I find that when trying to be creative, I think constraints actually often makes the creativity easier. There's also this interesting approach you can use where you take the space of all things and you try to break it into MECI categories. And in doing so, you can actually fill out the space sometimes much more effectively than if you just try to brainstorm the whole space directly. Yeah, there are probably lots of different creative brainstorming strategies that would help you to kind of more exhaustively explore space. It is cool to have lots of different flexible tools for messing around with ideas.
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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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