The Importance of a Generative Process in Creativity

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Sally Kohn: I think our creativity can be better when we start being extremely generative and generate lots of ideas. Rather than sort of wait until you just suddenly get struck with, you know, one or two good ideas, she says, the first process tends to work better. "I definitely agree that there can be a kind of an interplay between wide, generative creation and this windowing process"

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Where does innovation come from? How common is it for "lone wolf" scientists to make large leaps in innovation by themselves? How can we imbue AIs with creativity? Or, conversely, how can we apply advances in AI creativity to our own personal creative processes? How do creative strategies that work well for individuals differ from creative strategies that work well for groups? To what extent are models like DALL-E and ChatGPT "creative"? Can machines love? Or can they only ever pretend to love? We've worried a fair bit about AI misalignment; but what should we do about the fact that so many humans are misaligned with humanity's own interests? What might it mean to be "reverent" towards science?

Joel Lehman is a machine learning researcher interested in algorithmic creativity, AI safety, artificial life, and intersections of AI with psychology and philosophy. Most recently he was a research scientist at OpenAI co-leading the Open-Endedness team (studying algorithms that can innovate endlessly). Previously he was a founding member of Uber AI Labs, first employee of Geometric Intelligence (acquired by Uber), and a tenure track professor at the IT University of Copenhagen. He co-wrote with Kenneth Stanley a popular science book called Why Greatness Cannot Be Planned on what AI search algorithms imply for individual and societal accomplishment. Follow him on Twitter at @joelbot3000 or email him at lehman.154@gmail.com.

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