Brad DeLong has a new post up where he gets critical about scientific realism and inference to the best explanation:
Daniel Little: The Case for Realism in the Social Realm:
“The case for scientific realism in the case of physics is a strong one…
The theories… postulate unobservable entities, forces, and properties. These hypotheses… are not individually testable, because we cannot directly observe or measure the properties of the hypothetical entities. But the theories as wholes have a great deal of predictive and descriptive power, and they permit us to explain and predict a wide range of physical phenomena. And the best explanation of the success of these theories is that they are true: that the world consists of entities and forces approximately similar to those hypothesized in physical theory. So realism is an inference to the best explanation…”
“WTF?!” is the only reaction I can have when I read Daniel Little.
Ptolemy’s epicycles are a very good model of planetary motion–albeit not as good as General Relativity. Nobody believes that epicycles are real …
There is something there. But just because your theory is good does not mean that the entities in your theory are “really there”, whatever that might mean…
Although Brad sounds upset, I can’t really see any good reasons why.
In a time when scientific relativism is expanding, it is important to keep up the claim for not reducing science to a pure discursive level. We have to maintain the Enlightenment tradition of thinking of reality as principally independent of our views of it and of the main task of science as studying the structure of this reality. Perhaps the most important contribution a researcher can make is reveal what this reality that is the object of science actually looks like.
Science is made possible by the fact that there are structures that are durable and are independent of our knowledge or beliefs about them. There exists a reality beyond our theories and concepts of it. It is this independent reality that our theories in some way deal with. Contrary to positivism, I would as a critical realist argue that the main task of science is not to detect event-regularities between observed facts. Rather, that task must be conceived as identifying the underlying structure and forces that produce the observed events.
In a truly wonderful essay – chapter three of Error and Inference (Cambridge University Press, 2010, eds. Deborah Mayo and Aris Spanos) – Alan Musgrave gives strong arguments why scientific realism and inference to the best explanation are the best alternatives for explaining what’s going on in the world we live in:
For realists, the name of the scientific game is explaining phenomena, not just saving them. Realists typically invoke ‘inference to the best explanation’ or IBE …
IBE is a pattern of argument that is ubiquitous in science and in everyday life as well. van Fraassen has a homely example:
“I hear scratching in the wall, the patter of little feet at midnight, my cheese disappears – and I infer that a mouse has come to live with me. Not merely that these apparent signs of mousely presence will continue, not merely that all the observable phenomena will be as if there is a mouse, but that there really is a mouse.” (1980: 19-20)
Here, the mouse hypothesis is supposed to be the best explanation of the phenomena, the scratching in the wall, the patter of little feet, and the disappearing cheese.
What exactly is the inference in IBE, what are the premises, and what the conclusion? van Fraassen says “I infer that a mouse has come to live with me”. This suggests that the conclusion is “A mouse has come to live with me” and that the premises are statements about the scratching in the wall, etc. Generally, the premises are the things to be explained (the explanandum) and the conclusion is the thing that does the explaining (the explanans). But this suggestion is odd. Explanations are many and various, and it will be impossible to extract any general pattern of inference taking us from explanandum to explanans. Moreover, it is clear that inferences of this kind cannot be deductively valid ones, in which the truth of the premises guarantees the truth of the conclusion. For the conclusion, the explanans, goes beyond the premises, the explanandum. In the standard deductive model of explanation, we infer the explanandum from the explanans, not the other way around – we do not deduce the explanatory hypothesis from the phenomena, rather we deduce the phenomena from the explanatory hypothesis …
The intellectual ancestor of IBE is Peirce’s abduction, and here we find a different pattern:
The surprising fact, C, is observed.
But if A were true, C would be a matter of course.
Hence, … A is true.
(C. S. Peirce, 1931-58, Vol. 5: 189)
Here the second premise is a fancy way of saying “A explains C”. Notice that the explanatory hypothesis A figures in this second premise as well as in the conclusion. The argument as a whole does not generate the explanans out of the explanandum. Rather, it seeks to justify the explanatory hypothesis …
Abduction is deductively invalid … IBE attempts to improve upon abduction by requiring that the explanation is the best explanation that we have. It goes like this:
F is a fact.
Hypothesis H explains F.
No available competing hypothesis explains F as well as H does.
Therefore, H is true
(William Lycan, 1985: 138)
This is better than abduction, but not much better. It is also deductively invalid …
There is a way to rescue abduction and IBE. We can validate them without adding missing premises that are obviously false, so that we merely trade obvious invalidity for equally obvious unsoundness. Peirce provided the clue to this. Peirce’s original abductive scheme was not quite what we have considered so far. Peirce’s original scheme went like this:
The surprising fact, C, is observed.
But if A were true, C would be a matter of course.
Hence, there is reason to suspect that A is true.
(C. S. Peirce, 1931-58, Vol. 5: 189)
This is obviously invalid, but to repair it we need the missing premise “There is reason to suspect that any explanation of a surprising fact is true”. This missing premise is, I suggest, true. After all, the epistemic modifier “There is reason to suspect that …” weakens the claims considerably. In particular, “There is reason to suspect that A is true” can be true even though A is false. If the missing premise is true, then instances of the abductive scheme may be both deductively valid and sound.
IBE can be rescued in a similar way. I even suggest a stronger epistemic modifier, not “There is reason to suspect that …” but rather “There is reason to believe (tentatively) that …” or, equivalently, “It is reasonable to believe (tentatively) that …” What results, with the missing premise spelled out, is:
It is reasonable to believe that the best available explanation of any fact is true.
F is a fact.
Hypothesis H explains F.
No available competing hypothesis explains F as well as H does.
Therefore, it is reasonable to believe that H is true.
This scheme is valid and instances of it might well be sound. Inferences of this kind are employed in the common affairs of life, in detective stories, and in the sciences.
Of course, to establish that any such inference is sound, the ‘explanationist’ owes us an account of when a hypothesis explains a fact, and of when one hypothesis explains a fact better than another hypothesis does. If one hypothesis yields only a circular explanation and another does not, the latter is better than the former. If one hypothesis has been tested and refuted and another has not, the latter is better than the former. These are controversial issues, to which I shall return. But they are not the most controversial issue – that concerns the major premise. Most philosophers think that the scheme is unsound because this major premise is false, whatever account we can give of explanation and of when one explanation is better than another. So let me assume that the explanationist can deliver on the promises just mentioned, and focus on this major objection.
People object that the best available explanation might be false. Quite so – and so what? It goes without saying that any explanation might be false, in the sense that it is not necessarily true. It is absurd to suppose that the only things we can reasonably believe are necessary truths.
What if the best explanation not only might be false, but actually is false. Can it ever be reasonable to believe a falsehood? Of course it can. Suppose van Fraassen’s mouse explanation is false, that a mouse is not responsible for the scratching, the patter of little feet, and the disappearing cheese. Still, it is reasonable to believe it, given that it is our best explanation of those phenomena. Of course, if we find out that the mouse explanation is false, it is no longer reasonable to believe it. But what we find out is that what we believed was wrong, not that it was wrong or unreasonable for us to have believed it.
People object that being the best available explanation of a fact does not prove something to be true or even probable. Quite so – and again, so what? The explanationist principle – “It is reasonable to believe that the best available explanation of any fact is true” – means that it is reasonable to believe or think true things that have not been shown to be true or probable, more likely true than not.
I do appreciate when mainstream economists like Brad make an effort at doing some methodological-ontological-epistemological reflection. On this issue, unfortunately — although it’s always interesting and thought-provoking to read what Brad has to say — his arguments are too weak to warrant the negative stance on scientific realism and inference to the best explanation.
And if you want to know more on the paradox of confirmation, science, and inference, the one book you should read is Peter Lipton‘s Inference to the Best Explanation (2nd ed, Routledge, 2004). A truly great book that has influenced my own scientific thinking tremendously.
Den antiintellektuella avgrunden är nära när den postmoderna sanningsrelativismen infekterar det offentliga samtalet på alla nivåer, inklusive den akademiska världen.
I Sverige tycks den pedagogiska disciplinen vara värst smittad. En docent i pedagogik fick för några år sedan Skolverkets uppgift att skriva en rapport om fysikundervisningen i den svenska skolan, samt komma med förslag på hur den skulle attrahera fler flickor.
”Föreställningen om det vetenskapliga tänkandets självklara överhöghet rimmar illa med jämställdhets- och demokratiidealen. […] Vissa sätt att tänka och resonera premieras mera än andra i naturvetenskapliga sammanhang. […] Om man inte uppmärksammar detta riskerar man att göra missvisande bedömningar. Till exempel genom att oreflekterat utgå från att ett vetenskapligt tänkande är mer rationellt och därför borde ersätta ett vardagstänkande” …
Pedagogen skriver vidare i rapporten: ”En genusmedveten och genuskänslig fysik förutsätter en relationell infallsvinkel på fysiken samt att en hel del av det traditionella vetenskapliga kunskapsinnehållet i fysiken plockas bort.”
Det vetenskapliga kunskapsinnehållet i fysiken ska alltså ”plockas bort” för att ”underlätta” för flickor. Inte nog med att detta är en förfärlig kunskapssyn, det är dessutom kränkande att betrakta flickor som oförmögna eller sämre på att ta till sig kunskap i fysik.
Författaren till rapporten heter Moira von Wright och är numera professor i pedagogik och rektor för Södertörns högskola. När nu en sådan kunskapsteoretisk grundsyn slagit rot i våra högre lärosäten har vi ett problem …
Efter att ha läst i ett av de senaste numren av Pedagogisk Forskning i Sverige (2-3 2014) — där författaren till artikeln “En pedagogisk relation mellan människa och häst. På väg mot en pedagogisk filosofisk utforskning av mellanrummet” ger följande intressanta “programförklaring” — är man dock föga förvånad över sakernas tillstånd inom svensk pedagogisk “vetenskap”:
Med en posthumanistisk ansats belyser och reflekterar jag över hur både människa och häst överskrider sina varanden och hur det öppnar upp ett mellanrum med dimensioner av subjektivitet, kroppslighet och ömsesidighet.
The primary aim of this study is the development of a systematic realist account of science. In this way I hope to provide a comprehensive alternative to the positivism that has usurped the title of science. I think that only the position developed here can do full justice to the rationality of scientific practice or sustain the intelligibility of such scientific activities as theoryconstruction and experimentation. And that while recent developments in the philosophy of science mark a great advance on positivism they must eventually prove vulnerable to positivist counter-attack, unless carried to the limit worked out here.
My subsidiary aim is thus to show once-and-for-all why no return to positivism is possible. This of course depends upon my primary aim.For any adequate answer to the critical metaquestion ‘what are the conditions of the plausibility of an account of science ?’ presupposes an account which is capable of thinking of those conditions as special cases. That is to say, to adapt an image of Wittgenstein’s, one can only see the fly in the fly-bottle if one’s perspective is different from that of the fly. And the sting is only removed from a system of thought when the particular conditions under which it makes sense are described. In practice this task is simplified for us by the fact that the conditions under which positivism is plausible as an account of science are largely co-extensive with the conditions under which experience is significant in science. This is of course an important and substantive question which we could say, echoing Kant, no account of science can decline, but positivism cannot ask, because (it will be seen) the idea of insignificant experiences transcends the very bounds of its thought.
This book is written in the context of vigorous critical activity in the philosophy of science. In the course of this the twin templates of the positivist view of science, viz. the ideas that science has a certain base and a deductive structure, have been subjected to damaging attack. With a degree of arbitrariness one can separate this critical activity into two strands. The first, represented by writers such as Kuhn, Popper, Lakatos, Feyerabend, Toulmin, Polanyi and Ravetz, emphasises the social character of science and focusses particularly on the phenomena of scientific change and development. It is generally critical of any monistic interpretation of scientific development, of the kind characteristic of empiricist historiography and implicit in any doctrine of the foundations of knowledge. The second strand, represented by the work of Scriven, Hanson, Hesse and Harré among others, calls attention to the stratification of science. It stresses the difference between explanation and prediction and emphasises the role played by models in scientific thought. It is highly critical of the deductivist view of the structure of scientific theories, and more generally of any exclusively formal account of science. This study attempts to synthesise these two critical strands; and to show in particular why and how the realism presupposed by the first strand must be extended to cover the objects of scientific thought postulated by the second strand. In this way I will be describing the nature and the development of what has been hailed as the ‘Copernican Revolution’ in the philosophy of science.
To see science as a social activity, and as structured and discriminating in its thought, constitutes a significant step in our understanding of science. But, I shall argue, without the support of a revised ontology, and in particular a conception of the world as stratified and differentiated too, it is impossible to steer clear of the Scylla of holding the structure dispensable in the long run (back to empiricism) without being pulled into the Charybdis of justifying it exlusively in terms of the fixed or changing needs of the scientific community (a form of neoKantian pragmatism exemplified by e.g. Toulmin and Kuhn). In this study I attempt to show how such a revised ontology is in fact presupposed by the social activity of science. The basic principle of realist philosophy of science, viz. that perception gives us access to things and experimental activity access to structures that exist independently of us, is very simple. Yet the full working out of this principle implies a radical account of the nature of causal laws, viz. as expressing tendencies of things, not conjunctions of events. And it implies that a constant conjunction of events is no more a necessary than a sufficient condition for a causal law.
A passage from Stanley Lieberson’s classic book on the methodology of social research, Making It Count (1985), has always stuck with me. In it, he considers what a social scientist might conclude from a regression model predicting black and white earnings from various background characteristics, including education. Invariably the coefficient for schooling is strong, positive, and significant—the more education one has, the greater one’s earnings. Moreover, the apparent gap between black and white earnings is much smaller when schooling is included as a predictor in the equation than when it is left out. In this sense, the racial gap is “explained” by lower average levels of education among blacks compared with whites. Obviously, therefore, all one has to do to reduce the racial gap in earnings is to increase levels of black education. The social scientist thus recommends that policymakers design and implement programs to reduce black dropout rates and increase the odds of college attendance.
“Suppose we start with a radically different perspective on this question and see where it leads us.
Let us hypothesize that racial or other interest groups will tend to take as much as they can for
themselves and will give as little as necessary to maintain the system and avoid having it overturned.
In this case, whites will give blacks as little as they can. Under such circumstances, one would assume that observed interrelations between income gaps and features such as education . . . describe . . . the current pathways leading from a specific causal force to the outcome of that force. If so, a complicated causal analysis of factors contributing to the racial gaps in income has not the causal value one might have assumed. It describes the given set of events at a given time; it describes what a black person might well follow as a get-ahead strategy if he or she can assume that not many other blacks will follow the same strategy and hence the basic [social] matrix will remain unaltered. But there is no assurance that this matrix will continue to operate—indeed, there is virtual certainty that the matrix will not continue to operate if some superficial factor that appears to cause the income gap is no longer relevant (for example, if the groups end up with the same educational distribution). In which case, new rules and regulations will operate; the other regression coefficients will change in value in order to maintain the existing system.” (pp. 191–92)
Simply put, Lieberson argues that if whites are selfishly motivated to discriminate against blacks to enhance their own material well-being, then when the government forces them to end a particular discriminatory practice, they will simply look for other means to maintain white privilege. If an older discriminatory mechanism based explicitly on race becomes impossible to sustain, whites will substitute new ones that are more subtly associated with race. The specific mechanisms by which racial stratification is achieved may thus be expected to change over time as practices shift in response to civil rights enforcement.
In my eyes, social orders are normally fragile and precarious; unpleasant surprises may turn up at any moment. I also think it wrong to demand that someone who identifies a problem should immediately offer a solution as well. I do not bow to such prescriptions … Problems may be such that there is no solution to them — or anyway, none achievable here and now. If someone were to ask me reproachfully where was ‘the positive,’ this would then indeeed be a case where I could appeal to Adorno. For his reply, much better formulated, would doubtless have been: what if there is nothing positive?
[h/t Lord Keynes]
For more on my own objections to Bayesianism:
Bayesianism — a patently absurd approach to science
Bayesianism — preposterous mumbo jumbo
One of the reasons I’m a Keynesian and not a Bayesian
Keynes and Bayes in paradise
One of my favourite “problem situating lecture arguments” against Bayesianism goes something like this: Assume you’re a Bayesian turkey and hold a nonzero probability belief in the hypothesis H that “people are nice vegetarians that do not eat turkeys and that every day I see the sun rise confirms my belief.” For every day you survive, you update your belief according to Bayes’ Rule
P(H|e) = [P(e|H)P(H)]/P(e),
where evidence e stands for “not being eaten” and P(e|H) = 1. Given that there do exist other hypotheses than e, P(e) is less than 1 and a fortiori P(H|e) is greater than P(H). Every day you survive increases your probability belief that you will not be eaten. This is totally rational according to the Bayesian definition of rationality. Unfortunately — as Bertrand Russell famously noticed — for every day that goes by, the traditional Christmas dinner also gets closer and closer …
When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations and abstractions necessary for the deductivist machinery to work simply don’t hold.
If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? The logic of idealization is a marvellous tool in mathematics and axiomatic-deductivist systems, but a poor guide for action in real-world systems, in which concepts and entities are without clear boundaries and continually interact and overlap.
Or as Hans Albert has it on the neoclassical style of thought:
In everyday situations, if, in answer to an inquiry about the weather forecast, one is told that the weather will remain the same as long as it does not change, then one does not normally go away with the impression of having been particularly well informed, although it cannot be denied that the answer refers to an interesting aspect of reality, and, beyond that, it is undoubtedly true …
We are not normally interested merely in the truth of a statement, nor merely in its relation to reality; we are fundamentally interested in what it says, that is, in the information that it contains …
Information can only be obtained by limiting logical possibilities; and this in principle entails the risk that the respective statement may be exposed as false. It is even possible to say that the risk of failure increases with the informational content, so that precisely those statements that are in some respects most interesting, the nomological statements of the theoretical hard sciences, are most subject to this risk. The certainty of statements is best obtained at the cost of informational content, for only an absolutely empty and thus uninformative statement can achieve the maximal logical probability …
The neoclassical style of thought – with its emphasis on thought experiments, reflection on the basis of illustrative examples and logically possible extreme cases, its use of model construction as the basis of plausible assumptions, as well as its tendency to decrease the level of abstraction, and similar procedures – appears to have had such a strong influence on economic methodology that even theoreticians who strongly value experience can only free themselves from this methodology with difficulty …
Science progresses through the gradual elimination of errors from a large offering of rivalling ideas, the truth of which no one can know from the outset. The question of which of the many theoretical schemes will finally prove to be especially productive and will be maintained after empirical investigation cannot be decided a priori. Yet to be useful at all, it is necessary that they are initially formulated so as to be subject to the risk of being revealed as errors. Thus one cannot attempt to preserve them from failure at every price. A theory is scientifically relevant first of all because of its possible explanatory power, its performance, which is coupled with its informational content …
The connections sketched out above are part of the general logic of the sciences and can thus be applied to the social sciences. Above all, with their help, it appears to be possible to illuminate a methodological peculiarity of neoclassical thought in economics, which probably stands in a certain relation to the isolation from sociological and social-psychological knowledge that has been cultivated in this discipline for some time: the model Platonism of pure economics, which comes to expression in attempts to immunize economic statements and sets of statements (models) from experience through the application of conventionalist strategies …
Clearly, it is possible to interpret the ‘presuppositions’ of a theoretical system … not as hypotheses, but simply as limitations to the area of application of the system in question. Since a relationship to reality is usually ensured by the language used in economic statements, in this case the impression is generated that a content-laden statement about reality is being made, although the system is fully immunized and thus without content. In my view that is often a source of self-deception in pure economic thought …
A further possibility for immunizing theories consists in simply leaving open the area of application of the constructed model so that it is impossible to refute it with counter examples. This of course is usually done without a complete knowledge of the fatal consequences of such methodological strategies for the usefulness of the theoretical conception in question, but with the view that this is a characteristic of especially highly developed economic procedures: the thinking in models, which, however, among those theoreticians who cultivate neoclassical thought, in essence amounts to a new form of Platonism.