In research, both problem finding and problem solving are important. Surprisingly often, problem finding is more important than problem solving.
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Replying to @michael_nielsen
I'm reminded of
@Meaningness's "problem formulation" section in How To Think Real Good https://meaningness.com/metablog/how-to-think …, which has a lot of anecdotal gems1 reply 0 retweets 4 likes -
Replying to @MuhammadPuter12 @michael_nielsen
Slightly embarrassed by that piece now; I wrote it in one long day, many years ago, when
@xuenay asked “if not Bayesianism, then what?” It’s a half-baked brain-dump. But I’m glad it’s still of some interest! Book I’m writing now is trying to do a better job on the same topic.1 reply 0 retweets 1 like -
Replying to @Meaningness @MuhammadPuter12 and
In the current outline, problem finding/creation is in “When to get meta-rational,” “Locating trouble,” “Creating a Problem,” and “Feeling for an ontology.”pic.twitter.com/PDtPf9Nsb5
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Looking forward to the book. Just want to point out that the topic of my thread is field finding (not field founding nor problem finding).
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A fascinating topic about which very little else has been written, that I know of!
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Replying to @Meaningness @michael_nielsen and
Phil Agre’s investigation of the early history of AI/cogsci has some interesting examples. E.g., re your “developing an underlying narrative,” he looks closely at the the seminal Miller, Galanter, and Pribram paper, Newell and Simon’s GPS paper, and I think JMC’s Advice Taker
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Replying to @Meaningness @michael_nielsen and
These were out-of-the-blue, not addressing existing issues, and the set up the system of narrative metaphors that shaped AI through to the end of the symbolic era. (And arguably to the present day in some ways.)
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I don't explicitly remember, but it may well have been reading Agre that primed me to think along these lines. I used to read his Red Rock Eater newsletter, and tonnes of other things he wrote.
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