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by Frank | May 27, 2020, 9:18 PM

Theory

Historically, human creativity has been a neglected topic in psychology in general and intelligence testing in particular. Despite this, creativity is considered by most to be an essential component of human intelligence. Consequently, in attempting to answer the question of whether computers can think, it is only natural to ask whether computers can think creatively. Many feel, in fact, that whereas computers can excel in well-structured areas of problem solving - e.g. logic, algebra, etc. - they have little hope of ever producing truly creative work. For a work to be creative, it must be novel and useful- this represents an enormous challenge for AI.

The first two links below provide readers with general background on human creativity. The next two deal specifically with creativity in the context of AI.

  • Harnad on Creativity (if link fails, click here for a local copy) - This article is an excellent introduction to the study of human creativity, and focuses on "Pasteur's dictum": Chance favours the prepared mind.
  • The Creative Mind: Myths and Mechanisms (if link fails, click here for a local copy) - This article by Margaret Boden is actually the precis of her book covering creativity from a computational perspective. She proposes a theory of creativity that is subject to computational analysis, and potentially even computer simulation.
  • Creativity and Unpredictability (if link fails, click here for a local copy) - Margaret Boden, author of "The Creative Mind: Myths and Mechanisms" (above) discusses the idea that creativity is just an unpredictable combination of ideas. If so, computer modeling of creativity would be simple, it can combine ideas at random until something creative emerges. If not, we must find a more adequate theory of creativity before computer creativity is possible.
  • Schank on Creativity (if link fails, click here for a local copy) - Schank, like Boden, is interested in the possibility of defining, and then mechanising, the creative process. He discusses his own theories of creativity, which includes the use of some unique terminology: MOPs (Memory Organization Packets) and XPs (Explanation Patterns).

Practice

If AI is famous for anything, it's the so-called "engineering end-run". The idea that resources should not be spent over philosophical debates, instead focus should be on building actual engineering solutions. Later when we find an implementation that works, it can form the basis of more adequate theory. Many in the field of AI will remind you that this is precisely the strategy that worked quite well for aviation. After almost a century of debate on whether a flying machine would be possible, the first machine was constructed, the debate was solved, and a wealth of new data was produced. With that in mind, there have been several attempts to build creative computers, despite the lack of conceptual and theoretical consensus. The most impressive of these is AARON, a painting program that produces both abstract and lifelike works. How are we to judge whether such works of art are truly creative? Is it sufficient to judge the products or is the process by which they were created the determining factor? Below are two pages which do a particularly good job of summarizing the current applied work in computer creativity. Read the articles, look at the illustrations, and ask yourself if you would ever doubt, under normal circumstances, that the pictures were produced by an intelligent mind.

  • AARON (if link fails, click here for a local copy) - AARON is a now 20-year long project by Harold Cohen in machine creativity. The AARON system uses a small robotic turtle, combined with several drawing strategies, to produce original artwork. Its creator provides a detailed and accessible account of its progress, as well as several full colour images of AARON's work.
  • Creative Computers (local copy) - Robert Matthews of New Scientist Magazine discusses a large number of attempts at building creative computers. Includes commentary on many famous creative computers such as AARON and BACON. An accessible and fascinating read.
  • Harold Cohen, the inventor of AARON. You need Adobe Acrobat to view his latest essay "Colouring without seeing: a problem in machine creativity" which discusses how he defines creativity,
    and why AARON seems to fall short.

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