[A] large literature has focused on what is frequently termed 'aleatory uncertainty' due to the fundamental indeterminacy or randomness in the world, often couched in terms of luck or chance. This generally relates to future events, which we can't know for certain. This form of uncertainty is an essential part of the assessment, communication and management of both quantifiable and unquantifiable future risks, and prominent examples include uncertain economic forecasts, climate change models and actuarial survival curves.
By contrast, our focus in this paper is uncertainties about facts, numbers and science due to limited knowledge or ignorance—so-called epistemic uncertainty. Epistemic uncertainty generally, but not always, concerns past or present phenomena that we currently don't know but could, at least in theory, know or establish.
By contrast, our focus in this paper is uncertainties about facts, numbers and science due to limited knowledge or ignorance—so-called epistemic uncertainty. Epistemic uncertainty generally, but not always, concerns past or present phenomena that we currently don't know but could, at least in theory, know or establish.
The distinction is of interest to philosophers, psychologists, economists, and statisticians. But it is a little hard to pin down with the definition in the article. Aleatory uncertainty applies on the quantum mechanical level, but is it true that "in theory" predictions like weather and life span cannot be certain? Chaos theory shows that the lack of perfect knowledge about initial conditions of nonlinear systems makes long-term predictions very uncertain, but is it theoretically impossible to have perfect knowledge? The card drawn from a well-shuffled deck is a matter of luck, but if we knew enough about the shuffle, couldn't we know the card that is drawn? Thus, I am not so sure that the distinction is between (1) "fundamental ... randomness in the world" and (2) ignorance that could be remedied "in theory."
Could the distinction be between (1) instances of a phenomenon that has variable outcomes at the level of our existing knowledge of the world and (2) a single instance of a phenomenon that we do not regard as the outcome of a random process or that already has occurred, so that the randomness is gone? The next outcome of rolling a die (an alea in Latin) is always uncertain (unless I change the experimental setup to precisely fix the conditions of the roll), 1/ but whether the last roll produced a 1 is only uncertain to the extent that I cannot trust my vision or memory. I could reduce the latter, epistemic uncertainty by improving my system of making observations. For example, I could have several keen and truthful observers watch the toss, or I could film it and study the recording thoroughly. From this perspective, the frequency and propensity conceptions of probability concern aleatory uncertainty, and the subjective and logical conceptions traffic in both aleatory and epistemic uncertainty.
When it comes to the courtroom, epistemic uncertainty is usually in the forefront, and I may get to that example at a later date. For now, I'll just note that, regardless of whether the distinction offered above between aleatory and epistemic uncertainty is philosophically rigorous, people's attitudes toward aleatory and epistemic risk defined in this way do seem to be somewhat different. 2/
NOTES
- Cf. P. Diaconis, S. Holmes & R. Montgomery, Dynamical Bias in the Coin Toss, 49(2) SIAM Rev. 211-235 (2007), http://epubs.siam.org/doi/abs/10.1137/S0036144504446436?journalCode=siread
- Gülden Ülkümen, Craig R. Fox & B. F. Malle, Two Dimensions of Subjective Uncertainty: Clues from Natural Language, 145(10) Journal of Experimental Psychology: General, 1280-1297. http://dx.doi.org/10.1037/xge0000202; Craig R. Fox & Gülden Ülkümen, Distinguishing Two Dimensions of Uncertainty, in Perspectives on Thinking, Judging, and Decision Making (Brun, W., Keren, G., Kirkebøen, G., & Montgomery, H. eds. 2011).
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