Complicaciones

The first to introduce the term ‘inference to the best explanation’ (in the modern debate at least) was Harman (1965), in an article arguing that IBE provides a more fundamental form of non-demonstrative inference than enumerative induction. He claims that the inference he calls IBE “correspond[s] approximately to what others have called “abduction,” “the method of hypothesis,” “hypothetic inference,” “the method of elimination,” “eliminative inference,” and “theoretical inference”” (88-9). However, since he takes these labels to have “misleading suggestions” (89), he prefers the IBE- terminology.

Specifically, Harman characterises IBE as an inference where one infers the truth of a hypothesis H from the fact that H would explain the available evidence. He then notices that since multiple hypotheses can often explain the same evidence, one needs to somehow judge which is the better explanation. Such judgments he takes to be based “on considerations such as which hypothesis is simpler, more plausible, which explains more, which is less ad hoc, and so forth” (89). Harman does not specify further what he means

by a ‘better explanation’, but he takes it to depend, at least in part, on non-empirical criteria, such as simplicity, scope of explained phenomena and non-ad hocness.

The idea that IBE provides a legitimate form of inference, distinct from enumerative induction, which relies on non-empirical criteria quickly became popular within philosophy. This was motivated by several factors. First, it was supported by Quine’s argument (also used by Harman) that theories are underdetermined by the empirical evidence and that non-empirical reasons therefore play a crucial role in choosing which theories to accept (Quine 1953b, c; cf. Lycan 1985: 159, note 2). Second, IBE also seemed to give a plausible rational reconstruction of the observation that non-empirical criteria play an important role in ‘theory choice’, as highlighted by Kuhn (1977) and others (e.g. Buchdahl 1970). Third, the supposed ubiquity of IBE within science suggested a respectable strategy for naturalistically inclined philosophers to argue for metaphysical conclusions: if scientists use IBE to support theories that go beyond the empirical evidence, and philosophy is in some sense continuous with science, then supporting metaphysical theories through the same form of argument appears more respectable.62 _In

philosophy of science, in particular, this was seen to provide a strong argument for scientific realism, the so-called ‘Ultimate Argument’ or ‘No-Miracles Argument’ associated e.g. with Putnam (1975) and Boyd (1983) (cf. van Frassen 1980: 34-50; Psillos 1999: ch. 3).

I will return to the question of how to understand the notion of ‘the best explanation’ in the next section. First, I want to highlight some refinements to Harman’s original formulation that have been proposed in the recent literature.

62 _{E.g. Armstrong (1983: ch. 5) argues for the existence of laws of nature on the grounds that they provide}

the best explanation for the existence of regularities (cf. van Frassen 1989: 138-142). Saatsi (2017) provides many further examples from metaphysics, philosophy of mathematics and meta-ethics.

In its simplest form, an IBE is supposed to proceed as follows: a scientist is faced with range of competing hypotheses, each of which could potentially explain some set of empirical phenomena. Comparing the quality of the explanation offered by these hypotheses, she then infers the best explanation along the lines of the following schema (e.g. Lycan 1985: 138; Psillos 2002: 614):

(IBE1) D is a set of empirical phenomena (data, facts, observations, etc.). (IBE2) The hypothesis H explains D.

(IBE3) No other available competing hypothesis explains D as well as H. (IBE-C) Therefore, H is (probably) true.

An influential objection to this simple schema is van Fraassen’s (1989: 142-3) “best of a bad lot” problem. The scientist is only comparing the available competing hypotheses, the hypotheses that have actually been formulated so far. Since the range of possible explanations of D is vast, most competitors to H have not yet been formulated and perhaps never will be (146). We know that most possible explanations of D will be false and there does not seem to be any reason to think that the true hypothesis will be among the hypotheses considered so far. Thus, even if being the best explanation is indicative of the truth, we cannot conclude that being the best available explanation is.

Explanationists have usually replied to this objection by restating the conclusion of an IBE as a comparative claim about the available hypotheses. There are a number of possible ways to do this. One is to say that being a good explanation only makes a hypothesis more likely to be true (van Fraassen 1989: 145-6 mentions this possibility), so that the conclusion of an IBE is rather:

(IBE-C’) H is more likely to be true than the available competing hypotheses.

This does not imply that H is more likely to be true than not. A different strategy is instead to claim that being the best available explanation is an indicator of closeness to the truth (Douven 2011: §2), such that the conclusion of an IBE becomes:

(IBE-C’’) H is closer to the truth than the available competing hypotheses.

Again, H can be closer to the truth without being close to it in absolute terms. The two strategies can, furthermore, be combined to yield conclusions such as:

(IBE-C’’’) H is more likely than the competing hypotheses to be the closest to the truth out of the available hypotheses.

Each of these construals of IBE avoids the charge that we are assuming an implausible ability to ensure that the true explanation will be among the potential explanations we can consider at a given time. These responses still allow explanationists to endorse the simple version of IBE in the special cases where we do have good reason to think that the correct hypothesis is among those generated.

A further refinement, proposed by Lipton (2004: 148-63), attempts to give an argument for why we should expect the correct hypothesis to be generated (at least in the long run). It rests on the observation that explanatory reasoning does not just guide the

selection of hypotheses but also informs the generation of available hypotheses. This

hypotheses by considering what could possibly explain an otherwise puzzling phenomenon. Of course, scientists do not try to generate every conceivable hypothesis. Rather, they rely on their background knowledge of what tend to be regarded as good explanations within their field to formulate a limited range of potential explanations which, in light of this background knowledge, seem promising. Building on this observation, Lipton argues that if explanatory considerations can be used to reliably rank the available hypotheses in terms of their likeliness (as van Fraassen grants for the purposes of this objection), we also have a reason to think that they are somewhat reliable in generating new hypotheses (2004: 151ff). After all, Lipton reasons, the hypotheses which make up the background knowledge guiding the generation of new hypotheses were ranked highly by previous applications of IBE. In other words, Lipton’s argument is that repeated applications of a reliable selection criterion, along with subsequent hypothesis-generation informed by the results of this selection, will tend to increase the reliability of the generation step as well. Thus, in the long run at least, we have good reason to assume that IBE will guide us towards true hypotheses.

My purpose here is not to endorse Lipton’s argument. For one thing, one may question the premise that generating hypotheses based on background theories which are merely likelier or closer to the truth than potentially very poor competitors, should increase the reliability of the generative process.63 Rather, I want to highlight a few aspects of these refinements to the simple version of IBE which will be relevant to my further discussion.

First, the responses to the “best of a bad lot” objection differ in terms of whether they take being the best explanation as a reason to regard the hypothesis as the likeliest,

63 _{Stanford (2006) argues, based on case studies, that we have empirical reasons to think that scientists often}

or the otherwise closest to the truth (compared to the available competitors). What they have in common is that the fact that H is the best available explanation does not always provide reason for regarding H as true, but rather for regarding it as having some truth- related property such as being more likely or closer to the truth. Since the objections I will discuss below are unaffected by these distinctions I will, for ease of exposition, often not distinguish them carefully in the following. When I talk of explanatory reasoning providing reasons for the truth of a hypothesis or being a reliable guide to the truth, this should be read as also covering these other truth-related properties.

Second, the above refinements naturally lead explanationists to the claim that being a better explanation can serve as a guide to evaluate any given hypothesis in terms of its likeliness or truth-closeness, rather than merely the best explanation. For one thing, the comparative conclusions (IBE-C’)-(IBE-C’’’) are supposed to be justified independently of what the set of competing hypotheses are. Suppose that out of a given set we remove the best explanation. Then, the second-best explanation will be the best explanation in this new, smaller set and thus the most likely/closest to the truth in the new set (though of course no more likely/close to the truth than the explanation which was removed from the original set). This can be repeated until we have ranked all hypotheses from the original set. Besides, it seems a natural extension of IBE to say that, just as the best explanation is the likeliest (or closest to the truth), the second-best explanation is the second-likeliest, and so on. For these reasons, I shall interpret explanationism not just as committed to (some form) of IBE being correct, but to the more general view that the ‘quality’ of an explanation provides some reasons for its truth.

Finally, as Lipton’s proposal highlights, explanatory reasoning can play a role in both the selection and generation of hypotheses. While most discussions of IBE focus on the former, similar questions arise about the reliability of generating hypotheses through

explanatory reasoning. Although I shall focus on hypothesis selection in this chapter, the Peircean view can equally be applied to account for generative uses of explanatory reasoning.64