I don’t know if you meant “people” in a generalized sense, meaning “every rational probability user”, or more in the sense of “the common wo/men”. If in the first sense, there are different principles you can use that depends on what you already know to be true: the indifference principle, Laplace’s succession rule, minimum entropy, group invariance, Solomonoff induction, etc., and possibly even more. It should be an active area of research in probability theory (if it’s not, shame on you, researchers!). As a general principle, the ideal prior is the most inclusive prior that is not ruled out by the information (you consider true). Even after that, you want to be very careful not to let any proposition to be 0 or 1, because outside of mathematical idealization, everybody is imperfect and has access only to imperfect information. If, otherwise, you meant “the common person in the street”, then I can only say that I see used overwhelmingly the bias of authority and generalization from one example. After all, “construct prior” just means “decide what is true and to what degree”. ”Constructing better prior” amounts to not using information we don’t have, avoiding the mind projection fallacy, and using the information we have, constructing an informed model of the world. It is indeed worth trying to figure out how to be better at those things, but not as much as in idealized setting. Since we have access only to inconsistent information, it is sometimes the case that we must completely discard what we held to be true, a case that doesn’t happen in pure probability theory.
I don’t know if you meant “people” in a generalized sense, meaning “every rational probability user”, or more in the sense of “the common wo/men”.
If in the first sense, there are different principles you can use that depends on what you already know to be true: the indifference principle, Laplace’s succession rule, minimum entropy, group invariance, Solomonoff induction, etc., and possibly even more. It should be an active area of research in probability theory (if it’s not, shame on you, researchers!). As a general principle, the ideal prior is the most inclusive prior that is not ruled out by the information (you consider true). Even after that, you want to be very careful not to let any proposition to be 0 or 1, because outside of mathematical idealization, everybody is imperfect and has access only to imperfect information.
If, otherwise, you meant “the common person in the street”, then I can only say that I see used overwhelmingly the bias of authority and generalization from one example. After all, “construct prior” just means “decide what is true and to what degree”.
”Constructing better prior” amounts to not using information we don’t have, avoiding the mind projection fallacy, and using the information we have, constructing an informed model of the world. It is indeed worth trying to figure out how to be better at those things, but not as much as in idealized setting. Since we have access only to inconsistent information, it is sometimes the case that we must completely discard what we held to be true, a case that doesn’t happen in pure probability theory.