Scientific phenomena and patterns in data
Pascal Ströing · Electronic Theses of LMU Munich (Ludwig-Maximilians-Universität München) · 2018
To defend this view I have to present a sufficiently powerful epistemological framework that does not leave the door open for anything unexplained to happen in processes of phenomenon selection and that could be responsible for letting completely observer-independent criteria for phenomenon selection in favour of phenomenon realism creep in.Strategies for the defence of phenomenon realism vi Abstract are usually to deflate the notion of realism by elevating human consciousness or interests to the status of instantiating or creating reality (Dennett), or to stipulate that reality is best explained by notions that neatly fit to our human ways of describing the world (e.g.ontic structural realism).In my view, both of these defence strategies are unjustified.I defend my view in three successive steps.We need to have a notion of patterns to clarify the relation between patterns and phenomena.Patterns occur or are detected in data.Therefore, a notion of data needs to be explicated first.As opposed to some notions from the literature (Hacking; Leonelli) but with similarities to others (Suppes) data is non-material and purely mathematical.Data itself does not play a representing role, due to the problem of relation without relata.In a second step, I follow Grenander's epistemological approach to define patterns by a genuinely constructive (with an idiosyncratic notion of constructivity) mathematical approach in opposition to, for this application in philosophy, more influential notions of information in data from information theory (Shannon; Kolmogorov).In a third step, I argue that not only data and patterns are mathematical, scientific inferences that lead to phenomena selection and theory formation can, in principle, be expressed in purely mathematical terms, too.This view has classical proponents (Russell) and can even be defended empirically with reference to recent developments in artificial intelligences that are employed to mind games (e.g.Go; poker).Under this view of a mathematised epistemology, scientific reasoning is independent from having or not having a specific human consciousness and there is no reason to believe that human agency is necessary to accomplish cognitive tasks of even our most accomplished scientific reasoning, as some authors contrarily imply (Searle).The empirical world presents itself to agents of science by material causal interactions with sensory organs or measurement devices.What patterns in observation data appear as phenomena and what as uninteresting depends on the shared body of the agents' background assumptions, as well as the agents' sensory and cognitive capabilities.This distinction is misunderstood by some due to the extreme complexity of human cognitive processes and not due to the real fabric of the world or the importance of consciousness for scientific reasoning.