> Frequentist probability is objective because it defined in terms of falsifiable real-world observations. An objective definition of probability can be used to

> Frequentist probability is objective because it defined in terms of falsifiable real-world observations. An objective definition of probability can be used to resolve disagreements between scientists. A subjective definition cannot. That's why Frequentist probability is used as the foundation of science and Bayesian probability isn't. Such statements are one of reasons I cannot take Lesswrong seriously. The author has very vague mental model of a science, he doesn't read scientific articles (because if he was reading them he would know that bayesian analysis is a thing in a scientific research), but he has an opinion on relationships of science and bayesian probability. The very first skill of any rationalist is to know boundaries of his competence. Author's failure with his prediction of outcome of Russia-Ukraine war should tell him just about it: you need to learn boundaries of your competence. But the author failed to generalize his experience. If you have no idea about Russia, Ukraine, war, then you cannot make a reliable prediction on outcome of the war. If experts cannot make a reliable prediction, then all your bayesianism wouldn't help you. If you was an expert then you probably could make better predictions with bayesianism than without it. Knowledge is a necessary prerequisite for a successful prediction, bayesianism can help to use knowledge, but it cannot substitute it. Knowledge without bayesianism can be enough for a successful prediction, but bayes theorem without knowledge is just a bunch of math symbols. "Garbage in, garbage out". If you feed your lack of knowledge into Bayes' formula then you get lack of predictions out of it. If you know about science from textbooks, then you cannot hope for insights about science. Harry Potter in HPMoR thinks of himself as of scientist. It is so clueless I have no words to explain. And people from lesswrong seem to share his delusions: like if they know about bayes probability it makes them to be scientists. No. If you want to become a scientist you need to work for a while on some scientific research with an advisor. To read dozens of papers, to search through hundreds of papers, to talk with people, to share your ideas with them and to defend your ideas from their critique. And to collect real data from real experiment to see all the shortcomings of the process. One cannot become a scientist without real experience of a scientific work. Though, I'd say I liked his examples how to apply bayes theorem to a real task.