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> The entire point was to throw away entirely our reliance on frequency and association -- this is ancient superstition. And instead, to explain the world by n

> The entire point was to throw away entirely our reliance on frequency and association -- this is ancient superstition. And instead, to explain the world by necessary mechanisms born of causal properties which interact in complex ways that can never uniquely reveal themselves by direct measurement. Who said that? You make it sound like this was some important trend in the past, that got derailed by the evil statisticians (spoiler: there never was such a trend that was big enough to have momentum). Your rant against statistics is all nice and dandy, but when you have to translate that website from a foreign language into English automatically, when you ask ChatGPT to generate you some code for a project you work on, or when you are glad that Google Maps predicted your arrival time at the office correctly, you rely on the statistics you vilify in essential ways. You basically are a customer of statistics every day (unless you live under a rock, which I don't think you do). Statistics is good because it works, and it works well in 90% cases which is enough. What you advocate for so zealously (whatever such a causally validated theory would be) currently doesn't.

mjburgess 3y ago
Well if you want something like the actual history... we have francis bacon getting us close to an abductive (ie., explanatory) method, decartes helped a bit -- then a great catastrophe befell science called Hume. Since Hume it become popular to somehow rig measurement to make it necessarily informative (Kant), or to claim that measurement has no necessarily informative relation to reality at all (in the end, Russell, Ayer et al.). It took a while to dig out of that nightmarish hole that philosophers largely created, back into the cold light of experimental reality. It wasnt statisticians who made the mess; it was first philosophers, and today, people learning statistical methods without learning statistics at all. Thankfully philosophers started actually reading science, and then they realised they'd go it all wrong. So today, professional research philosophy is allied against the forces of nonsense. As far as the success of causal explanations, you owe to that everything, including the very machine which runs ChatGPT. That we can make little trinkets on association alone pales in comparison to what we have done by knowing how the world works.

mjburgess 3y ago

Well if you want something like the actual history... we have francis bacon getting us close to an abductive (ie., explanatory) method, decartes helped a bit -- then a great catastrophe befell science called Hume. Since Hume it become popular to somehow rig measurement to make it necessarily informative (Kant), or to claim that measurement has no necessarily informative relation to reality at all (in the end, Russell, Ayer et al.). It took a while to dig out of that nightmarish hole that philosophers largely created, back into the cold light of experimental reality. It wasnt statisticians who made the mess; it was first philosophers, and today, people learning statistical methods without learning statistics at all. Thankfully philosophers started actually reading science, and then they realised they'd go it all wrong. So today, professional research philosophy is allied against the forces of nonsense. As far as the success of causal explanations, you owe to that everything, including the very machine which runs ChatGPT. That we can make little trinkets on association alone pales in comparison to what we have done by knowing how the world works.