
Now that’s arrogance , but funny as hell!
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It's how I once teased a normie who complained that I dare to think for myself and disagree with the ideology of her cult
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She’s not a friend of you I hope
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Some of my best friends are normies
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I don’t know if that is arrogance speaking as in you can tolerate them ? Or are you serious?
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I am serious, of course. Normies are only a threat when you don't understand them or they are swarming in mob mode; most are good people who are just influenced more by external validation than by their own judgement. Terrence Malik's new movie "Hidden Life" comes to mind.
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There’s an argument embedded in this thread that basically says “internal logic properly representing truth is the only reasonable basis for behavior”. This is false.
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That is a misunderstanding. It's just that when your default behavioral wiring (which we perceive as intuition) does not lead to successful results, reason is the most important tool to fix it. Reason goes wrong very easily, but faulty behavioral intuitions go wrong all the time.
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The beginning of this conversation was about bias. I’m assuming Cornelia’s desire to avoid bias is to be correct because then people will behave cooperatively
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Put differently, I often see an intuition that if I do all the right things people will behave as I’d like them to. And if I’m wrong they’ll fight me. But this doesn’t really engage with the part that matters, which is signaling ingroup
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I am not sure what you mean by bias. The presently popular normie cult uses the term as newspeak for the difference between public and private opinion. Bias can also be a systematic distortion of the world model from the truth, or it can simply mean preference.
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Cordelia’s reply: “You mean your own emotions are making you biased” Implicit assumptions in here include: 1) emotions are a problem 2) being biased is bad I’m drawing a conclusion here that there is a value for being correct, which translates to logical
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I would say that 1) feelings are system 1 assessments of your situation; they have to be fully accounted for but can be systematically wrong or systematically misunderstood. 2) Biases make it less likely to arrive at truthful models; the modeling part of you needs equanimity.
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