Abstract
In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” (IBE) and “Explaining for the Best Inference” (EBI), respectively. We also provide some initial support for EBI and identify promising directions for future research.
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Notes
For purposes of this paper, we treat “accurate,” “true,” and “right” explanations as roughly interchangeable. This begs certain questions—particularly as pertains to the debate about scientific realism and anti-realism—but these issues are not directly relevant to the distinction between IBE and EBI.
This use of “EBI” is distinct from the use expounded in Persson (2007).
This point was made to us by an anonymous reviewer.
Even on our expanded notion, EBI and IBE are not quite exhaustive of the way explanations could be of cognitive value—it is possible that the product of explanations could be valuable for some reason aside from their truth, while also not as a function of the explanatory reasoning process that led to them. For instance, one could believe that having any explanation, regardless of its truth, is what’s important. This view combines the focus on explanations from IBE with the tolerance for inaccuracy from EBI.
On the former account, IBE helps us by pointing us to the laws and initial and boundary conditions governing a system, and on the latter account, it helps us by pointing to assumptions and argument patterns that would unify our overall knowledge store. (For a review of those accounts, see Woodward 2014).
Mechanists rarely claim that mechanisms account for all causal relations, though.
To be clear, this taxonomy of causal accounts is not meant to be exhaustive; as the details of the accounts are not relevant for our analysis, a comprehensive review is unnecessary.
It is worth pointing out that the remarks about the unimportance of the act of explaining extend to any theory that takes the explanation as the only valuable product of the explaining act. In other words, everything we have said about IBE in the narrow sense applies to the broader class of explanation-acquisition discussed in Sect. 1.
Achinstein and Wilkenfeld’s accounts are still open to the possibility that the best explanations are the best as a result of having some particular explanatory virtues (on Wilkenfeld’s 2013, representation-centric approach, natural candidates would be the accuracy and fecundity of the representational content of the explanation). Thus, their accounts do not preclude evaluating explanations in terms of their more traditional virtues, but do allow for an additional class of considerations.
Of course, hitting on false explanations won’t always be beneficial; conditions that have a net epistemic benefit when explanations are false may be rare, even if they are important in providing evidence for EBI. For instance, we know that in some cases explaining can actually impair learning, and that this appears to be in part because people perseverate in making judgments on the basis of false explanations. See for example Williams et al. (2013) on how prompts to explain in uncooperative worlds can actually impede learning.
One anonymous reviewer pointed out to us that several thinkers (e.g., Papineau 1993 Sect. 5.11) have argued that this sort of rule circularity is perfectly reasonable. If this is right, then there is no problem for EBI either, and so much the better. However, our own inclination is that such seemingly question-begging responses should be adopted only as a last resort (though perhaps “last resort” accurately reflects our present place in the dialectic).
Briefly: such justification cannot advert solely to the a priori, since our conclusion has to do with the actual contingent arrangement of the world, but it cannot be based on prior experience, since the validity of extending lessons learned from prior experience to unseen cases is the very thing in question.
We thank an anonymous reviewer for drawing our attention to this comparison.
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Acknowledgments
We would like to thank the University of California, Berkeley, the John Templeton Foundation Varieties of Understanding project, the McDonnell Scholar Award, and NSF Grant DRL-1056712 (to Tania Lombrozo) for support during the writing of this paper.
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Wilkenfeld, D.A., Lombrozo, T. Inference to the Best Explanation (IBE) Versus Explaining for the Best Inference (EBI). Sci & Educ 24, 1059–1077 (2015). https://doi.org/10.1007/s11191-015-9784-4
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DOI: https://doi.org/10.1007/s11191-015-9784-4