Claus Beisbart

What is the status of a cat in a virtual reality environment? Is it a real object? Or part of a fiction? Virtual realism, as defended by D. J. Chalmers, takes it to be a virtual object that really exists, that has properties and is involved in real events. His preferred specification of virtual realism identifies the cat with a digital object. The project of this paper is to use a comparison between virtual reality environments and scientific computer simulations to critically engage with Chalmers’s position. I first argue that, if it is sound, his virtual realism should also be applied to objects that figure in scientific computer simulations, e.g. to simulated galaxies. This leads to a slippery slope because it implies an unreasonable proliferation of digital objects. A philosophical analysis of scientific computer simulations suggests an alternative picture: The cat and the galaxies are parts of fictional models for which the computer provides model descriptions. This result motivates a deeper analysis of the way in which Chalmers builds up his realism. I argue that he buys realism too cheap. For instance, he does not really specify what virtual objects are supposed to be. As a result, rhetoric aside, his virtual realism isn’t far from a sort of fictionalism.

The paper provides a systematic overview of recent debates in epistemology and philosophy of science on the nature of understanding. We explain why philosophers have turned their attention to understanding and discuss conditions for “explanatory” understanding of why something is the case and for “objectual” understanding of a whole subject matter. The most debated conditions for these types of understanding roughly resemble the three traditional conditions for knowledge: truth, justification and belief. We discuss prominent views about how to construe these conditions for understanding, whether understanding indeed requires conditions of all three types and whether additional conditions are needed.

This paper details the content and structure of the folk concept of life, and discusses its relevance for scientific research on life. In four empirical studies, we investigate which features of life are considered salient, universal, central, and necessary. Functionings, such as nutrition and reproduction, but not material composition, turn out to be salient features commonly associated with living beings (Study 1). By contrast, being made of cells is considered a universal feature of living species (Study 2), a central aspect of life (Study 3), and our best candidate for being necessary for life (Study 4). These results are best explained by the hypothesis that people take life to be a natural kind subject to scientific scrutiny.

If cosmology is to obtain knowledge about the whole universe, it faces an underdetermination problem: Alternative space-time models are compatible with our evidence. The problem can be avoided though, if there are good reasons to adopt the Cosmological Principle (CP), because, assuming the principle, one can confine oneself to the small class of homogeneous and isotropic space-time models. The aim of this paper is to ask whether there are good reasons to adopt the Cosmological Principle in order to avoid underdetermination in cosmology. Various strategies to justify the CP are examined. For instance, arguments to the effect that the truth of the CP follows generically from a large set of initial conditions; an inference to the best explanation; and an inductive strategy are assessed. I conclude that a convincing justification of the CP has not yet been established, but this claim is contingent on a number of results that may have to be revised in the future.

In den vergangenen Jahren hat die Europäische Union (EU) wiederholt versucht, ihre Institutionen zu reformieren. Als der Entwurf für eine Europäische Verfassung und später der Vertrag von Lissabon ausgehandelt wurden, betraf einer der meistdiskutiertesten Streitpunkte die Frage, nach welcher Entscheidungsregel der EU-Ministerrat abstimmen sollte. Diese Frage ist eine genuin normative Frage. Deshalb sollten auch politische Philosophen und Ethiker etwas zu dieser Frage beitragen können. Im folgenden wollen wir uns dieser Herausforderung stellen und alternative Entscheidungsregeln für den EU-Ministerrat bewerten. Dabei erweisen sich die Methoden der probablistische Modellierung und der Simulation sozialer Prozesse als unerlässlich.1 Damit wird deutlich, wie Simulationen auch innerhalb der angewandten politischen Philosophie als Methode eingesetzt werden können.

The mean majority deficit in a two-tier voting system is a function of the partition of the population. We derive a new square-root rule: For odd-numbered population sizes and equipopulous units the mean majority deficit is maximal when the member size of the units in the partition is close to the square root of the population size. Furthermore, within the partitions into roughly equipopulous units, partitions with small even numbers of units or small even-sized units yield high mean majority deficits. We discuss the implications for the winner-takes-all system in the US Electoral College.

It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some objections and reject the view that computer simulations produce knowledge because they are experiments. I conclude by comparing thought experiments and computer simulations, assuming that both are arguments

The goal of this paper is to re-assess reflective equilibrium (“RE”). We ask whether there is a conception of RE that can be defended against the various objections that have been raised against RE in the literature. To answer this question, we provide a systematic overview of the main objections, and for each objection, we investigate why it looks plausible, on what standard or expectation it is based, how it can be answered and which features RE must have to meet the objection. We find that there is a conception of RE that promises to withstand all objections. However, this conception has some features that may be unexpected: it aims at a justification that is tailored to understanding and it is neither tied to intuitions nor does it imply coherentism. We conclude by pointing out a cluster of questions we think RE theorists should pay more attention to.

N. Bostrom’s simulation argument and two additional assumptions imply that we likely live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies.

Consider the following two seemingly unrelated questions. First, why does Rousseau (1993 [1762]) believe that the formation of factions or partial associations is not conducive to the general will in Du Contrat Social, II, 3? Second, why do federal assemblies typically strive for some form of degressive proportionality, i.e. a balance between equal and proportional representation, for the countries in the federation? We will show that there is a surprising connection between these questions. We turn to our first question. It is often thought that Rousseau’s opposition to factions can be interpreted in reference to the Condorcet Jury Theorem. The Condorcet Jury Theorem states that if voters are more likely to be right on some issue than not and cast their votes independently, then the chance that the majority is correct converges to one as the number of voters goes to infinity. This interpretation is tempting, but it is inconsistent with some crucial textual evidence. We turn to our second question. Consider a federation of countries with a decision-making assembly in which each country casts a block vote. On equal representation, the vote of each country has the same weight. On proportional representation, the weights of the votes are proportional to the countries’ population sizes. In between these extremes, we can let the weights increase as a function of population sizes, but smaller countries receive greater weights and larger countries receive lesser weights than proportionality would warrant. Such weightings are called degressively proportional weightings. How can degressive proportionality be justified? And does this justification provide us any guidance as to how these weights should be set? A correct understanding of Rousseau’s misgivings about the formation of factions will hold the key to these questions.

Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, _contra_ Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan’s claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.

Computer simulations and experiments share many important features. One way of explaining the similarities is to say that computer simulations just are experiments. This claim is quite popular in the literature. The aim of this paper is to argue against the claim and to develop an alternative explanation of why computer simulations resemble experiments. To this purpose, experiment is characterized in terms of an intervention on a system and of the observation of the reaction. Thus, if computer simulations are experiments, either the computer hardware or the target system must be intervened on and observed. I argue against the first option using the non-observation argument, among others. The second option is excluded by e.g. the over-control argument, which stresses epistemological differences between experiments and simulations. To account for the similarities between experiments and computer simulations, I propose to say that computer simulations can model possible experiments and do in fact often do so.

Reflective equilibrium (RE) is often regarded as a powerful method in ethics, logic, and even philosophy in general. Despite this popularity, characterizations of the method have been fairly vague and unspecific so far. It thus may be doubted whether RE is more than a jumble of appealing but ultimately sketchy ideas that cannot be spelled out consistently. In this paper, we dispel such doubts by devising a formal model of RE. The model contains as components the agent’s commitments and a theory that tries to systematize the commitments. It yields a precise picture of how the commitments and the theory are adjusted to each other. The model differentiates between equilibrium as a target state and the dynamic equilibration process. First solutions to the model, obtained by computer simulation, show that the method allows for consistent specification and that the model’s implications are plausible in view of expectations on RE. In particular, the mutual adjustment of commitments and theory can improve one’s commitments, as proponents of RE have suggested. We argue that our model is fruitful not only because it points to issues that need to be dealt with for a better understanding of RE, but also because it provides the means to address these issues.

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

If we are to constrain our place in the world, two principles are often appealed to in science. According to the Copernican Principle, we do not occupy a privileged position within the Universe. The Cosmological Principle, on the other hand, says that our observations would roughly be the same, if we were located at any other place in the Universe. In our paper we analyze these principles from a logical and philosophical point of view. We show how they are related, how they can be supported and what use is made of them. Our main results are: 1. There is a logical gap between both principles insofar as the Cosmological Principle is significantly stronger than the Copernican Principle. 2. A step that is often taken for establishing the Cosmological Principle on the base of the Copernican Principle and observations is not incontestable as it stands, but can be supplemented with a different argument. 3. The Cosmological Principle might be crucial for cosmology to the extent it is not supported by empirical evidence.

We construct a new measure of voting power that yields reasonable measurements even if the individual votes are not cast independently. Our measure hinges on probabilities of counterfactuals, such as the probability that the outcome of a collective decision would have been yes, had a voter voted yes rather than no as she did in the real world. The probabilities of such counterfactuals are calculated on the basis of causal information, following the approach by Balke and Pearl. Opinion leaders whose votes have causal influence on other voters' votes can have significantly more voting power under our measure. But the new measure of voting power is also sensitive to the voting rule. We show that our measure can be regarded as an average treatment effect, we provide examples in which it yields intuitively plausible results and we prove that it reduces to Banzhaf voting power in the limiting case of independent and equiprobable votes

Kant famously thought that mathematics contains synthetic a priori truths. In his book, Wille defends a version of the Kantian thesis on not-so-Kantian grounds. Wille calls his account neo-Kantian, because it makes sense of Kantian tenets by using a methodology that takes the linguistic and pragmatic turns seriously.Wille's work forms part of a larger project in which the statuses of mathematics and proof theory are investigated. The official purpose of the present book is to answer the question: what is mathematics. Wille sets himself the task of finding a definition that enables him to distinguish between mathematics and proof theory. His solution reads roughly as follows. Mathematics is about how to generate synthetic a priori knowledge by acting within some calculus. This definition does not seem to be a promising starting point, because in this way a very controversial claim becomes true by definition. However, Wille's strategy is to make sense of his definition during the course of his argument and to show that the definition is appropriate regarding research that is commonly taken to be mathematics.The second part of the book explains what ‘acting within some calculus’ amounts to. In Wille's view, mathematics should be characterized in …

Statistical physicists assume a probability distribution over micro-states to explain thermodynamic behavior. The question of this paper is whether these probabilities are part of a best system and can thus be interpreted as Humean chances. I consider two Boltzmannian accounts of the Second Law, viz. a globalist and a localist one. In both cases, the probabilities fail to be chances because they have rivals that are roughly equally good. I conclude with the diagnosis that well-defined micro-probabilities under-estimate the robust character of explanations in statistical physics.

What is it to judge something to be a natural end? And what objects may properly be judged natural ends? These questions pose a challenge, because the predicates “natural” and “end” seemingly can not be instantiated at the same time – at least given some Kantian assumptions. My paper defends the thesis that Kant’s “Critique of Teleological Judgment”, nevertheless, provides a sensible account of judging something a natural end. On the account, a person judges an object O a natural end, if she thinks that the parts of O cause O and if she is committed to approach O in a top-down manner, as if the parts were produced in view of the whole. The account is non-realist, because it involves a commitment. With the account comes a characterization that provides necessary and sufficient conditions on objects that may properly be judged natural ends. My paper reconstructs the argument in CTJ, §§64-65 where the account and the characterization are derived

In physics, objects are often assigned vector characteristics such as a specific velocity. How can this be understood from a metaphysical point of view – is assigning an object a vector characteristic to attribute it an intrinsic property? As a short review of Newtonian, special relativistic and general relativistic physics shows, if we wish to assign some object a vector characteristic, we have to relate it to something – call it S. If S is to be different from the original object – and I argue for this assumption – then having the specific vector characteristic is not an intrinsic property under different readings of “intrinsic”. For instance, I argue that lonely objects with different orientations do not constitute metaphysically distinct possibilities. There are, however, difficulties in applying the loneliness test, and they concern the role of the space‐time

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.

We develop a utilitarian framework to assess different decision rules for the European Council of Ministers. The proposals to be decided on are conceptualized as utility vectors and a probability distribution is assumed over the utilities. We first show what decision rules yield the highest expected utilities for different means of the probability distri- bution. For proposals with high mean utility, simple bench- mark rules (such as majority voting with proportional weights) tend to outperform rules that have been proposed in the political arena. For proposals with low mean utility, it is the other way round. We then compare the expected utilities for smaller and larger countries and look for Pareto- dominance relations. Finally, we provide an extension of the model, discuss its restrictions, and compare our approach with assessments of decision rules that are based on the Penrose measure of voting power.

In his Critique of Pure Reason, in the chapter on the antinomy of pure reason, Kant not only argues that aprioristic cosmology is doomed to failure; he also implies that empirical knowledge about the universe is impossible. Today, such a negative verdict about the possibility of cosmological knowledge seems implausible because physical cosmology has made substantial progress. In particular, the spatiotemporal extension of the universe now seems a matter of empirical investigation in which models figure centrally. But I think it is worth considering the possibility that Kant got something right and that he offers insights that can help us to better understand problems in present-day cosmology. In this article, I explore a striking coincidence: according to both Kant and current wisdom, cosmology faces a serious underdetermination problem regarding the spatiotemporal extension of the world. As a closer analysis reveals, however, Kant and modern cosmology differ on the reasons why underdetermination arises. In current cosmology, underdetermination follows from laws that are knowable a posteriori, and not only from the very idea of cosmological knowledge, as Kant would have it. This suggests that the current underdetermination problem is not fully a Kantian one.

The choice of a social decision rule for a federal assembly affects the welfare distribution within the federation. But which decision rules can be recommended on welfarist grounds? In this paper, we focus on two welfarist desiderata, viz. (i) maximizing the expected utility of the whole federation and (ii) equalizing the expected utilities of people from different states in the federation. We consider the European Union as an example, set up a probabilistic model of decision making and explore how different decision rules fare with regard to the desiderata. We start with a default model, where the interests, and therefore the votes of the different states are not correlated. This default model is then abandoned in favor of models with correlations. We perform computer simulations and find that decision rules with a low acceptance threshold do generally better in terms of desideratum (i), whereas the rules presented in the Accession Treaty and in the (still unratified) Constitution of the European Union tend to do better in terms of desideratum (ii). The ranking obtained regarding desideratum (i) is fairly stable across different correlation patterns.

Ever since work of Paul Feyerabend, Russell Hanson and Thomas Kuhn in the 1960s, the thesis of the theory-ladenness of scientific observation has attracted much attention both in the philosophy and the sociology of science. The main concern has always been epistemic. It was argued –or feared– that if scientific observations depend on prevalent theories, an objective empirical test of theories and hypotheses by independent observation and experience is impossible. This suggests that theories might appear to be well confirmed by observation, and yet it is not likely that they are largely true or empirically adequate. While some philosophers like Ian Hacking have argued that serious theory-dependence is less common than often assumed, sociologists such as David Bloor, Stephen Shapin, Karin Knorr-Cetina or Harry Collins have based their constructivist programs for the sociology of science on strong claims of theory-ladenness.

Computer simulations are often claimed to be opaque and thus to lack transparency. But what exactly is the opacity of simulations? This paper aims to answer that question by proposing an explication of opacity. Such an explication is needed, I argue, because the pioneering definition of opacity by P. Humphreys and a recent elaboration by Durán and Formanek are too narrow. While it is true that simulations are opaque in that they include too many computations and thus cannot be checked by hand, this doesn’t exhaust what we might want to call the opacity of simulations. I thus make a fresh start with the natural idea that the opacity of a method is its disposition to resist knowledge and understanding. I draw on recent work on understanding and elaborate the idea by a systematic investigation into what type of knowledge and what type of understanding are required if opacity is to be avoided and why the required sort of understanding, in particular, is difficult to achieve. My proposal is that a method is opaque to the degree that it’s difficult for humans to know and to understand why its outcomes arise. This proposal allows for a comparison between different methods regarding opacity. It further refers to a kind of epistemic access that is important in scientific work with simulations.