The problem is that when you talk about “ideal Science” it sounds like you mean something scientific practice attempts to achieve but falls short of but what you’re actually discussing is a second-hand imprecise (idealized) description of science. This sort of “science as hypothesis-testing” is a philosophical model. Historians often use it to interpret the history of science (although this has thankfully changed in recent years) and even scientists will resort to it when pressed for a description of their methods. But it’s not used (or aimed for) within science; I didn’t get any classes on general scientific method (or logic or inductive probabilism), I just learned a set of practical (including mathematical) skills. Science itself is an institutional and social practice and like all institutional and social practices we don’t presently understand how it works.
To expand on what I said about your other essay: Being able to create relevant hypotheses is an important skill and one a scientist spends a great deal of his or her time developing. It may not be part of the traditional description of science but that doesn’t mean it’s not included in the actual social institution of science that produces actual real science here in the real world; it’s your description and not science that is faulty. Think of science as movement along a trajectory. The period of apprenticeship in the scientific community that every practicing scientist goes through exists in order to calibrate the budding scientist and set him or her on the right course; it’s to get us all moving in the same direction. That this can’t be encapsulated into a set of neat rules isn’t a failure of science but a failure of descriptions of science.
This isn’t unique to science; it’s an issue in most institutions. When developing countries try to create a simulcrum of industrial practice from theory and description the result is usually a failure. When developing countries open themselves to foreign industry the newly established facilities, run by foreign experts who have causal ties through history to the very site of origin of their practices, impart a skillset on the local population who often then manage to combine that skillset and their unique understanding of their own culture to create their own businesses that can out-compete foreign industry. This is necessary because we don’t have a general understanding of institutions and therefore any description or theory designed to encapsulate what we need to do in order to copy their practices is necessarily incomplete or wrong.
Now, if you’re just saying the problem is that you, Eliezer, had a crappy understanding of Science and therefore went astray then what I’m saying supports your thesis. But you seem to be going further than that and making a claim about scientific practice. (It’s ambiguous though so I apologize if I have misinterpreted your intent.) I still, however, would reject the notion that Bayesianism is the hidden structure behind the success of science. What you would perhaps say is that when scientists learn to develop worthy hypotheses they are secretly learning how to become good Bayesians or learning cognitive practices that approximate what Bayes would tell us to do. But inasmuch as Bayes can be made to fit any scientific inferences it’s being used to address pseudo-problems (i.e., problems of justification) that the inferences did not need to be defended against to begin with; it’s in this respect that I think it’s unnecessary.
The difference between a scientist and a theologian is not a difference of rationality or a difference between how their cognitive processes approximate Bayesian insights. The difference is simply that one studied science and trained as a scientist and now works in a laboratory while the other studied theology and trained as a theologian and now works in the theology department. The scientist avoids coming to theological conclusions about his scientific studies as a matter of socialization. It is not necessary, however, that this socialization involve a general method for coming to the right conclusions. Science doesn’t need any such thing.
The Great Secret of Science, the reason scientists more often than not are the ones who produce science, is that science has all the science. Science begets science. What you learn from rolling balls down an inclined plane allows you to predict the trajectories projectiles, which allows you to discover that motion is parabolic or analyze the periodic motion of pendulums and eventually you, or one your colleagues, develops the calculus, and so on. This doesn’t all happen in one institution because of some general methodology or some universal recipe for getting the truth; it happens because that institution has all the experts. It’s always going to be the guy who understands the science who uses it to create new science because you need to understand the old science to create the new science. Beyond that there’s really nothing more left to explain; we have a complete causal explanation of science. If we wanted a philosophical justification of why we should accept science in the face of philosophical skepticism, then we would need to invoke Bayes (or whatever), but I’m not sure you think we need one of those. You seem to apply Bayes as the hidden cause of scientific success rather than the philosophical justification.
The problem is that when you talk about “ideal Science” it sounds like you mean something scientific practice attempts to achieve but falls short of but what you’re actually discussing is a second-hand imprecise (idealized) description of science. This sort of “science as hypothesis-testing” is a philosophical model. Historians often use it to interpret the history of science (although this has thankfully changed in recent years) and even scientists will resort to it when pressed for a description of their methods. But it’s not used (or aimed for) within science; I didn’t get any classes on general scientific method (or logic or inductive probabilism), I just learned a set of practical (including mathematical) skills. Science itself is an institutional and social practice and like all institutional and social practices we don’t presently understand how it works.
To expand on what I said about your other essay: Being able to create relevant hypotheses is an important skill and one a scientist spends a great deal of his or her time developing. It may not be part of the traditional description of science but that doesn’t mean it’s not included in the actual social institution of science that produces actual real science here in the real world; it’s your description and not science that is faulty. Think of science as movement along a trajectory. The period of apprenticeship in the scientific community that every practicing scientist goes through exists in order to calibrate the budding scientist and set him or her on the right course; it’s to get us all moving in the same direction. That this can’t be encapsulated into a set of neat rules isn’t a failure of science but a failure of descriptions of science.
This isn’t unique to science; it’s an issue in most institutions. When developing countries try to create a simulcrum of industrial practice from theory and description the result is usually a failure. When developing countries open themselves to foreign industry the newly established facilities, run by foreign experts who have causal ties through history to the very site of origin of their practices, impart a skillset on the local population who often then manage to combine that skillset and their unique understanding of their own culture to create their own businesses that can out-compete foreign industry. This is necessary because we don’t have a general understanding of institutions and therefore any description or theory designed to encapsulate what we need to do in order to copy their practices is necessarily incomplete or wrong.
Now, if you’re just saying the problem is that you, Eliezer, had a crappy understanding of Science and therefore went astray then what I’m saying supports your thesis. But you seem to be going further than that and making a claim about scientific practice. (It’s ambiguous though so I apologize if I have misinterpreted your intent.) I still, however, would reject the notion that Bayesianism is the hidden structure behind the success of science. What you would perhaps say is that when scientists learn to develop worthy hypotheses they are secretly learning how to become good Bayesians or learning cognitive practices that approximate what Bayes would tell us to do. But inasmuch as Bayes can be made to fit any scientific inferences it’s being used to address pseudo-problems (i.e., problems of justification) that the inferences did not need to be defended against to begin with; it’s in this respect that I think it’s unnecessary.
The difference between a scientist and a theologian is not a difference of rationality or a difference between how their cognitive processes approximate Bayesian insights. The difference is simply that one studied science and trained as a scientist and now works in a laboratory while the other studied theology and trained as a theologian and now works in the theology department. The scientist avoids coming to theological conclusions about his scientific studies as a matter of socialization. It is not necessary, however, that this socialization involve a general method for coming to the right conclusions. Science doesn’t need any such thing.
The Great Secret of Science, the reason scientists more often than not are the ones who produce science, is that science has all the science. Science begets science. What you learn from rolling balls down an inclined plane allows you to predict the trajectories projectiles, which allows you to discover that motion is parabolic or analyze the periodic motion of pendulums and eventually you, or one your colleagues, develops the calculus, and so on. This doesn’t all happen in one institution because of some general methodology or some universal recipe for getting the truth; it happens because that institution has all the experts. It’s always going to be the guy who understands the science who uses it to create new science because you need to understand the old science to create the new science. Beyond that there’s really nothing more left to explain; we have a complete causal explanation of science. If we wanted a philosophical justification of why we should accept science in the face of philosophical skepticism, then we would need to invoke Bayes (or whatever), but I’m not sure you think we need one of those. You seem to apply Bayes as the hidden cause of scientific success rather than the philosophical justification.