The Creativity Code: How AI is learning to write, paint and think

by Marcus du Sautoy

David Cope first turned to algorithms out of desperation. He’d been commissioned to write a new opera and was procrastinating, unable to commit notes to stave. But then he had an idea. He remembered how Ada Lovelace had speculated that ‘the engine might compose elaborate and scientific pieces of music of any degree of complexity or extent’ and decided to explore her idea. He started experimenting by feeding punch cards into an IBM computer (this was the early 1980s). Notes appeared as output. His early experiments, he later admitted, were truly dreadful. But he persevered, heading off to Stanford to do a course in computer music. With the deadline for his opera commission fast approaching, he decided to put his computing skills to the test. If he could get an algorithm to understand his compositional style, then whenever he got stuck and didn’t know how to proceed, the algorithm could make a suggestion that would be compatible with his particular way of composing. Even if the algorithm suggested something Cope considered absurd, it would at least help him understand what might have been a better choice. The algorithm would act as catalyst to spur his creativity. Cope called his new concept ‘Experiments in Musical Intelligence’, or EMI for short. The alter ego composer that began to emerge from these algorithmic experiments would later be called Emmy, partly to avoid confusing the project with the British recording label EMI, partly to give the algorithm a more human name.