Computational Creativity: Coming of Age

ing software that exhibits behavior that would be deemed creative in humans. Such creative software can be used for autonomous creative tasks, such as inventing mathematical theories, writing poems, painting pictures, and composing music. However, computational creativity studies also enable us to understand human creativity and to produce programs for creative people to use, where the software acts as a creative collaborator rather than a mere tool. Historically, it’s been difficult for society to come to terms with machines that purport to be intelligent and even more difficult to admit that they might be creative. For instance, in 1934, some professors at the University of Manchester in the United Kingdom built meccano models that were able to solve some mathematical equations. Groundbreaking for its time, this project was written up in a piece in Meccano Magazine. The article was titled “Are Thinking Machines Possible” and was very upbeat, but surprisingly ends by stating that “Truly creative thinking of course will always remain beyond the power of any machine.” Surely, though, this attitude has changed in light of the amazing advances in hardware and software technology that followed those meccano models? Sadly, no. Not much. Even within computer science, people are still skeptical about the creative potential of software. For instance, in Non-Photorealistic Rendering, a graphics textbook published in 2000, authors Thomas Stothotte and Stefan Schlechtweg boldly state that “simulating artistic techniques means also simulating human thinking and reasoning, especially creative thinking. This is impossible to do using algorithms or information processing systems.” We couldEditorial