There are also things which are bad to learn for epistemic rationality reasons.
Sampling bias is an obvious case of this. Suppose you want to learn about the demographics of city X. Maybe half of the Xians have black hair, and the other half have blue hair. If you are introduced to 5 blue-haired Xians but no black-haired Xians, you might infer that all or most Xians have blue hair. That is a pretty obvious case of sampling bias. I guess what I’m trying to get at is that learning a few true facts (Xian1 has blue hair, Xian2 has blue hair, … , Xian5 has blue hair) may lead you to make incorrect inferences later on (all Xians have blue hair).
The example you give, of debating being harmful to epistemic rationality, seems comparable to sampling bias, because you only hear good arguments for one side of the debate. So you learn a bunch of correct facts supporting position X, but no facts supporting position Y. Thus, your knowledge has increased (seemingly helpful to epistemic rationality), but leads to incorrect inferences (actually bad for epistemic rationality).
There’s also the question of what to learn. You could spend all day reading celebrity magazines, and this would give you an increase in knowledge, but reading a math textbook would probably give you a bigger increase in knowledge (not to mention an increase in skills). (Two length-n sets of facts can, of course, increase your knowledge a different amount. Information theory!)
If you are introduced to 5 blue-haired Xians but no black-haired Xians, you might infer that all or most Xians have blue hair. That is a pretty obvious case of sampling bias.
If a-priori you had no reason to expect that the population was dominantly blue-haired then you should begin to suspect some alternative hypothesis, like your sampling is biased for some reason, rather than believe everyone is blue haired.
There are also things which are bad to learn for epistemic rationality reasons.
Sampling bias is an obvious case of this. Suppose you want to learn about the demographics of city X. Maybe half of the Xians have black hair, and the other half have blue hair. If you are introduced to 5 blue-haired Xians but no black-haired Xians, you might infer that all or most Xians have blue hair. That is a pretty obvious case of sampling bias. I guess what I’m trying to get at is that learning a few true facts (Xian1 has blue hair, Xian2 has blue hair, … , Xian5 has blue hair) may lead you to make incorrect inferences later on (all Xians have blue hair).
The example you give, of debating being harmful to epistemic rationality, seems comparable to sampling bias, because you only hear good arguments for one side of the debate. So you learn a bunch of correct facts supporting position X, but no facts supporting position Y. Thus, your knowledge has increased (seemingly helpful to epistemic rationality), but leads to incorrect inferences (actually bad for epistemic rationality).
There’s also the question of what to learn. You could spend all day reading celebrity magazines, and this would give you an increase in knowledge, but reading a math textbook would probably give you a bigger increase in knowledge (not to mention an increase in skills). (Two length-n sets of facts can, of course, increase your knowledge a different amount. Information theory!)
If a-priori you had no reason to expect that the population was dominantly blue-haired then you should begin to suspect some alternative hypothesis, like your sampling is biased for some reason, rather than believe everyone is blue haired.