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theory of enaction claims that cognition and creativity always emerge through a
real-time and improvised interaction with the environment and other agents in that
environment (Varela et al.
1991
; Stewart et al.
2010
). While traditional theories
could work to incorporate this perception-action feedback loop to model continuous
improvised interaction, the enaction theory begins with the assumption that all cog-
nition is based on this principle of improvised interactions guided by feedback from
the environment. Starting from this basic assumption makes developing an enactive
model of collaborative creativity and co-creation much easier due to their improvi-
sational nature.
The overall aim of this chapter is to show how an enactive approach to computa-
tional creativity can make it easier to think about, design, and build creative com-
puters, especially those that are able to improvise in real-time collaboration with
human users. To situate and motivate our contribution, we fi rst describe the fi eld of
computational creativity. Next, we introduce the cognitive science theory of enac-
tion and describe creativity through its theoretical lens. Then, we present our enac-
tive model of creativity and explain how its principles helped design “enactive”
creative systems in two different domains: visual art and design.
7.2
Computational Creativity
Computational creativity is an outgrowth of artifi cial intelligence, cognitive science,
and creativity research. It studies and builds creative systems involving different
combinations of creative humans and creative computers. Making creative comput-
ers is a kind of grand challenge for the modern era of computing, and the recent
efforts in computational creativity show a promising path forward. The fi eld of
computational creativity can be segmented into three broad categories that each
have different motivations and goals.
Creativity support tools
augment and enhance
human creativity, such as Adobe's Photoshop or Computer Aided Design tools.
Generative systems
produce creative artifacts (semi-)autonomously, such as com-
puters that paint pictures (see Fig.
7.1
) (McCorduck
1991
; Colton and Wiggins
2012
) or generate poetry (Colton et al.
2012
).
Computer colleagues
collaborate with
human users on creative tasks much like another human would (see Fig.
7.2
).
Once it was established that creativity could be trained, facilitated, and mea-
sured, researchers began to develop techniques to support creativity (Smith et al.
1995
; Guilford
1970
; Csikszentmihalyi
1997
). Initially, these techniques were pro-
cedural activities one could engage in to stimulate creativity, such as brainstorming
and lateral thinking exercises (Rawlinson
1981
; Bono
1970
). Researchers also
began developing a new class of technology referred to as creativity support tools
(CSTs) (Shneiderman
2002
; Shneiderman et al.
2006
; Hewett et al.
2005
; Carroll
et al.
2009
). CSTs are designed to help users explore a creative domain, record deci-
sion histories, and scaffold skills to allow and encourage users to learn expertise
(Candy
1997
; Shneiderman
2007
).
