Hmmm... would have to think more in depth on this, but on first blush, my dumb answers would be that essentially, those three things seem to go together, in low-stakes/trivial stuff (e.g. poker, sports betting); while (a) and (b) go together for higher-stakes hard-science estimates of well-understood physical phenomena (e.g. climate chan…
Hmmm... would have to think more in depth on this, but on first blush, my dumb answers would be that essentially, those three things seem to go together, in low-stakes/trivial stuff (e.g. poker, sports betting); while (a) and (b) go together for higher-stakes hard-science estimates of well-understood physical phenomena (e.g. climate change). In these cases, Bayes is the right way to go, I think.
But generally, as the stakes get higher, stuff is simply not predictable, and applying game theory approaches to fundamentally unpredictable things can get us all into very serious trouble. I keep going back to the Herman Kahn game theory approach to nuclear weapons. Maybe there really is a kind deity, because I suspect we have been incredibly lucky not to have blown it all up using that kind of kooky approach. I used to think the game theorists had kept us alive until I read Michael Dobbs' 2009 book "One Minute to Midnight" about the Cuban Missile Crisis. Everything I had crammed into my head about that event (mainly via Bobby Kennedy's "Thirteen Days" in Harvard Government classes) was complete fiction. The JFK ExComm had this very elaborate mental model of the Soviet leadership's approach to the crisis, and it was complete crap. If one Soviet sub officer had not vetoed nuking a US Navy convoy that was forcing it to the surface in the Caribbean, we might not be here discussing this. There was no "the other guy blinked" moment non the quarantine line; there was no Politburo coup against Khrushchev with the second hard-line cable; there were 80 MRBMs armed and ready to launch if attacked, with local control. We were incredibly lucky, not good at game theory.
I think we try to apply mathematically rigorous game-theory-type approaches to way too many intersubjective realities (of Keynes' "beauty pageant" type). And as long as the mental models are shared widely, they work. But as soon as mass opinion shifts, they go kablooey. Because the laws of physics do not apply to mass delusions (e.g. religion, patriotism, fashion, the stock market, belief that home prices in the U.S. never decline across the entire country), they can abruptly shift in a way physical materials, poker games, and even baseball games cannot.
Games are designed to deliver dopamine hits in small increments, with reasonably low stakes, the exact way cigarettes deliver nicotine hits. Real fundamental uncertainty doesn't do that, but Nate Silver implicitly seems to promise his readers that it can. What we really need for the high-stakes stuff is not more Bayes, but a more systematic and rigorous approach to imagining the full range of plausible large scale outcomes, and then use math and logic to explain how those outcomes might happen. It's a bit terrifying, because you cannot go through that process and remain unaware of just how vast the scale of uncertainty (and the universe of truly plausible outcomes) really is.
I'm about to write a few scenarios of this election from about four years in the future. I think they will correspond to your "small things that happened in the past of which we are now ignorant will turn out to have made the difference" hypothesis. (The monster early voting turnout in Georgia is of this type of thing.) I never like to say things are predictable, but if she loses, the "She should have chosen Josh Shapiro" garbage that would follow is kind of a lock. As well as the "If only Trump had moderated in the last few weeks he would have won" garbage that would follow him losing. No one knows, as you say - abortion might already have won the election for Kamala; her 2019 trans-friendly statement might have already lost it for her.
It's a scary world, and nobody knows nuttin.' That's why we like to pretend there is talismanic power in poll aggregation. Gimme another nicotine hit...
Hmmm... would have to think more in depth on this, but on first blush, my dumb answers would be that essentially, those three things seem to go together, in low-stakes/trivial stuff (e.g. poker, sports betting); while (a) and (b) go together for higher-stakes hard-science estimates of well-understood physical phenomena (e.g. climate change). In these cases, Bayes is the right way to go, I think.
But generally, as the stakes get higher, stuff is simply not predictable, and applying game theory approaches to fundamentally unpredictable things can get us all into very serious trouble. I keep going back to the Herman Kahn game theory approach to nuclear weapons. Maybe there really is a kind deity, because I suspect we have been incredibly lucky not to have blown it all up using that kind of kooky approach. I used to think the game theorists had kept us alive until I read Michael Dobbs' 2009 book "One Minute to Midnight" about the Cuban Missile Crisis. Everything I had crammed into my head about that event (mainly via Bobby Kennedy's "Thirteen Days" in Harvard Government classes) was complete fiction. The JFK ExComm had this very elaborate mental model of the Soviet leadership's approach to the crisis, and it was complete crap. If one Soviet sub officer had not vetoed nuking a US Navy convoy that was forcing it to the surface in the Caribbean, we might not be here discussing this. There was no "the other guy blinked" moment non the quarantine line; there was no Politburo coup against Khrushchev with the second hard-line cable; there were 80 MRBMs armed and ready to launch if attacked, with local control. We were incredibly lucky, not good at game theory.
I think we try to apply mathematically rigorous game-theory-type approaches to way too many intersubjective realities (of Keynes' "beauty pageant" type). And as long as the mental models are shared widely, they work. But as soon as mass opinion shifts, they go kablooey. Because the laws of physics do not apply to mass delusions (e.g. religion, patriotism, fashion, the stock market, belief that home prices in the U.S. never decline across the entire country), they can abruptly shift in a way physical materials, poker games, and even baseball games cannot.
Games are designed to deliver dopamine hits in small increments, with reasonably low stakes, the exact way cigarettes deliver nicotine hits. Real fundamental uncertainty doesn't do that, but Nate Silver implicitly seems to promise his readers that it can. What we really need for the high-stakes stuff is not more Bayes, but a more systematic and rigorous approach to imagining the full range of plausible large scale outcomes, and then use math and logic to explain how those outcomes might happen. It's a bit terrifying, because you cannot go through that process and remain unaware of just how vast the scale of uncertainty (and the universe of truly plausible outcomes) really is.
I'm about to write a few scenarios of this election from about four years in the future. I think they will correspond to your "small things that happened in the past of which we are now ignorant will turn out to have made the difference" hypothesis. (The monster early voting turnout in Georgia is of this type of thing.) I never like to say things are predictable, but if she loses, the "She should have chosen Josh Shapiro" garbage that would follow is kind of a lock. As well as the "If only Trump had moderated in the last few weeks he would have won" garbage that would follow him losing. No one knows, as you say - abortion might already have won the election for Kamala; her 2019 trans-friendly statement might have already lost it for her.
It's a scary world, and nobody knows nuttin.' That's why we like to pretend there is talismanic power in poll aggregation. Gimme another nicotine hit...