How can [a creative idea] arise, then, if not by magic? And how can one impossible idea be more surprising, more creative, than another? How can creativity happen?- from Margaret Boden's Creativity and Unpredictability
How can [a creative idea] arise, then, if not by magic? And how can one impossible idea be more surprising, more creative, than another? How can creativity happen?
- from Margaret Boden's Creativity and Unpredictability
Creativity is sometimes taken to be an inexplicable aspect of human activity. By summarizing a considerable body of literature on creativity, I hope to show how to turn some of the best ideas about creativity into programs that are demonstrably more creative than any we have seen to date. I believe the key to building more creative programs is to give them the ability to reflect on and modify their own frameworks and criteria. That is, I believe that the key to creativity is at the metalevel.
"Our goal is to come up with an algorithmic definition of creativity, a set of processes and steps that can account for the kind of creative thinking that we observe in people. Although the idea of a human or machine exhibiting creativity by following a set of rules seems on the face to be a contradiction, this is not necessarily so."
AARON is a program designed to investigate the cognitive principles underlying visual representation. Under continuous development for fifteen years, it is now able autonomously to make "freehand" drawings of people in garden-like settings. This has required a complex interplay between two bodies of knowledge: object-specific knowledge of how people are constructed and how they move, together with morphological knowledge of plant growth: and procedural knowledge of representational strategy.
I write programs which are intended to throw some light upon what people do, in a cognitive sense, when they make images: not upon what their images look like. Art is a series of acts, not a series of objects. From which it follows that nobody ever made original art - with or without a computer - by mimicking the appearances of existing original art.
My most astonishing discovery came at Carnegie Mellon University, where Marcel Just and Tom Mitchell have been using real-time functional MRI scanners to do some actual mind reading---or thought recognition, as they more responsibly call it.
As I lay in the fMRI, I saw 20 images on the screen (of a strawberry, skyscraper, cave, and so on). I was instructed to imagine the qualities of each object. The computer would try to figure out, from every two objects, the sequence of the two images I had just seen (whether strawberry had come before skyscraper, for example). It got them 100 percent right.
[Patrick] Tresset's robots use computer vision to identify their subjects---they can recognize faces---and then they spend about 30 minutes on each portrait. (One of his earlier-generation robots, Pete, will actually doodle when there are no faces in sight to draw.) The early versions were crude and involved not physical robots but simulated drawing created with computer-aided drafting programs. But over the past 10 years or so, Tresset and Frederic Fol Leymarie, his co-director at the Aikon project at Goldsmiths University of London, have made tremendous progress.
Ashok Goel challenges well-worn notions of design and creativity and makes a powerful case for bio-inspired design wherein nature serves as the ultimate inspiration for design innovation and sustainability.
When BYU PhD candidate Kristine Monteith was sitting in natural language processing class, it wasn't letter sequences going through her head but music notes. The Utah State graduate in music therapy pursuing her PhD in computer at BYU decided to apply her right and left brain abilities to combine music and computer science. She invented a computer program that can compose original music that evokes emotions humans can relate with, even though it was generated from a machine. In the survey she performed for that, she found that 54 percent of listeners could identify the emotions in computer-generated music, while for the human-composed music, only 43 percent could identify the emotions in the melodies.
Just one of the many papers available in this collection of papers by Harold Cohen, creator of Aaron, the painter.
Excellent summary of the development of the Aaron program through 1994.
See also: Stanford Humanities Review, Volume 4, issue 2
An 18th Century automaton that could beat human chess opponents seemingly marked the arrival of artificial intelligence. But what turned out to be an elaborate hoax had its own sense of genius, says Adam Gopnik.
...So the inventor's real genius was not to build a chess-playing machine. It was to be the first to notice that, in the modern world, there is more mastery available than you might think; that exceptional talent is usually available, and will often work cheap.