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Computational Creativity: Coming of Age

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Computational Creativity: Coming of Age Editorial Computational Creativity: Coming of Age Simon Colton, Ramon López de Mántaras, and Oliviero Stock n This editorial provides an introduction to current AI research on computationally created A artifacts as well as to the papers and topics cov- t its heart, computational creativity is the study of build- ered by this special issue on computational cre- ing software that exhibits behavior that would be deemed cre- ativity. ative in humans. Such creative software can be used for autonomous creative tasks, such as inventing mathematical the- ories, writing poems, painting pictures, and composing music. However, computational creativity studies also enable us to understand human creativity and to produce programs for cre- ative people to use, where the software acts as a creative collab- orator rather than a mere tool. Historically, it’s been difficult for society to come to terms with machines that purport to be intel- ligent and even more difficult to admit that they might be cre- ative. 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. Groundbreak- ing for its time, this project was written up in a piece in Mecca- no Magazine. The article was titled “Are Thinking Machines Pos- sible” 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 amaz- ing advances in hardware and software technology that fol- lowed those meccano models? Sadly, no. Not much. Even with- in computer science, people are still skeptical about the creative potential of software. For instance, in Non-Photorealistic Render- ing, 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 could- Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved. ISSN 0738-4602 FALL 2009 11 Editorial n’t disagree more. As is hopefully evident from the ue are produced by increasingly autonomous cre- articles in this volume, creativity is not some mys- ative systems. tical gift that is beyond scientific study but rather In the article by Amilcar Cardoso, Geraint Wig- something that can be investigated, simulated, and gins, and Tony Veale (“Converging on the Diver- harnessed for the good of society. And while soci- gent: The History [and Future] of the Internation- ety might still be catching up, computational cre- al Joint Workshops in Computational Cre - ativity as a discipline has come of age. This matu- ativity”), more of the issues about which the com- rity is evident in the amount of activity related to munity is coming to consensus are explored. This computational creativity in recent years; in the is done within the context of a survey of 10 years sophistication of the creative software we are of computational creativity workshops. The building; in the cultural value of the artifacts being authors start by separating the word creativity produced by our software; and most importantly, from the concept of “creativity,” and put both of in the consensus we are finding on general issues these into historical context. In addition to his- of computer creativity. torical case studies, they survey, compare, and In the early days of AI research, many of the contrast the philosophical and practical contribu- projects had grand goals: to build software able to tions made by key players in the field over the compose sonatas, invent mathematical theories, years and describe some logistics, such as the rise and so on. In those days, the artifact-generation of the “show and tell” sessions at the annual paradigm reigned supreme: the emphasis was on meetings. They end by highlighting the prospects software that simulated entire reasoning and for research in this area and arguing that the field invention processes in order to build artifacts of of computational creativity is very close to hav- real value. However, as further studies highlighted ing firm enough foundations for rigorous scien- how difficult it is to implement artificially intelli- tific investigations in the future. This will be test- gent programs, AI researchers adopted the prob- ed in coming years, as the series of computational lem-solving paradigm. Here, an intelligent task is creativity workshops evolves into the first com- immediately broken down into manageable sub- putational creativity conference, to be held in Lis- parts and characterized as either a machine-learn- bon in January 2010.1 ing problem, a planning problem, a theorem-prov- Margaret Boden has been a key player in the ing problem, and so on. This kind of shoehorning field of computational creativity for a long time, enabled AI research to advance and—important- having authored a number of influential books ly—to demonstrate advances in concrete terms. and papers. Her scholarly article here (“Computer Research in these subareas flourished, but it frag- Models of Creativity”) examines some of the mented AI research: how many people regularly go thorny philosophical issues surrounding human to both machine-learning and theorem-proving and computer creativity. Unlike some authors conferences, for instance? working on creativity issues, she starts from the While problem solving certainly requires cre- premise that creativity isn’t a magical process that ativity, the majority of computational creativity should be held in awe. From this starting point, researchers are more interested in the artifact-gen- Boden goes on to describe various ways in which eration paradigm and are actively engaged in put- computers can—and do—exhibit the same kinds ting the pieces back together again. In this way, by of behaviors that creative humans do. With special combining AI systems, we are able to “climb the emphasis on humor and visual arts as application metamountain.” By this, we mean that individual domains, and looking at evolutionary processes as techniques from AI and other areas of computing particularly valuable for computational creativity, such as graphics are sufficiently powerful enough Boden characterizes creative behaviors in terms of for us to enable software to take on tasks at increas- computer exploration, whether combinatorial and ing metalevels. For instance, automated painting transformational. The article ends by posing a has largely been associated with graphics research, question about whether computers can be truly where researchers have produced great tools that creative and by pointing out that through AI simulate some physical aspects of the painting research, we now have an understanding of what process but not the cognitive aspects. Computa- sort of phenomenon creativity is. tional creativity researchers take their techniques, The article by Gerhard Widmer, Sebastian Floss- and ones from machine vision and other areas of mann, and Maarten Grachten (“YQX Plays AI, and simulate the way in which artists use these Chopin”) describes a computer program that tools, for instance, by implementing scene con- learns to expressively perform classical piano struction methods. After this, we can look at the music. The approach is data intensive and based motivation for scene construction to express cer- on statistical learning. Performing music expres- tain concepts and ideas, and so on. In this fashion, sively certainly requires high levels of creativity, more of the cognitive aspects of creative processes but the authors take a very pragmatic view to the are simulated, and artifacts of higher cultural val- question of whether their program can be said to 12 AI MAGAZINE Editorial be creative or not and claim that “creativity is in humor. To some, the field may sound too ambi- the eye of the beholder.” In fact, the main goal of tious: many people view humor as one of the most the authors is to investigate and better under- intriguing and distinguished forms of intelligence. stand music performance as a creative human In fact, if an artificial system were to produce jokes behavior by means of AI methods. AI has played and forms of humor of all sorts, it would be based a crucial role in the history of computer music on the realization of most intelligent capabilities. almost since its beginning in the 1950s. However, The computational humor scope is currently much until quite recently, most effort had been on com- narrower, but some interesting forms of humor, positional and improvisational systems and little like puns, funny ambiguous references, or for that efforts had been devoted to expressive perform- matter ironical expressions, can be produced auto- ance. matically. Ritchie provides an overview of some The article by Pablo Gervás (“Computational realizations, which in fact display a certain level of Approaches to Storytelling and Creativity”) first creativity, and discusses various aspects involved. addresses the issue of creativity from a general per- Our final article is a surprise, a kind of special spective, not only emphasizing the main features guest for this issue of AI Magazine. It is a pleasure of interest in any creative process, such as novelty, to include in this collection of written contribu- unexpectedness, and usefulness (or goal satisfac- tions something different, food for the brain in an tion)
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