying to fit in; a
maternal ancestor might have experienced reproductive success for distinct genetic
reasons, which carries the success of their otherwise insignificant cultural behaviour
through vertical cultural transmission. Value creation does not necessarily mean
“adding value” (as in making the world a better place), but “manipulating value”:
shifting the social conditions within which other individuals must act. A challenge
for arts-based computational creativity is to understand whether “adding value” is at
all meaningful: can we make better art through technology? To assume so without
evidence would justifiably be viewed as complacency.
Alternative social aspects of the arts such as identity cast into doubt the cen-
trality to arts-based computational creativity of the capacity to evaluate, which is
commonly cited as critical in building artificial creative systems. From the perspec-
tive of strict adaptive creativity this is less problematic: an individual cannot behave
adaptively if it cannot determine the real-world value of its creative produce. But if
an individual is able to create value through influence, then the role of evaluation
in the creative process should strike a balance with other elements. Evaluation in
human artistic behaviour must be understood in the context of value creation, and
other aspects of artistic social interaction. We risk turning evaluation into a bottle-
neck through which we squeeze all artistic interaction. Escaping the narrow focus on
assessing aesthetic value, which avoids the need for a social individual that might be
capable of exporting or creating value, is an important but challenging direction for
arts-based computational creativity: what other dimensions of response, meaning
and interaction are needed in computational systems?
14.4 Generative and Adaptive Approaches to Arts-Based
Computational Creativity
Human-like adaptive creativity is the more traditional goal of arts-based computa-
tionally creative systems, but faces the challenge that the embodiment and situat-
edness of the artificial system is a poor reproduction of that of the human. It also
faces the additional challenge of building adaptively creative systems that satisfy
the constrained target of “valued” artistic output. Subsequently, some of the more
successful examples of computational creativity have been human-system collab-
orations, such as Harold Cohen and his
AARON
software (McCorduck
1990
), or
George Lewis and his
Voyager
software (Lewis
2000
).
A generative creativity approach seems equally problematic since generative cre-
ative systems are not adapted to goals and so cannot perform functions similar to
