Ioannis Votsis

This volume showcases the best of recent research in the philosophy of science. A compilation of papers presented at the EPSA 13, it explores a broad distribution of topics such as causation, truthlikeness, scientific representation, gender-specific medicine, laws of nature, science funding and the wisdom of crowds. Papers are organised into headings which form the structure of the book. Readers will find that it covers several major fields within the philosophy of science, from general philosophy of science to the more specific philosophy of physics, philosophy of chemistry, philosophy of the life sciences, philosophy of psychology, and philosophy of the social sciences and humanities, amongst others. This volume provides an excellent overview of the state of the art in the philosophy of science, as practiced in different European countries and beyond. ​It will appeal to researchers with an interest in the philosophical underpinnings of their own discipline, and to philosophers who wish to explore the latest work on the themes explored.

The recent surge of populism, nationalism and authoritarian tendencies in the political arena as well as the widespread propagation of fake news, conspiracy theories and disinformation in social media are increasingly worrisome and pose a severe threat to democratic societies and the rule of law. Political decisions in such societies must, first and foremost, be guided by evidence and reason. Unfortunately, the events of the last years have shown that the existing institutions and mechanisms are more and more vulnerable to misuse, leaving democracies well and truly adrift from wholesome deliberative practices. It thus seems imperative that those institutions and mechanisms be redesigned in an attempt to make democracy “foolproof” – that is, to provide some sort of immunisation against these threats, even if it is, of course, nearly impossible to achieve such a lofty ideal in practice. This is the second part of a special issue that explores ways to make democracies “foolproof” in the explicated sense.

The events of the year 2016 have led many critical observers to doubt the stability and longevity of democracy. Ideally, democracy effectuates the rule of reason. Debates in elected assemblies and in society as a whole should serve the process of finding best reasons for political decisions. However, the mechanisms that currently produce such decisions are vulnerable to misuse. Arguably, they need to be redesigned in an attempt to make them “foolproof” - i.e., to design them in a way to make misuse inherently impossible or to minimize its negative consequences.

In this paper, I investigate two potential ways to experimentally test the thesis that observation is theory-laden. One is a proposal due to Schurz (J Gen Philos Sci 46:139–153, 2015) and the other my own. The two are compared and found to have some features in common. One such feature is that both proposals seek to create conditions that compel test subjects with diverse theoretical backgrounds to resort to bare (or at least as bare as possible) observational judgments. Thus, if judgments made under those conditions are convergent across test subjects, the said convergence would lend credibility to the view that theory-neutral observations are feasible. This still leaves the question of why any such convergence exists unanswered. Towards the end of the paper, it is argued that the best explanation for observational judgment convergence is the veridicality of those judgments.

Of all the sub-disciplines of philosophy, the philosophy of science has perhaps the most privileged relationship to information theory. This relationship has been forged through a common interest in themes like induction, probability, confirmation, simplicity, non-ad hocness, unification and, more generally, ontology. It also has historical roots. One of the founders of algorithmic information theory, Ray Solomonoff, produced his seminal work on inductive inference as a direct result of grappling with problems first encountered as a student of the influential philosopher of science Rudolf Carnap. There are other such historical connections between the two fields. Alas, there is no space to explore them here. Instead this essay will restrict its attention to a broad and accessible overview of the aforementioned common themes, which, given their nature, mandate an emphasis on AIT as opposed to general information theory.

Science is increasingly becoming automated. Tasks yet to be fully automated include the conjecturing, modifying, extending and testing of hypotheses. At present scientists have an array of methods to help them carry out those tasks. These range from the well-articulated, formal and unexceptional rules to the semi-articulated and variously understood rules-of-thumb and intuitive hunches. If we are to hand over at least some of the aforementioned tasks to machines, we need to clarify, refine and make formal, not to mention computable, even the more obscure of the methods scientists successfully employ in their inquiries. The focus of this essay is one such less-than-transparent methodological rule. I am here referring to the rule that ad hoc hypotheses ought to be spurned. This essay begins with a brief examination of some notable conceptions of ad hoc-ness in the philosophical literature. It is pointed out that there is a general problem afflicting most such conceptions, namely the intuitive judgments that are supposed to motivate them are not universally shared. Instead of getting bogged down in what ad hoc-ness exactly means, I shift the focus of the analysis to one undesirable feature often present in alleged cases of ad hoc-ness. I call this feature the ‘monstrousness’ of a hypothesis. A fully articulated formal account of this feature is presented by specifying what it is about the internal constitution of a hypothesis that makes it monstrous. Using this account, a monstrousness measure is then proposed and somewhat sketchily compared with the minimum description length approach.

This is certainly true. Simulationists and experimentalists face equally relevant challenges when it comes to establishing that the results of their simulation or experiment are informative about the real world. But it is one thing to point this fact out, and it is another to understand how those challenges are overcome, under differing circumstances, and in varying contexts. It is here that Marcel Boumans’ contribution becomes especially valuable. He presents an example from economics in which a mathematical model performs the role, not of a representational entity, but of a data sensor. Boumans argues, and I concur, that the manner in which such models are assessed is particularly interesting. They cannot be assessed merely by being confronted with facts about the world, since these models are themselves used in generating the relevant data about the phenomena in question. The relevant strategy for assessing these models is calibration. In other words, rather than being held side by side with the relevant bit of the world, the models are held up against other instruments that are antecedently believed to be reliable sources of data.

In recent years, two challenges stand out against scientific realism: the argument from the underdetermination of theories by evidence (UTE) and the pessimistic induction argument (PI). In his book, Kyle Stanford accepts the gravity of these challenges, but argues that the most serious and powerful challenge to scientific realism has been neglected. The problem of unconceived alternatives (PUA), as he calls it, is introduced in chapter one and refined in chapter two. In short, PUA holds that throughout history scientists have failed to conceive alternative theories roughly equally well-confirmed to the theories of the day by the available evidence and, crucially, that such alternatives eventually were conceived and adopted by some section of the scientific community. PUA is a version of UTE, but, unlike its kin, enjoys substantial historical support. It leads to a sort of pessimistic induction that Stanford brands ‘the new induction’ (NI), according to which we should be doubtful about the truth claims of current theories since the historical record suggests that unconceived alternatives are typically lurking in the shadows. His proposal contains two important shifts of focus: First, there is a shift from artificially produced rival theories - of the kind typically talked about in the underdetermination debate - to actual rivals. Second, instead of focusing on empirically equivalent rivals, he urges a shift to rivals that are more or less equally well-confirmed to existing theories by the available evidence at a given point in time. Prima facie, PUA sounds like a welcome addition to the anti-realist arsenal, drawing on historical evidence to support the induction that current theories probably face genuine alternatives waiting to be conceived.

Structural realism is arguably one of the most influential movements to have emerged in philosophy of science in the last decade or so. Advocates of this movement attempt to answer epistemological and/or ontological questions concerning science by arguing that the key to all such questions is the mathematical formalism of a theory. This is so, according to structural realists, because the mathematical formalism encodes all and only what is important about a theory’s target domain, namely its structure. Almost without exception, discussions of structural realism centre on the natural sciences and in particular on modern physics. Given that a number of other sciences are less – indeed in some cases much less – mathematised than modern physics, does structural realism have anything informative to say about them? In this talk, I take up the task of articulating what structural realists ought to say about the social sciences if they are to consider themselves as offering a coherent philosophy for the whole of science

This paper examines what exactly amounts to the view commonly known as ‘perspectivism’, sometimes also known as ‘perspectivalism’. Of the various possible conceptions of perspectivism, four are singled out for closer inspection. Each makes clearly separable claims of varying strength. Their strength is judged against how much doubt they throw on key claims made by the view’s presumed arch-nemesis, namely realism. It is argued that the first two offer no serious challenge to realism. To be precise, it is argued that the first one is blatantly false, while the second is true but utterly harmless. Things are less clear cut with the other two conceptions of perspectivism. If true, they appear to present a more serious challenge to realism. It is argued that considerable doubts hang over their truth as to date arguments raised in their support are far from compelling. Even so, these conceptions cannot be summarily dismissed. Indeed, under more reasonable construals, they need not be for realism to survive and thrive. This is because claims these conceptions make in the name of perspectivism turn out to be easily coupled with realism.

When it comes to name-calling, structural realists have heard pretty much all of it. Among the many insults, they have been called ‘empiricist anti-realists’ but also ‘traditional scientific realists’. Obviously the collapse accusations that motivate these two insults cannot both be true at the same time. The aim of this paper is to defend the epistemic variety of structural realism against the accusation of collapse to traditional scientific realism. In so doing, I turn the tables on traditional scientific realists by presenting them with a dilemma. They can either opt for a construal of their view that permits epistemic access to non-structural features of unobservables but then face the daunting task of substantiating a claim that seems to have little hope of being true or they can drop the requirement of epistemic access to non-structural features but then face a collapse to epistemic structural realism. There is thus only one well supported way to be a realist. No wonder then that many traditional scientific realists have over the years expressed views that are strikingly similar to epistemic structural realism. It is high time to let these epistemic structural realists out of the closet.

The paper is divided into three parts. The first part identifies one of the main problems with many current accounts of the notion of explanation: The unreasonable demand, proposed by Michael Scriven and subsequently adopted by many philosophers, that we must square our account of scientific explanation to our intuitions about explanations in everyday contexts. It is first pointed out that the failure to provide a satisfactory account is not endemic to the notion of explanation, i.e. it is widespread amongst notions. Many of the notions considered in philosophical contexts originate and have a function in broader everyday contexts. Indeed, in evaluating accounts of these notions we rely on intuitions that originate in these broader contexts. Yet, we rarely seem to question the appropriateness of these intuitions in more restricted, in this case scientific, contexts. I argue against this complacency, pointing out that our intuitions can often be inconsistent.

This paper elaborates on the following correspondence theorem : if theory T has been empirically successful in a domain of applications A, but was superseded later on by a different theory T* which was likewise successful in A, then under natural conditions T contains theoretical expressions \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varphi}$$\end{document} which were responsible for T’s success and correspond to certain theoretical expressions \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varphi}^{*}$$\end{document} of T*. I illustrate this theorem at hand of the phlogiston versus oxygen theories of combustion, and the classical versus relativistic theories of mass. The ontological consequences of the theorem are worked out in terms of the indirect reference and partial truth. The final section explains how the correspondence theorem may justify a weak version of scientific realism without presupposing the no-miracles argument.

An integral part of the schooling of scientists, especially experimental ones, is the cultivation of the significance and role of scientific evidence. Naturally this schooling is not conducted in vacuuo. Budding scientists already have experiences of, and intuitions about, the use of evidence in everyday life. In this talk I take a sustained look at the relations between common-sense notions of evidence and scientific ones. Among other things, I argue that scientific notions of evidence and associated practices are in many ways conservative extensions of what is best about our common-sense notions and practices. This contradicts a rather widely held but often tacit view that science and its notions are largely insular.

Structural realists of nearly all stripes endorse the structural continuity claim. Roughly speaking, this is the claim that the structure of successful scientific theories survives theory change because it has latched on to the structure of the world. In this paper I elaborate, elucidate and modify the structural continuity claim and its associated argument. I do so without presupposing a particular conception of structure that favours this or that kind of structural realism. Instead I focus on how structural realists can best account for the neutrally formulated historical facts. The result, I hope, crystallises some of the shared commitments, desiderata and limits of structural realists

Most scientific realists nowadays would endorse an argument like the following: The empirical and explanatory success of theories or theory-parts is a good indicator of their approximate truth. In turn, approximate truth is a good indicator of referential success. Successor theories typically preserve all of the empirical and explanatory success of their predecessors as well as add to it. They are thus in general strictly more approximately true than their predecessors. Moreover, by preserving their predecessors’ approximately true parts they preserve the referential success the predecessors probably enjoy. This implies that successor theories that are more approximately true than their predecessors are typically also referentially continuous with them

This chapter traces the development of structural realism within the scientific realism debate and the wider current of structuralism that has swept the philosophy of the natural sciences in the twentieth century.1 The primary aim is to make perspicuous the many manifestations of structural realism and their underlying claims. Among other things, I will compare structural realism’s various manifestations in order to throw more light onto the relations between them. At the end of the chapter, I will identify the main objections raised against the epistemic form of structural realism. This last task will pave the way for the evaluation of the structural realist answer to the main epistemological question, an evaluation that will be central to the rest of this dissertation.

My main aim in this paper is to clarify the concepts of referential success and of referential continuity that are so crucial to the scientific realism debate. I start by considering the three dominant theories of reference and the intuitions that motivate each of them. Since several intuitions cited in support of one theory conflict with intuitions cited in support of another something has to give way. The traditional policy has been to reject all intuitions that clash with a chosen theory. A more radical policy, tied to some experimental philosophers, has called for the rejection of any evidential role for intuitions. I explore a largely ignored third alternative, i.e. saving intuitions (and their evidential role) even when they are at odds. To accommodate conflicting intuitions different sets of internally consistent (yet externally inconsistent) intuitions are taken to lend credence to different concepts of reference. In the current context, this means that the concepts of referential success and referential continuity are not monolithic. They are what I call 'polylithic'. This paper is as much about meta-philosophical concerns with the role of intuitions as it is about reference and the scientific realism debate. Regarding the former I hope that a blueprint will emerge for similar projects in other philosophical domains. Regarding the latter, I hope that polylithicity helps disentangle claims about referential success and continuity in the scientific realism debate by making perspicuous which concepts are best equipped to evaluate the realist's epistemic claims against the historical record of science

Participants in the debate about whether simplicity is a guide to truth or merely pragmatically useful typically wrangle over two problems: (1) how to weigh simplicity against other virtues like strength and fitness and (2) whether there is a unique measure for simplicity that straps it to truth. I would like to put forth a third problem: (3) Even if problems (1) and (2) could be solved, it is far from clear whether the simplest theory out of an available class of competitors would always be the one closest to the truth