Scientific Realism First published Wed Apr 27, 2011

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Scientific Realism

First published Wed Apr 27, 2011

Debates about scientific realism are centrally connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude towards the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts.

  • 1. What is Scientific Realism?

    • 1.1 Epistemic Achievements versus Epistemic Aims

    • 1.2 The Three Dimensions of Realist Commitment

    • 1.3 Qualifications and Variations

  • 2. Considerations in Favour of Scientific Realism (and Responses)

    • 2.1 The Miracle Argument

    • 2.2 Corroboration

    • 2.3 Selective Optimism/Scepticism

  • 3. Considerations Against Scientific Realism (and Responses)

    • 3.1 The Underdetermination of Theory by Data

    • 3.2 Scepticism about Inference to the Best Explanation

    • 3.3 The Pessimistic Induction

    • 3.4 Scepticism about Approximate Truth

  • 4. Antirealism: Foils for Scientific Realism

    • 4.1 Empiricism

    • 4.2 Historicism

    • 4.3 Social Constructivism

    • 4.4 Feminist Approaches

    • 4.5 Pragmatism, Quietism, and Dialectical Paralysis

  • Bibliography

  • Academic Tools

  • Other Internet Resources

  • Related Entries

1. What is Scientific Realism?

1.1 Epistemic Achievements versus Epistemic Aims

It is perhaps only a slight exaggeration to say that scientific realism is characterized differently by every author who discusses it, and this presents a challenge to anyone hoping to learn what it is. Fortunately, underlying the many idiosyncratic qualifications and variants of the position, there exists a common core of ideas, typified by an epistemically positive attitude towards the outputs of scientific investigation, regarding both observable and unobservable aspects of the world. The distinction here between the observable and the unobservable reflects human sensory capabilities: the observable is that which can, under favourable conditions, be perceived using the unaided senses (for example, planets and platypuses); the unobservable is that which cannot be detected this way (for example, proteins and protons). This is to privilege vision merely for terminological convenience, and differs from scientific conceptions of observability, which generally extend to things that are detectable using instruments (Shapere 1982). The distinction itself has been problematized (Maxwell 1962, Churchland 1985, Musgrave 1985, Dicken & Lipton 2006), but if it is problematic, this is arguably a concern primarily for certain forms of antirealism, which adopt an epistemically positive attitude only with respect to the observable. It is not ultimately a concern for scientific realism, which does not discriminate epistemically between observables and unobservables per se.

Before considering the nuances of what scientific realism entails, it is useful to distinguish between two different kinds of definition in this context. Most commonly, the position is described in terms of the epistemic achievements constituted by scientific theories (and models—this qualification will be taken as given henceforth). On this approach, scientific realism is a position concerning the actual epistemic status of theories (or some components thereof), and this is described in a number of ways. For example, most define scientific realism in terms of the truth or approximate truth of scientific theories or certain aspects of theories. Some define it in terms of the successful reference of theoretical terms to things in the world, both observable and unobservable. (A note about the literature: ‘theoretical term’, prior to the 1980s, was standardly used to denote terms for unobservables, but will be used here to refer to any scientific term, which is now the more common usage.) Others define scientific realism not in terms of truth or reference, but in terms of belief in the ontology of scientific theories. What all of these approaches have in common is a commitment to the idea that our best theories have a certain epistemic status: they yield knowledge of aspects of the world, including unobservable aspects. (For definitions along these lines, see Smart 1963, Boyd 1983, Devitt 1991, Kukla 1998, Niiniluoto 1999, Psillos 1999, and Chakravartty 2007a.)

Another way to think about scientific realism is in terms of the epistemic aims of scientific inquiry (van Fraassen 1980, p. 8, Lyons 2005). That is, some think of the position in terms of what science aims to do: the scientific realist holds that science aims to produce true descriptions of things in the world (or approximately true descriptions, or ones whose central terms successfully refer, and so on). There is a weak implication here to the effect that if science aims at truth and scientific practice is at all successful, the characterization of scientific realism in terms of aim may then entail some form of characterization in terms of achievement. But this is not a strict implication, since defining scientific realism in terms of aiming at truth does not, strictly speaking, suggest anything about the success of scientific practice in this regard. For this reason, some take the aspirational characterization of scientific realism to be too weak (Kitcher 1993, p. 150, Devitt 2005, n. 10, Chakravartty 2007b, p. 197)—it is compatible with the sciences never actually achieving, and even the impossibility of their achieving, their aim as conceived on this view of scientific realism. Most scientific realists commit to something more in terms of achievement, and this is assumed in what follows.

1.2 The Three Dimensions of Realist Commitment

The description of scientific realism as a positive epistemic attitude towards theories, including parts putatively concerning the unobservable, is a kind of shorthand for more precise commitments (Kukla 1998, ch. 1, Niiniluoto 1999, ch. 1, Psillos 1999, Introduction, Chakravartty 2007a, ch. 1). Traditionally, realism more generally is associated with any position that endorses belief in the reality of something. Thus, one might be a realist about one's perceptions of tables and chairs (sense datum realism), or about tables and chairs themselves (external world realism), or about mathematical entities such as numbers and sets (mathematical realism), and so on. Scientific realism is a realism about whatever is described by our best scientific theories—from this point on, ‘realism’ here denotes scientific realism. But what, more precisely, is that? In order to be clear about what realism in the context of the sciences amounts to, and to differentiate it from some important antirealist alternatives, it is useful to understand it in terms of three dimensions: a metaphysical (or ontological) dimension; a semantic dimension; and an epistemological dimension.

Metaphysically, realism is committed to the mind-independent existence of the world investigated by the sciences. This idea is best clarified in contrast with positions that deny it. For instance, it is denied by any position that falls under the traditional heading of ‘idealism’, including some forms of phenomenology, according to which there is no world external to and thus independent of the mind. This sort of idealism, though historically important, is rarely encountered in contemporary philosophy of science, however. More common rejections of mind-independence stem from neo-Kantian views of the nature of scientific knowledge, which deny that the world of our experience is mind-independent, even if (in some cases) these positions accept that the world in itself does not depend on the existence of minds. The contention here is that the world investigated by the sciences—as distinct from “the world in itself” (assuming this to be a coherent distinction)—is in some sense dependent on the ideas one brings to scientific investigation, which may include, for example, theoretical assumptions and perceptual training; this proposal is detailed further in section 4. It is important to note in this connection that human convention in scientific taxonomy is compatible with mind-independence. For example, though Psillos (1999, p. xix) ties realism to a ‘mind-independent natural-kind structure’ of the world, Chakravartty (2007a, ch. 6) argues that mind-independent properties are often conventionally grouped into kinds (see also Boyd 1991 and Humphreys 2004, pp. 22–25, 35–36).

Semantically, realism is committed to a literal interpretation of scientific claims about the world. In common parlance, realists take theoretical statements at “face value”. According to realism, claims about scientific entities, processes, properties, and relations, whether they be observable or unobservable, should be construed literally as having truth values, whether true or false. This semantic commitment contrasts primarily with those of so-called instrumentalist epistemologies of science, which interpret descriptions of unobservables simply as instruments for the prediction of observable phenomena, or for systematizing observation reports. Traditionally, instrumentalism holds that claims about unobservable things have no literal meaning at all (though the term is often used more liberally in connection with some antirealist positions today). Some antirealists contend that claims involving unobservables should not be interpreted literally, but as elliptical for corresponding claims about observables. These positions are described in more detail in section 4.

Epistemologically, realism is committed to the idea that theoretical claims (interpreted literally as describing a mind-independent reality) constitute knowledge of the world. This contrasts with sceptical positions which, even if they grant the metaphysical and semantic dimensions of realism, doubt that scientific investigation is epistemologically powerful enough to yield such knowledge, or, as in the case of some antirealist positions, insist that it is only powerful enough to yield knowledge regarding observables. The epistemological dimension of realism, though shared by realists generally, is sometimes described more specifically in contrary ways. For example, while many realists subscribe to the truth (or approximate truth) of theories understood in terms of some version of the correspondence theory of truth (as suggested by Fine 1986 and contested by Ellis 1988), some prefer deflationary accounts of truth (including Giere 1988, p. 82, Devitt 2005, and Leeds 2007). Though most realists marry their position to the successful reference of theoretical terms, including those for unobservable entities, processes, properties, and relations (Boyd 1983, and as described by Laudan 1981), some deny that this is a requirement (Cruse & Papineau 2002, Papineau 2010). Amidst these differences, however, a general recipe for realism is widely shared: our best scientific theories give true or approximately true descriptions of observable and unobservable aspects of a mind-independent world.

1.3 Qualifications and Variations

The general recipe for realism just described is accurate so far as it goes, but still falls short of the degree of precision most realists offer. The two main sources of imprecision here are found in the general recipe itself, which makes reference to the idea of ‘our best scientific theories’ and the notion of ‘approximate truth’. The motivation for these qualifications is perhaps clear. If one is to defend a positive epistemic attitude regarding scientific theories, it is rational to do so not merely in connection with any theory (especially when one considers that, over the long history of the sciences up to the present, some theories were not or are not especially successful), but rather with respect to theories that would appear, prima facie, to merit such a defence, viz. our best theories. And it is widely held, not least by realists, that even many of our best scientific theories are likely false, strictly speaking, hence the importance of the notion that theories may be “close to” the truth (that is, approximately true) even though they are false. The challenge of making these qualifications more precise, however, is significant, and has generated much discussion.

Consider first the issue of how best to identify those theories that realists should be realists about. A general disclaimer is in order here: realists are generally fallibilists, holding that realism is appropriate in connection with our best theories even though they likely cannot be proven with absolute certainty; some of our best theories could conceivably turn out to be significantly mistaken, but realists maintain that, granting this possibility, there are grounds for realism nonetheless. These grounds are bolstered by restricting the domain of theories suitable for realist commitment to those that are sufficiently mature and non-ad hoc (Worrall 1989, pp. 153-154, Psillos 1999, pp. 105–108). Maturity may be thought of in terms of the well established nature of the field in which a theory is developed, or the duration of time a theory has survived, or its survival in the face of significant testing; and the condition of being non-ad hoc is intended to guard against theories that are “cooked up” (that is, posited merely) in order to account for some known observations in the absence of rigorous testing. On these construals, however, both the notion of maturity and the notion of being non-ad hoc are admittedly vague. One strategy for adding precision here is to attribute these qualities to theories that make successful, novel predictions. The ability of a theory to do this, it is commonly argued, marks it as genuinely empirically successful, and the sort of theory to which realists should be more inclined to commit (Musgrave 1988, Lipton 1990, Leplin 1997, White 2003, Hitchcock & Sober 2004, Barnes 2008; for a dissenting view, see Harker 2008).

The idea that with the development of the sciences over time, theories are converging on (“moving in the direction of”, “getting closer to”) the truth, is a common theme in realist discussions of theory change (for example, Hardin & Rosenberg 1982 and Putnam 1982). Talk of approximate truth is often invoked in this context, and has produced a significant amount of often highly technical work, conceptualizing the approximation of truth as something that can be quantified, such that judgments of relative approximate truth (of one proposition or theory in comparison to another) can be formalized and given precise definitions. This work provides one possible means by which to consider the convergentist claim that theories can be viewed as increasingly approximately true over time, and this possibility is further considered in section 3.4.

A final and especially important qualification to the general recipe for realism described above comes in the form of a number of variations. These species of generic realism can be viewed as falling into three families or camps: explanationist realism; entity realism; and structural realism. There is a shared principle of speciation here, in that all three approaches are attempts to identify more specifically the component parts of scientific theories that are most worthy of epistemic commitment. Explanationism recommends realist commitment with respect to those parts of our best theories—regarding (unobservable) entities, processes, laws, etc.—that are in some sense indispensible or otherwise important to explaining their empirical success—for instance, components of theories that are crucial in order to derive successful, novel predictions. Entity realism is the view that under conditions in which one can demonstrate impressive causal knowledge of a putative (unobservable) entity, such as knowledge that facilitates the manipulation of the entity and its use so as to intervene in other phenomena, one has good reason for realism regarding it. Structural realism is the view that one should be a realist, not in connection with descriptions of the natures of things (like unobservable entities and processes) found in our best theories, but rather with respect to their structure. All three of these positions adopt a strategy of selectivity, and this and the positions themselves are considered further in section 2.3.

2. Considerations in Favour of Scientific Realism (and Responses)

2.1 The Miracle Argument

The most powerful intuition motivating realism is an old idea, commonly referred to in recent discussions as the ‘miracle argument’ or ‘no-miracles argument’, after Putnam's (1975, p. 73) claim that realism ‘is the only philosophy that doesn't make the success of science a miracle’. The argument begins with the widely accepted premise that our best theories are extraordinarily successful: they facilitate empirical predictions, retrodictions, and explanations of the subject matters of scientific investigation, often marked by astounding accuracy and intricate causal manipulations of the relevant phenomena. What explains this success? One explanation, favoured by realists, is that our best theories are true (or approximately true, or correctly describe a mind-independent world of entities, properties, laws, structures, or what have you). Indeed, if these theories were far from the truth, so the argument goes, the fact that they are so successful would be miraculous. And given the choice between a straightforward explanation of success and a miraculous explanation, clearly one should prefer the non-miraculous explanation, viz. that our best theories are approximately true (etc.). (For elaborations of the miracle argument, see Brown 1982, Boyd 1989, Lipton 1994, Psillos 1999, ch. 4, Barnes 2002, Lyons 2003, Busch 2008, and Frost-Arnold 2010.)

Though intuitively powerful, the miracle argument is contestable in a number of ways. One sceptical response is to question the very need for an explanation of the success of science in the first place. For example, van Fraassen (1980, p. 40; see also Wray 2007, 2010) suggests that successful theories are analogous to well-adapted organisms—since only successful theories (organisms) survive, it is hardly surprising that our theories are successful, and therefore, there is no demand here for an explanation of success. It is not entirely clear, however, whether the evolutionary analogy is sufficient to dissolve the intuition behind the miracle argument. One might wonder, for instance, why a particular theory is successful (as opposed to why theories in general are successful), and the explanation sought may turn on specific features of the theory itself, including its descriptions of unobservables. Whether such explanations need be true, though, is a matter of debate. While most theories of explanation require that the explanans be true, pragmatic theories of explanation do not (van Fraassen 1980, ch. 5). More generally, any epistemology of science that does not accept one or more of the three dimensions of realism—commitment to a mind-independent world, literal semantics, and epistemic access to unobservables—will thereby present a putative reason for resisting the miracle argument; these positions are considered in section 4.

Some authors contend that the miracle argument itself is an instance of fallacious reasoning called the base rate fallacy (Howson 2000, ch. 3, Lipton 2004, pp. 196–198, Magnus & Calendar 2004). Consider the following illustration. There is a test for a disease for which the rate of false negatives (negative results in cases where the disease is present) is zero, and the rate of false positives (positive results in cases where the disease is absent) is one in ten (that is, disease-free individuals test positive 10% of the time). If one tests positive, what are the chances that one has the disease? It would be a mistake to conclude that, based on the rate of false positives, the probability is 90%, for the actual probability depends on some further, crucial information: the base rate of the disease in the population (the proportion of people having it). The lower the incidence of the disease at large, the lower the probability that a positive result signals the presence of the disease. By analogy, using the success of a scientific theory as an indicator of its approximate truth (assuming a low rate of false positives—cases in which theories far from the truth are nonetheless successful) is arguably, likewise, an instance of the base rate fallacy. The success of a theory does not by itself suggest that it is likely approximately true, and since there is no independent way of knowing the base rate of approximately true theories, the chances of it being approximately true cannot be assessed. Worrall (2009) maintains that these contentions are ineffective against the miracle argument because they depend crucially on a misleading formalization of it in terms of probabilities.

2.2 Corroboration

One motivation for realism in connection with at least some unobservables described by scientific theories comes by way of “corroboration”. If an unobservable entity or property is putatively capable of being detected by means of a scientific instrument or experiment, one might think that this could form the basis of a defeasible argument for realism regarding it. If, however, that same entity or property is putatively capable of being detected by not just one, but rather two or more different means of detection—forms of detection that are distinct with respect to the apparatuses they employ and the causal mechanisms and processes they are described as exploiting in the course of detection—this may serve as the basis of a significantly enhanced argument for realism. Hacking (1983, p. 201; see also Hacking 1985, pp. 146–147) gives the example of dense bodies in red blood platelets that can be detected using different forms of microscopy. Different techniques of detection, such as those employed in light microscopy and transmission electron microscopy, make use of very different sorts of physical processes, and these operations are described theoretically in terms of correspondingly different causal mechanisms. (For similar examples, see Salmon 1984, pp. 217–219, and Franklin 1986, pp. 166–168, 1990, pp. 103–115.)

The argument from corroboration thus runs as follows. The fact that one and the same thing is apparently revealed by distinct modes of detection suggests that it would be an extraordinary coincidence if the supposed target of these revelations did not, in fact, exist. The greater the extent to which detections can be corroborated by different means, the stronger the argument for realism in connection with their putative target. The argument here can be viewed as resting on an intuition similar to that underlying the miracle argument: realism based on apparent detection may be only so compelling, but if different, theoretically independent means of detection produce the same result, suggesting the existence of one and the same unobservable, then realism provides a good explanation of the consilient evidence, in contrast with the arguably miraculous state of affairs in which theoretically independent techniques produce the same result in the absence of a shared target. The idea that techniques of (putative) detection are often constructed or calibrated precisely with the intention of reproducing the outputs of others, however, may stand against the argument from corroboration. Additionally, van Fraassen (1985, pp. 297–298) argues that scientific explanations of evidential consilience may be accepted without the explanations themselves being understood as true, which once again raises questions about the nature of scientific explanation.

2.3 Selective Optimism/Scepticism

In section 1.3, the notion of selectivity was introduced as a general strategy for maximizing the plausibility of realism, particularly with respect to scientific unobservables. This strategy is adopted in part to square realism with the widely accepted view that most if not all of even our best theories are false, strictly speaking. If, nevertheless, there are aspects of these theories that are true (or close to the truth) and one is able to identify these aspects, one might then plausibly cast one's realism in terms of an epistemically positive attitude towards those aspects of theories that are most worthy of epistemic commitment. The most important variants of realism to implement this strategy are explanationism, entity realism, and structural realism. (For related work pertaining to the notion of selectivity more generally, see Miller 1987, chs. 8–10, Fine 1990, Jones 1991, and Musgrave 1992.)

Explanationists hold that a realist attitude can be justified in connection with unobservables described by our best theories precisely when appealing to those unobservables is indispensible or otherwise important to explaining why these theories are successful. For example, if one takes successful novel prediction to be a hallmark of theories worthy of realist commitment generally, then explanationism suggests that, more specifically, those aspects of the theory that are essential to the derivation of novel predictions are the parts of the theory most worthy of realist commitment. In this vein, Kitcher (1993, pp. 140–149) draws a distinction between the ‘presuppositional posits’ or ‘idle parts’ of theories, and the ‘working posits’ to which realists should commit. Psillos (1999, chs. 5–6) argues that realism can be defended by demonstrating that the success of past theories did not depend on their false components: ‘it is enough to show that the theoretical laws and mechanisms which generated the successes of past theories have been retained in our current scientific image’ (p. 108). The immediate challenge to explanationism is to furnish a method with which to identify precisely those aspects of theories that are required for their success, in a way that is objective or principled enough to withstand the charge that realists are merely rationalizing

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