Want to Understand Creativity? Enlist an AI Collaborator – WIRED

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A metronome ticks time. Not for the student, but for the teacher, who plays a short piano melody. Without missing a measure, the student follows with an improvised, yet derivative, cello run. The student plays the same run again, and then again. I have it looping, actually, so you can hear the response over and over again, says the teacher, Jesse Engel, a computer scientist with Google Brain. And you can hear some similarities with what I played, but its not doing the job of trying to replicate what I played. Its trying to continue it in a meaningful way.

The student here is an artificial intelligence algorithm; the instrument, a synthesizer. And the reallesson is teaching an audience of hundreds how computers might someday become capable of producing real works of art. Engels is onstage at NYUs Skirball Center for the Performing Arts as part of the 2017 World Science Festival, along with three likeminded experts. Eachof themis there to showcasehow they nurture creativity in computers.

Which begs the question: What is creativity? The broadest definition is any nonlinear solution to a problem. Music is a creative way of making noises that sound pleasant. Language is creative communication. Airplanes are a creative solution to the problem of flight. But the fact that we can build airplanes that fly faster and higher than birds does not necessarily explain how birds fly, or how they evolved to fly, says Peter Ulric Tse, a neuroscientist at Dartmouth College. Tse is onstage with Engel, but rather than using AI to tackle a creative endeavor, such as music, he believes they are a vehicle for understanding the nature of creativity itself.

In humans, creativity evolved mysteriously. Homo sapiens became a distinct species around 200,000 years ago. Our ancestors characteristic (or, sapient, if you will) feature wastheir huge foreheads: the site ofthe frontal cortex, where high-level reasoning occurs. But the earliest indications of creativity in humans didnt appearuntil relatively recently. Asculpture of a human with a lions headone of the earliest examplesdates to around 40,000 years ago. That, and other archaeological evidence from the same time period meanswe Homo sapienslikely spent most of ourevolutionary history with unrealized creative potential. However, no physical evidence exists toexplain whatflipped the switch. Thoughts dont leave fossils, neurocircuits dont leave fossils, says Tse. All we have are bones and skulls and artifacts.

Artificial intelligences path towards creativity probably wont ever fully explain how it evolved in humans. At most, it will give neuroscientists like Tse ways to examine the problem laterally.But it could help scientists understand creativitys theoretical limits. Lav Varshney, another member of the onstage panel, is working on a mathematical theory of creativity. The way Ive been defining it is things that are both novel, and of high quality in their domain, says Varshney, an engineering theorist at the University of Illinois Urbana-Champaign. For example, a new kind of food.

In the case of cuisine, Varshney says he trains his AI to measure goodness based on things like hedonic psychophysicsa branch of research that studies the molecular properties of human flavor perception. He does similar work in fashion, feeding his algorithm information on color matching, and so on. And according to his research, creativity has theoretical limits. Varshney says that as you increase the value of both quality and novelty, you get more and more noise. That is, it becomes harder and harder to distinguish the newness, and the goodness, of a thing. This probably explains why the avant garde is so well, avant garde.

Like Engel, Varshney is also teaching algorithms to compose music. On stage, he demonstrates one that is learning to compose in the style of Bach. But, he points out, this is not pure creativity. The computer learns by having another algorithma teacherprogressively introduce constraintshere are different available instruments, these are chords, this what it means to sing in soprano. In essence, the algorithm is replicating Bachs creativity based, not evolving its own creative genius. As such, AI algorithms are best suited to be creative collaborators.

Which is exactly whatSougwen Chungdisplays next. Chung is a visual artist, currently an in residence at Bell Labs, who draws with a robotic arm assistant. Ive had a lot of human collaborators, and thought it was time to switch it up a little bit, she says. Watching the pairwoman and machinework together is mesmerizing. At first it looks like the arm is mirroring her strokes. But as a piece progresses, you see that the arm has its own style. Yes, a style that is derivativeof Chungsbut still not the same.

When Chung first started using the robotic armcalled DOUGshe thought the collaboration itself might be part of the artistic performance. However, she now believes the arm is pushing her to consider new creative frontiers. When I collaborate with this algorithm, theres a real randomness and sense of unpredictability to it, and a lack of understanding thats kind of exciting, she says.

If that kind of freedomis at the heart of creativity, the next logical question is whether algorithms could ever eclipse human creativity.Engel, who has settled back into his seat after his performance, seems to think the answer is no. The intentionality is human on both ends of the spectrum, he says. That is, humans are both the input and the consumer for anything a computer creates. You can treat it more like a garden, he says. You control the garden at a high level: planting seeds, watering it, pruning as necessary. But the garden grows on its own.

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Want to Understand Creativity? Enlist an AI Collaborator - WIRED