Epistemic: uncertainty due to gaps in knowledge; Aleatory: uncertainty due to variability or randomness [like throwing dice or flipping a coin] Differentiating between the type of risk is important because they are mitigated in completely different ways. Epistemic risk is the easier type to deal with because it is something that can be overcome ... ses are discussed. While many sources of uncertainty may exist, they are generally categorized as either aleatory or epistemic. Uncertainties are characterized as epistemic, if the modeler sees a possibility to reduce them by gathering more data or by refining models. Uncertainties are categorized as aleatory if Epistemic uncertainty is the subjective Bayesian interpretation, the kind of uncertainty that can be reduced by learning. Aleatory uncertainty is the objective Frequentist stuff, the kind of uncertainty you accept and work around. Philosophical disagreements often have interesting implications. These forms of uncertainty can have insidious consequences for modeling if not properly identified and accounted for. In particular, confusion between aleatoric and epistemic uncertainty can lead to a fundamentally incorrect model being inappropriately fit to data such that the model seems to be correct. Aleatory vs. Epistemic Uncertainty – Commentary and Observations • Distinction depends on frame of reference (“model of the world”). • Example: Weld crack propagation depends on local material conditions (e.g., Cu content, flaw geometry). – Aleatory model: conditions have a statistical distribution. Epistemic uncertainty targets single cases (or statements), while aleatory uncertainty focuses on a range of possible outcomes that can derive from the repetition of an event. Robinson et al. (2006) as cited in Fox and Ülkümen (2011) [7] , carried out an experiment asking children to predict the color of a building block drawn from a bag containing only two colors. 5 Aleatory Variability and Epistemic Uncertainty Aleatory variability and epistemic uncertainty are terms used in seismic hazard analysis that are not commonly used in other fields, but the concepts are well known. Aleatory variability is the natural randomness in a process. For discrete variables, the "Aleatory" and "Epistemic" Uncertainties Terminology/concepts built into multiple documents, e.g., • ASME/ANS PRA Standard • Regulatory Guides 1 200 aleatory uncertainty: the uncertainty inherent in a nondeterministic (s tochastic, random) phenomenon… is reflected by modeling the – 1.200 phenomenon in terms of a probabilistic – 1.174 also can be distinguished by distinct coping strategies: epistemic uncertainty can be reduced by searching for patterns or causality, whereas aleatory uncertainty cannot be reduced but can be managed by determining the relative propensities of events (Feature 5). Finally, epistemic and aleatory uncertainty have distinct markers in natural language. Aleatory uncertainty and the resulting risk is modeled with a Probability Distribution Function. This PDF describes all the possible values the process can take and the probability of each value. For a single toss of a coin, there is a 50% probability it will be either heads or tails.
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