Aleatoric uncertainty, aka statistical uncertainty, which is unknowns that differ each time we run the same experiment. For an example of simulating the take-off of an airplane, even if we could exactly control the wind speeds along the run way, if we let 10 planes of the same make start their trajectories would still differ due to fabrication differences. Similarly, if all we knew is that the average wind speed is the same, letting the same plane start 10 times would still yield different trajectories because we do not know the exact wind speed at every point of the runway, only its average. Aleatoric uncertainties are therefore something an experimenter cannot do anything about: they exist, and they cannot be suppressed by more accurate measurements. Epistemic uncertainty, aka systematic uncertainty, which is due to things we could in principle know but don’t in practice. This may be because we have not measured a quantity sufficiently accurately, or because our model neglects certain effects, or because particular data are deliberately hidden.
Could we say that aleatoric uncertainty would be akin to not knowing whether a coin will land heads or tails (but we know the odds are 1:1) and epistemic uncertainty would be akin to not knowing the odds of the coin at all?
Aleatoric uncertainty is basically seeing randomness as a property of the universe, rather than a property of minds. Unless you verge into quantum territory, basically all randomness is actually epistemic uncertainty, and even if you verge into quantum territory, you can view quantum randomness as epistemic uncertainty.
Bayesians are comfortable viewing all uncertainties as epistemic. Non-Bayesians aren’t, and all of the people I know who do professional decision-making under uncertainty dread someone even mentioning aleatoric uncertainty because it’s a dead giveaway that the person mentioning it isn’t Bayesian, and thus a long, unproductive philosophical discussion may be necessary before they can get anywhere.
The Wikipedia definition makes it sound more like aleatoric uncertainty is not knowing whether it will land heads or tails (because it will do something different each time), and epistemic uncertainty is not having a camera accurate enough to see whether it has landed heads or tails.
I realize that LW collectively doesn’t like unreferenced definitions, but in this case maybe it’s OK… a friend of mine whose PhD is in decision theory explained aleatory uncertainty to me as the uncertainty of chance with known parameters: if you roll a normal six-sided die, you know it’s going to come up with a value in the range 1-6, but you don’t know what it will be. There’s no chance it will come up 7. Epistemic uncertainty is the uncertainty of chance with unknown parameters: there may not be enough data to know the bounds of an event, or it may have such large and random bounds that trying to place them is not very meaningful.
Wikipedia says:
http://en.wikipedia.org/wiki/Uncertainty_quantification
Could we say that aleatoric uncertainty would be akin to not knowing whether a coin will land heads or tails (but we know the odds are 1:1) and epistemic uncertainty would be akin to not knowing the odds of the coin at all?
Aleatoric uncertainty is basically seeing randomness as a property of the universe, rather than a property of minds. Unless you verge into quantum territory, basically all randomness is actually epistemic uncertainty, and even if you verge into quantum territory, you can view quantum randomness as epistemic uncertainty.
Bayesians are comfortable viewing all uncertainties as epistemic. Non-Bayesians aren’t, and all of the people I know who do professional decision-making under uncertainty dread someone even mentioning aleatoric uncertainty because it’s a dead giveaway that the person mentioning it isn’t Bayesian, and thus a long, unproductive philosophical discussion may be necessary before they can get anywhere.
The Wikipedia definition makes it sound more like aleatoric uncertainty is not knowing whether it will land heads or tails (because it will do something different each time), and epistemic uncertainty is not having a camera accurate enough to see whether it has landed heads or tails.
I realize that LW collectively doesn’t like unreferenced definitions, but in this case maybe it’s OK… a friend of mine whose PhD is in decision theory explained aleatory uncertainty to me as the uncertainty of chance with known parameters: if you roll a normal six-sided die, you know it’s going to come up with a value in the range 1-6, but you don’t know what it will be. There’s no chance it will come up 7. Epistemic uncertainty is the uncertainty of chance with unknown parameters: there may not be enough data to know the bounds of an event, or it may have such large and random bounds that trying to place them is not very meaningful.
You could probably mad words any two buzz words together though. How about quantum rationality?