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'Artificial Intelligence Challenges What It Means to Be Creative' by Richard Moss
Richard Moss writes the following for Science News:
When British artist Harold Cohen met his first computer in 1968, he wondered if the machine might help solve a mystery that had long puzzled him: How can we look at a drawing, a few little scribbles, and see a face? Five years later, he devised a robotic artist called AARON to explore this idea. …
Not far behind was the composer David Cope, who coined the phrase ‘musical intelligence’ to describe his experiments with artificial intelligence–powered composition. Cope once told me that as early as the 1960s, it seemed to him ‘perfectly logical to do creative things with algorithms’ rather than to painstakingly draw by hand every word of a story, note of a musical composition or brush stroke of a painting. …
Cohen and Cope were among a handful of eccentrics pushing computers to go against their nature as cold, calculating things. The still-nascent field of AI had its focus set squarely on solid concepts like reasoning and planning, or on tasks like playing chess and checkers or solving mathematical problems. Most AI researchers balked at the notion of creative machines.
Slowly, however, as Cohen and Cope cranked out a stream of academic papers and books about their work, a field emerged around them: computational creativity. It included the study and development of autonomous creative systems, interactive tools that support human creativity and mathematical approaches to modeling human creativity. In the late 1990s, computational creativity became a formalized area of study with a growing cohort of researchers. ...
Soon enough—thanks to new techniques rooted in machine learning and artificial neural networks, in which connected computing nodes attempt to mirror the workings of the brain—creative AIs could absorb and internalize real-world data and identify patterns and rules that they could apply to their creations.
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