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Before Twitter and Google we used to become overnight experts on big news topics by rushing to the library and reading encyclopedias.
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Dunno why people are so down on sudden expertise. It’s better than persistent ignorance. Twitter sense-making crash courses have in fact made me more knowledgeable on many hot-take topics than on topics I’ve taken college classes in.
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People really have poor intuitions on the radical effects of information abundance, real-time updating, collective sensemaking, and Darwinian filtering of bs. College is good for topics where deep reasoning is needed. For everything else, use the hive mind.
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Never forget, fast-OODA people with Twitter degrees making up mental models out of shitposts routinely did better than people listening to degreed experts through the pandemic. High variance outcomes of course but not random.
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In data rich situations, boundary intelligence can eat interior intelligence for lunch. The way deep learning can beat traditional GOFAI. Twitter hive-mind is a deep learning system. Turn up your nose at it at your own peril.
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1/ I'd like to make up a theory of intelligence based on a 2-element ontology: boundary and interior intelligence
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The trick is not to get attached to the hive mind either. Thar be crackpottery. The evil twin to “when did you become an expert on X?” Karen is “do your own research” crank.
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One big reason the hivemind works unexpectedly well on messy FUD is that no matter what they topic there’s likely to be somebody who knows enough to penetrate media Gell-Mann amnesia fields. Which is a function of raw data more than credentials or process discipline.
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Why is “filtering well” easier than judging the subject directly? Or in other words, how do you accurately judge an expert without having your own expertise on their area? (Honest question. Some people clearly get this wrong, after all.)
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