Creativity Versus the Perception of Creativity in Computational Systems

By Simon Colton. AAAI Spring Symposium: Creative Intelligent Systems, 2008

299 citations recorded by the source corpus.

How researchers see this paper

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CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms (2017, background): “Colton 2008 suggested three criteria that a creative system should have: the ability to produce novel artifacts (imagination), the ability to generate quality artifacts (skill), and the ability to assess its own creation [4].”
CLIP-CLOP: CLIP-Guided Collage and Photomontage (2022, methodology): “2010) in the The Painting Fool (Colton 2008) employed keyword retrieval-based methods to make thematic news-based juxtapositions of images.”
Computational Creativity: The Final Frontier? (2012, background): “In domains like the visual arts, information about how an artefact has been produced is often used when judging the value of that artefact [10, 16, 20].”
Copyright in generative deep learning (2021, unknown): “Second, because of the nature of the generated outputs (especially against the nature of outputs generated by other kinds of AI (Colton, 2008), which simply follow rules explicitly provided by the programmer).”
Characterizing LLM scientific concept generation: A multi-dimensional measurement study (2026, unknown): “…creativity literature provides theoretical frameworks for assessing creative outputs, including Boden’s distinction between combinational, exploratory, and transformational creativity [7], Colton’s creative tripod framework [14], and Wiggins’ formalization of creative search spaces [15].”