From the beginning of chaos research until today, the unpredictability of chaos has been a central theme. It is widely believed and claimed by philosophers, mathematicians and physicists alike that chaos has a new implication for unpredictability, meaning that chaotic systems are unpredictable in a way that other deterministic systems are not. Hence, one might expect that the question ‘What are the new implications of chaos for unpredictability?’ has already been answered in a satisfactory way. However, this is not the (...) case. I will critically evaluate the existing answers and argue that they do not fit the bill. Then I will approach this question by showing that chaos can be defined via mixing, which has never before been explicitly argued for. Based on this insight, I will propose that the sought-after new implication of chaos for unpredictability is the following: for predicting any event, all sufficiently past events are approximately probabilistically irrelevant. (shrink)

A common type of argument against the existence of God is to argue that certain essential features associated with the existence of God are inconsistent with certain other features to be found in the actual world. for an analysis of the different ways to deploy the term “God” in philosophical and theological discourse and for an analysis of the logical form of arguments for and against the existence of God.) A recent example of this type of argument against the existence (...) of God is based on the assumption that there are random processes or chancy states of affairs in the actual world that contradict God being absolute sovereign over his creation: Chancy states of affairs are said to entail a denial of divine providence or omniscience. argues that “classical Big Bang cosmology is inconsistent with theism due to the unpredictable nature of the Big Bang singularity.”) More often than not, however, this apparent conflict is formulated only intuitively and lacks sufficient conceptual clarification of the crucial terms involved. As a consequence, it is seldom clear where the conflict really lies. In what follows, I first provide a brief analysis of chance and randomness before I turn to cosmological and evolutionary arguments against the existence of God that in some way or other are based on chance and randomness. I end by way of comparing three popular conceptions of God as regards their ability to deal with God’s relation to a world of chance and randomness. Neither classical theism, nor open theism, nor indeed process panentheism has difficulties in accounting for God’s relation to a world of chance and randomness. (shrink)

In philosophical logic and metaphysics there is a long-standing debate around the most appropriate structures to represent indeterministic scenarios concerning the future. We reconstruct here such a debate in a computational setting, focusing on the fundamental difference between moment-based and history-based structures. Our presentation is centered around two versions of an indeterministic scenario in which a programmer wants a machine to perform a given task at some point after a specified time. One of the two versions includes an assumption about (...) the future behaviour of the machine that cannot be encoded in any programming instruction; such version has models over history-based structures but no model over a moment-based structure. Therefore, our work adds a new stance to the debate: moment-based structures can be said to rule out certain indeterministic scenarios that are computationally unfeasible. (shrink)

When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. Making this suggestion both precise (...) and compelling is surprisingly difficult. Toward this end, I propose two fundamental rationales for randomization, drawing upon diverse ideas and results from the wider theory of computation. The first unifies common intuitions in favour of randomization from the aforementioned disciplines. The second introduces a deep connection between randomization and memory: access to a randomizing device is provably helpful for an agent burdened with a finite memory. Aside from fit with ordinary intuitions about rational action, the two rationales also make sense of empirical observations in the biological world. Indeed, random behaviour emerges more or less where it should, according to the proposal. (shrink)

The Principle of Indifference is a central element of the ‘classical’ conception of probability, but, for all its strong intuitive appeal, it is widely believed that it faces a devastating objection: the so-called (by Poincare´) ‘Bertrand paradoxes’ (in essence, cases in which the same probability question receives different answers). The puzzle has fascinated many since its discovery, and a series of clever solutions (followed promptly by equally clever rebuttals) have been proposed. However, despite the long-standing interest in this problem, an (...) important assumption, necessary for its generation, has been overlooked. My aim in this paper is to identify this assumption. Since what it claims turns out to be prima facie problematic, I will urge that the burden of proof now shifts to the objectors to PI; they have to provide reasons why this assumption holds. (shrink)

Early work on the frequency theory of probability made extensive use of the notion of randomness, conceived of as a property possessed by disorderly collections of outcomes. Growing out of this work, a rich mathematical literature on algorithmic randomness and Kolmogorov complexity developed through the twentieth century, but largely lost contact with the philosophical literature on physical probability. The present chapter begins with a clarification of the notions of randomness and probability, conceiving of the former as a property of a (...) sequence of outcomes, and the latter as a property of the process generating those outcomes. A discussion follows of the nature and limits of the relationship between the two notions, with largely negative verdicts on the prospects for any reduction of one to the other, although the existence of an apparently random sequence of outcomes is good evidence for the involvement of a genuinely chancy process. (shrink)

John Hawthorne in a recent paper takes issue with Lewisian accounts of counterfactuals, when relevant laws of nature are chancy. I respond to his arguments on behalf of the Lewisian, and conclude that while some can be rebutted, the case against the original Lewisian account is strong.I develop a neo-Lewisian account of what makes for closeness of worlds. I argue that my revised version avoids Hawthorne’s challenges. I argue that this is closer to the spirit of Lewis’s first (non-chancy) proposal (...) than is Lewis’s own suggested modification. (shrink)

In artificial intelligence (AI), a number of criticisms were raised against the use of probability for dealing with uncertainty. All these criticisms, except what in this article we call the non-adequacy claim, have been eventually confuted. The non-adequacy claim is an exception because, unlike the other criticisms, it is exquisitely philosophical and, possibly for this reason, it was not discussed in the technical literature. A lack of clarity and understanding of this claim had a major impact on AI. Indeed, mostly (...) leaning on this claim, some scientists developed an alternative research direction and, as a result, the AI community split in two schools: a probabilistic and an alternative one. In this article, we argue that the non-adequacy claim has a strongly metaphysical character and, as such, should not be accepted as a conclusive argument against the adequacy of probability. (shrink)

"Chance" crops up all over philosophy, and in many other areas. It is often assumed -- without argument -- that chances are probabilities. I explore the extent to which this assumption is really sanctioned by what we understand by the concept of chance.

This article focuses on three recent discussions on determinism in the philosophy of science. First, determinism and predictability will be discussed. Then, second, the paper turns to the topic of determinism, indeterminism, observational equivalence and randomness. Finally, third, there will be a discussion about deterministic probabilities. The paper will end with a conclusion.

John Hawthorne in a recent paper takes issue with Lewisian accounts of counterfactuals, when relevant laws of nature are chancy. I respond to his arguments on behalf of the Lewisian, and conclude that while some can be rebutted, the case against the original Lewisian account is strong. I develop a neo-Lewisian account of what makes for closeness of worlds. I argue that my revised version avoids Hawthorne's challenges. I argue that this is closer to the spirit of Lewis's first (non-chancy) (...) proposal than is Lewis's own suggested modification. (shrink)

On the observational equivalence of continuous-time deterministic and indeterministic descriptions Content Type Journal Article Pages 193-225 DOI 10.1007/s13194-010-0011-5 Authors Charlotte Werndl, Department of Philosophy, Logic and Scientific Method, London School of Economics, Houghton Street, London, WC2A 2AE UK Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 2.

Although widely investigated and used in psychology, the concept of randomness is beset with philosophical and practical difficulties. In this paper, I propose a resolution to a long-standing problem in psychological research by arguing that the inability to comprehend and produce random behavior is not caused by a defect on the part of the observer but is a consequence of conceptual confusion. Randomness describes a state of high complexity which defies analysis and understanding. The well-known biases in predictive behavior are (...) not caused by the observers’ inability to comprehend randomness but reflect a natural pattern-seeking response to high-complexity situations. Further, I address the circularity at the heart of the randomness debate. Replacing randomness with complexity in psychology and cognitive science would eliminate many of the current problems associated with defining, investigating and using this elusive term. (shrink)

This dissertation shows how initial conditions play a special role in the explanation of contingent and irregular outcomes, including, in the form of geographic context, the special case of uneven development in the social sciences. The dissertation develops a general theory of this role, recognizes its empirical limitations in the social sciences, and considers how it might be applied to the question of uneven development. The primary purpose of the dissertation is to identify and correct theoretical problems in the study (...) of uneven development; it is not intended to be an empirical study. Chapter 1 introduces the basic problem, and discusses why it has become especially salient in debates concerning uneven development. Chapter 2 develops an argument for the importance of initial conditions in the philosophy of science, developed specifically in the context of the Bhaskar/Cartwright ‘open systems’ (and by extension, ‘exogenous factor’) emphasis on the ubiquity of contingency in the universe and rejection of explanation based on laws of nature (regularity accounts) of causation. Chapter 3 makes three claims concerning the concept of contingency, especially as related to the study of society: 1) that there are eight distinct uses of the word contingency, and its many meanings are detrimental to clarity of discussion and thought in history and the social sciences; 2) that it is possible to impose some order on these different uses through developing a classification of contingency into three types based on assumptions concerning possible worlds and determinism; 3) that one of the classes is a special use of the word without relevance to the social sciences, while the two remaining classes are nothing more than a variety of the ‘no hidden factors’ argument in the debate on indeterminism and determinism (and thus related to the concept of spacetime trajectories caused by initial conditions and the interference of these in the form of ‘exogenous factors’ with ‘open systems’). Chapter 4 The concept of explanation based on initial conditions together with laws of nature is widely associated with determinism. In the social sciences determinism has frequently been rejected due to the moral dilemmas it is perceived as presenting. Chapter 4 considers problems with this view. Chapter 5 considers attitudes among geographers, economists, and historians towards using geographic factors as initial conditions in explanation and how they might acceptably be used, in particular their role in ‘anchoring’ aspatial theories of social processes to real-world distributions. Chapter 6 considers the relationship of the statistical methods common in development studies with the trend towards integrating geographical factors into econometric development studies. It introduces the statistical argument on ‘apparent populations’ that arrives at conclusions concerning determinism consistent with Chapters 2 and 3 of the dissertation. The need for the visual interpretation of data with descriptive statistics and maps and their utility in the study of uneven development is discussed with a number of examples. Chapter 7 applies these concepts to the ‘institutions versus geography’ debate in development studies, using Acemoglu, Johnson and Robinson’s 2002 ‘reversal of fortune’ argument as a primary example. Chapter 8 considers possible directions for future work, both theoretical and empirical. Chapter 9 concludes with a discussion of additional possible objections to the use of initial conditions as exogenous factors in explanation. (shrink)

1. Characterizing randomness. Consider a physical process that, if suitably idealized, generates an indefinite sequence of independent random bits. One such process might be radioactive decay of a lump of uranium whose mass is kept at just the level needed to ensure that the probability is one-half that no alpha particle is emitted in the nth microsecond of the experiment. Let us think of the bits as drawn from {0, 1} and denote the resulting sequence by x with coordinates x0, (...) x1, . . .. Now wouldn’t it be odd if there were a computer program P with the following property? (shrink)

In 1866, the young John Venn published The Logic of Chance, motivated largely by the desire to correct what he saw as deep fallacies in the reasoning of historical determinists such as Henry Buckle and in the optimistic heralding of a true social science by Adolphe Quetelet. Venn accepted the inevitable determinism implied by the physical sciences, but denied that the stable social statistics cited by Buckle and Quetelet implied a similar determinism in human actions. Venn maintained that probability statements (...) were intelligible solely as projections of the ultimate frequency of an outcome in an unlimited series of trials and therefore led to no inferences about free will. An issue here was Venn's claim that although the aggregate probability may be stable, the individual events were completely irregular and, in fact, displayed randomness. Venn's concept of randomness was really apparent, or pseudo-, randomness, which could be totally determined. Ironically, Venn's frequentist position was very useful to the growing field of statistics, which could develop correlations and predictive models empirically without having to address implications for personal freedom or fatalism. (shrink)

This article explores the connection between objective chance and the randomness of a sequence of outcomes. Discussion is focussed around the claim that something happens by chance iff it is random. This claim is subject to many objections. Attempts to save it by providing alternative theories of chance and randomness, involving indeterminism, unpredictability, and reductionism about chance, are canvassed. The article is largely expository, with particular attention being paid to the details of algorithmic randomness, a topic relatively unfamiliar to philosophers.