Chirimuuta, M.
(2022)
Reorienting Realism.
In: UNSPECIFIED.
Abstract
The way that I seek to redirect the realism debate is away from the question of the reality of unobservable posits of scientific theories and models, and towards the question of whether those theories and models should be interpreted realistically. This makes it easier to include within the realism debate sciences of relatively large and observable items, as are many branches of biology. But it is not a simple trade of the ontological question of realism for a semantic one. My contribution will focus on computational neuroscience. In this discipline, models are normally interpreted as representing computations actually performed by parts of the brain. Semantically, this interpretation is literal and realistic. Ontologically, it supposes that the structure represented mathematically as a computation (i.e. a series of state transitions) there in the brain processes. I call this supposition of a structural similarity (homomorphism) between model and target, formal realism. This stands in contrast to an alternative way to interpret the model which I call formal idealism. The view here is that whatever processes exist in the brain are vastly more complicated than the structures represented in the computational models, and that the aim of modelling is to achieve an acceptable simplification of those processes. Thus, the success of the research is more a matter of structuring than of discovering pre-existing structures.
Ultimately, the realism debate is motivated by curiosity about what it is that the best scientific representations have to tell us about the world: is this thing really as presented in the model? Thus, I argue that the contrast between formal realism vs. idealism is a good template for framing the realism debate when discussing the implications of sciences of extremely complex macro and mesoscopic systems, such as the nervous system, and generalising to elsewhere in biology, including ecology, as well as the physical sciences of large complex systems such as climate and geological formations. Formal idealism does not suppose that the structures given in scientific models are fully constructed or mind-dependent, but that there is an eliminable human component in all scientific representations, due to the fact that they can never depict the full complexity of their target systems and as such are the result of human decisions about how to simplify. The acceptability of certain simplifications (abstractions and idealisations) over others is due to a number of factors, including predictive accuracy, mathematical/computational tractability, and the envisaged technological applications of the model. Formal realism supposes that scientific representations are, at their best, a clear-view window onto mind-independent nature, whereas formal idealism maintains that this is an unrealistic way to describe the practices and achievements of science.
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