Abstract
The paper offers an account of the structure of information provided by models that relevantly deviate from reality. It is argued that accounts of scientific modeling according to which a model’s epistemic and pragmatic relevance stems from the alleged fact that models give access to possibilities fail. First, it seems that there are models that do not give access to possibilities, for what they describe is impossible. Secondly, it appears that having access to a possibility is epistemically and pragmatically idle. Based on these observations, an alternative is developed.
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Notes
Models also pose a number of significant metaphysical problems, some of which may bear on the epistemology of scientific modeling, and one may suggest that the way they represent the world poses special problems as well. Numerous monographs and papers deal with these and related topics, and the literature on this topic is still growing. A useful summary can be found in (Hartmann and Frigg 2012). Prominent suggestions have been made by Wimsatt (1987), Giere (2004), Sugden (2000), Godfrey-Smith (2006), van Fraassen (1980), Frigg (2010). Recent monographs include (Weisberg 2013) and (Toon 2012).
Here, I am interested in factive doxastic relations; pragmatic notions of understanding or notions that tie understanding to prediction (de Regt 2014), though of course interesting in the context of scientific modeling, do not play a key role for the topic we are dealing with here. In Sect. 4, I will briefly come back to the relation between modeling and prediction as well as intervention.
Recently, Julian Reiss has described a cognate of this problem as a paradox; he puts it as follows:
We have now reached an impasse of the kind philosophers call a paradox: a set of statements, all of which seem individually acceptable or even unquestionable but which, when taken together, are jointly contradictory. These are the statements:
Economic models are false.
Economic models are nevertheless explanatory.
Only true accounts can explain. (Reiss 2012, p. 49)
Apparently, this is not a problem for economics only (and one may doubt that it is a paradox in any robust sense): any explanation that is based on a model that relevantly deviates from reality suffers from the same defect. And we find such models all across the hierarchy (or, in more modern terms: the various hierarchies) of sciences – from the social sciences to psychology, from biology to chemistry and to physics. The physical laws describing gases as if they were ideal are, strictly speaking, false, just like the Lotka-Volterra model in Biology is. Thus, the problem is, if a problem at all, widespread.
Whether or not this is the adequate rendering of the intuitive notion of “how possible” explanations is debatable. One may suggest that we require at least the explanandum to be true in the actual world. For what follows, it will suffice to assume that whatever the correct rendering of this idea is, any how possible explanation will imply a statement of this form.
Persson (2012) suggests that one could also interpret reference to possibility as distancing oneself from the truth of the explanation (this is how I interpret his idea that “it is possible that (p because q)” roughly functions like “it is a potential explanation, that p because q”. On this view, one does not commit oneself to the explanation; one reads it as a potential explanation. The examples below will show that this reading cannot be applied to some significant cases of models that deviate from reality. More importantly, the epistemic benefit of contemplating an explanation is lost once we come to see that it is not a real explanation.
One may object that knowledge just is not the right kind of epistemic state; rather, something like grasping does the trick. And we certainly cannot grasp a logical possibility without grasping the conceptual content (although we can grasp that some sentence expresses a logical possibility without fully grasping its conceptual content). But then, isn’t grasping a logical possibility, in an interesting sense of the term, just having access to a metaphysically possible world?
This is Lewis’ suggestion to guarantee that we truly get some definition (cf. Lewis 1972).
This bears some similarities to fictional accounts of modeling. Frigg 2010 and Toon 2012 refer to Walton’s theory of fiction. Whereas these accounts are mostly concerned with representation and the role of games of make-belief in scientific modeling, the account proposed here remains entirely neutral as to the metaphysics of models, the question of whether or not there is a specific representational structure in modeling, and the cognitive aspect of modeling. It should be noted, however, that due to the hyper-intensionality of ‘according to_,_’, we could easily get rid of metaphysical problems that may come up in the context of scientific modeling. This, however, is a topic for another paper.
This appears to account for what Strevens (2013) calls ‘understanding with’. Strevens characterizes this notion, roughly, as follows: Understanding with requires to be able to explain a range of phenomena, but the explanations need not be correct. In this sense, one can understand a phenomenon with a model; but this does not imply that one understands why the phenomenon occurs.
There may be one exception, though. Consider cases where scientists look for actual models, models that do get it right. Then, as an intermediate step, it may help to know that the model captures at least a possibility; one way of being a false model is thereby excluded, namely, being a model that captures an impossibility. But this knowledge does not concern the application of a model; it concerns the status of the model itself.
More needs to be said about this kind of conceptual implication. We can think of it as a cognate of the kind of implication modeled in two-dimensional semantics. For a recent paper that also offers a summary of earlier developments, see (Chalmers 2011).
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Acknowledgments
I would like to thank the audience at the “Explanatory Power II”-Workshop in Bochum in Spring 2013, the audiences at colloquia in Belgrade, Bochum and Hannover, the guests at Thomas Spitzley’s discussion group at the University Duisburg-Essen, Jens Harbecke, Markus Eronen and, especially, two anonymous referees for extremely helpful comments on earlier drafts of this paper. Generous funding for this work was provided by the Volkswagen Stiftung within the Dilthey-Fellowship scheme, as part of the funding for the Project “A Study in Explanatory Power”, based at the University Duisburg-Essen.
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van Riel, R. The content of model-based information. Synthese 192, 3839–3858 (2015). https://doi.org/10.1007/s11229-015-0728-y
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DOI: https://doi.org/10.1007/s11229-015-0728-y