There are various equivalent formulations of the Church-Turing thesis. A common one is that every effective computation can be carried out by a Turing machine. The Church-Turing thesis is often misunderstood, particularly in recent writing in the philosophy of mind.

Lectures, scientific papers, top secret wartime material, correspondence, and broadcasts are introduced and set in context by Jack Copeland, Director of the Turing Archive for the History of Computing."--Jacket.

Que serait une exposition qui, au lieu de prendre place dans un musée ou dans une galerie, prendrait place au cinéma? (un projet de Mathieu Copeland, avec Chantal Akerman, Peter Downsbrough, Liam Gillick, John Giorno, Philippe Grandrieux, Isidore Isou, Philippe-Alain Michaud, Meredith Monk, Lee Ranaldo, Susan Stenger, Alan Vega, Jacques Villeglé, Lawrence Weiner, Apichatpong Weerasethakul...).

That there is a “crisis of peer review” at the moment is not in dispute, but sufficient attention has not yet been paid to the normative potential that lies in current calls for reform. In contrast to approaches to “fixing” the problems in peer review, which tend to maintain the status quo in terms of professionalising opportunities, this paper addresses the needs of philosophers and how peer‐review reform can be an opportunity to improve the academic discipline of philosophy, whereby progress (...) is understood as making the discipline more fair to the global academic community and more conducive to the flourishing of academic philosophers. The paper evaluates recent categories of relevant norms and correlating reforms. In conclusion, it recommends that philosophy pursue the norms of transparency and democracy explicitly when proposing peer‐review reform and suggest that proposals for forum‐based models of peer review are most likely to support those norms. (shrink)

Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question ‘What does a particular neuronal system do?’ is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends (...) some support to the idea that a single neuronal structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation. (shrink)

An increasingly popular solution to the anti-scientific climate rising on social media platforms has been the appeal to more critical thinking from the user's side. In this paper, we zoom in on the ideal of critical thinking and unpack it in order to see, specifically, whether it can provide enough epistemic agency so that users endowed with it can break free from enclosed communities on social media (so called epistemic bubbles). We criticise some assumptions embedded in the ideal of critical (...) thinking online and, instead, we propose that a better way to understand the virtuous behaviour at hand is as critical engagement, namely a mutual cultivation of critical skills among the members of an epistemic bubble. This mutual cultivation allows members within an epistemic bubble (in contrast, as we will show, with the authority-based models of epistemic echo chambers) to become more autonomous critical thinkers by cultivating self-trust. We use the model of relational autonomy as well as resources from work on epistemic self-trust and epistemic interdependence to develop an explanatory framework, which in turn may ground rules for identifying and creating virtuous epistemic bubbles within the environments of social media platforms. (shrink)

This volume brings together for the first time the diverse threads within the growing field of serendipity research, to reflect both on the origins of this emerging field within different disciplines as well as its increasing influence as its own field with foundational texts and emerging practices. The phenomenon of serendipity has been described in many ways since Horace Walpole initially coined the term in 1754 to categorize those discoveries that happen by “both accidents and sagacity”. This book offers a (...) sampling of perspectives from experts in serendipity research from organizational studies, management theory, information science and library studies, psychology, literature, computer science, social science, ethics, and the history and philosophy of science. Considerations about the importance and role of serendipity are being raised now across science (both empirical and theoretical) as well as practice (from art and innovation to leadership and governance), with ever more eyes looking closer at its significance in human history and the likelihood it will play a key, while unpredictable, role in forming our future. Serendipity Science represents an emerging, and also important and potentially necessary field of study, if we are to deal well as a society with our complex times and uncertain future. (shrink)

Alan Turing, pioneer of computing and WWII codebreaker, is one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich in philosophical and logical insight.

Serendipity is fundamental to science. This quirky and intriguing phenomenon permeates across scientific disciplines, including the medical sciences, psychological sciences, management and organizational sciences, innovation science, philosophy and library and information sciences. Why is it so ubiquitous? Because of what it facilitates and catalyzes: scientific discoveries from velcro to Viagra, innovation of all forms, unexpected encounters of useful information, novel and important ideas, and deep reflection on how we, as individuals, organizations, communities and societies can take leaps forwards by seizing (...) unexpected opportunities and ‘making our own luck.’. (shrink)

The prelims comprise: The Birth of the Modern Computer What is a Turing Machine? The Basic Operations of a Turing Machine Human Computation The Church—Turing Thesis Beyond the Universal Turing Machine Misunderstandings of the Church—Turing Thesis: The Limits of Machines Conclusion.

Michel Foucault's concept of normalisation is taken as a basis to explore the factors involved in the identification of dull, deficient and backward pupils in British Elementary Education between 1870 and 1914. Normalisation consists of the five processes of comparison, differentiation, hierarchisation, homogenisation and exclusion. These processes operate through dividing practices which distribute groups socially and are supported in this work by scientific ideas. In this instance, the norm of the intellect is the basis of the dividing practices. The empirical (...) focus opens with an examination of the main features of Elementary education. It then moves to consider the deliberations of the Royal Commission on the Blind, Deaf and Dumb, etc and those of the Departmental Committee on Defective and Epileptic Children. The analysis concludes with a consideration of the consequences of the Elementary Education Act, 1899, and its effects up until 1914. (shrink)

Agouti expression during the middle portion of the mouse hair growth cycle induces melanocytes to synthesize yellow instead of black pigment, generating black hairs with a yellow band. Dominant agouti alleles increase the amount of yellow pigment in the coat and are associated with pleiotropic effects including obesity, diabetes and increased tumor susceptibility. Four dominant agouti alleles (Aiapy, Aiy, Asy and Avy) were recently shown to result from insertions that cause ubiquitous expression of chimeric transcripts encoding a wild‐type agouti protein(1,2). (...) Three insertions were identified as intracisternal A‐particles, which helps explain the variable coat colors and parental imprinting effects associated with some dominat agouti alleles. (shrink)

The concept of social reproduction of sets of advantages and disadvantages together with that of status group, is used to explore the evidence and thinking presented in the Royal Commission on the Blind, the Deaf and Dumb, etc. regarding the education of children with disabilities in 1889. Even though the evidence was ambiguous, models for the education of children with disabilities were laid down. Integration into mainstream elementary schools was recommended for the blind. Recommendations for deaf children were divided in (...) allegiance with belief in the principles of either oralism or signing. The largest group numerically received the least attention in the Commission. The idea of feeble-minded children as a product of social, economic and educational circumstances had its champion but was overwhelmed by the acceptance of the doctrine of the innate characteristics of the child's mind identifiable by medical science. (shrink)

Famous examples of conceivability arguments include (i) Descartes’ argument for mind-body dualism, (ii) Kripke's ‘modal argument’ against psychophysical identity theory, (iii) Chalmers’ ‘zombie argument’ against materialism, and (iv) modal versions of the ontological argument for theism. In this paper, we show that for any such conceivability argument, C, there is a corresponding ‘mirror argument’, M. M is deductively valid and has a conclusion that contradicts C's conclusion. Hence, a proponent of C—henceforth, a ‘conceivabilist’—can be warranted in holding that C's premises (...) are conjointly true only if she can find fault with one of M's premises. But M's premises are modelled on a pair of C's premises. The same reasoning that supports the latter supports the former. For this reason, a conceivabilist can repudiate M's premises only on pain of severely undermining C's premises. We conclude on this basis that all conceivability arguments, including each of (i)–(iv), are fallacious. (shrink)

To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of computation against (...) a difficulty that has persistently been raised against it, and undercuts various objections that have been made to the computational theory of mind. (shrink)

Parents whose child is diagnosed with a serious disease such as trisomy 18 first rely on the medical community for an accurate description and prognosis. In the case of trisomy 18, however, many families are told the disease is “incompatible with life” even though some children with the condition live for several years. This paper considers parents’ response to current medical discourse concerning trisomy 18 by examining blogs written by the parents of those diagnosed. Using interpretive humanistic reading and foregrounding (...) Cathryn Molloy’s recuperative ethos theory, we find that parents demonstrate recuperative ethos in response to physicians’ descriptions of trisomy 18, particularly in rhetoric addressing survival, medicalized language, and religious and/or spiritual rhetoric. We argue that, by using language such as “incompatible with life,” physicians distance themselves from families, creating not care, but the very gulf that requires recuperation. We conclude that medical professionals would do well to engage with the trisomy 18 community—including learning from blogs and online forums— employ palliative care practices, and seek more accurate, descriptive language that is compatible with care. (shrink)

While resilience is a major concept in development, climate adaptation, and related domains, many doubts remain about how to interpret this term, its relationship with closely overlapping terms, or its normativity. One major view is that, while resilience originally was a descriptive concept denoting some adaptive property of ecosystems, subsequent applications to social contexts distorted its meaning and purpose by framing it as a transformative and normative quality. This article advances an alternative philosophical account based on the scrutiny of C.S. (...) Holling’s original work on resilience. We show that resilience had a central role among Holling’s proposals for reforming environmental science and management, and that Holling framed resilience as an ecosystem’s capacity of absorbing change and exploiting it for adapting or evolving, but also as the social ability of maintaining and opportunistically exploiting that natural capacity. Resilience therefore appears as a transformative social-ecological property that is normative in three ways: as an intrinsic ecological value, as a virtue of organizations or management styles, and as a virtuous understanding of human–nature relations. This interpretation accounts for the practical relevance of resilience, clarifies the relations between resilience and related terms, and is a firm ground for further normative work on resilience. (shrink)

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. (...) John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

This article traces the development of possible worlds semantics through the work of: Wittgenstein, 1913-1921; Feys, 1924; McKinsey, 1945; Carnap, 1945-1947; McKinsey, Tarski and Jónsson, 1947-1952; von Wright, 1951; Becker, 1952; Prior, 1953-1954; Montague, 1955; Meredith and Prior, 1956; Geach, 1960; Smiley, 1955-1957; Kanger, 1957; Hintikka, 1957; Guillaume, 1958; Binkley, 1958; Bayart, 1958-1959; Drake, 1959-1961; Kripke, 1958-1965.

The host actin nucleation machinery is subverted by many bacterial pathogens to facilitate their entry, motility, replication, and survival. The majority of research conducted in the past primarily focused on exploitation of a host actin nucleator, the Arp2/3 complex, by bacterial pathogens. Recently, new studies have begun to explore the role of formins, another family of host actin nucleators, in bacterial pathogenesis. This review provides an overview of recent advances in the study of the exploitation of the Arp2/3 complex and (...) formins by bacterial pathogens. Secreted bacterial effector proteins seem to manipulate the regulation of these actin nucleators or functionally mimic them to drive bacterial entry, motility and survival within host cells. An enhanced understanding of how formins are exploited will provide us with greater insight into how a fundamental eurkaryotic cellular process is utilized by bacteria and will also advance our knowledge of host‐pathogen interactions. (shrink)

This article contributes to recent work on justice in resilience-based projects for climate adaptation. At present, the model commonly used for guiding normative reflection in this domain is the tripartite model of justice, whereby justice is seen as comprising distributive, procedural and recognitional aspects. After discussing some conceptual problems and practical shortcomings of this model, we propose an alternative model with six forms of justice or kinds of justice demands: distributive, procedural, intergenerational, restorative and retributive justice, and justice in system (...) outcomes. We also illustrate some advantages of this model with respect to representative accounts of the tripartite model. (shrink)

Abstract‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science (...) as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

A survey of the field of hypercomputation, including discussion of a variety of objections.

‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science (...) as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

Turing''s test has been much misunderstood. Recently unpublished material by Turing casts fresh light on his thinking and dispels a number of philosophical myths concerning the Turing test. Properly understood, the Turing test withstands objections that are popularly believed to be fatal.

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John (...) Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

Accelerating Turing machines have attracted much attention in the last decade or so. They have been described as “the work-horse of hypercomputation” (Potgieter and Rosinger 2010: 853). But do they really compute beyond the “Turing limit”—e.g., compute the halting function? We argue that the answer depends on what you mean by an accelerating Turing machine, on what you mean by computation, and even on what you mean by a Turing machine. We show first that in the current literature the term (...) “accelerating Turing machine” is used to refer to two very different species of accelerating machine, which we call end-stage-in and end-stage-out machines, respectively. We argue that end-stage-in accelerating machines are not Turing machines at all. We then present two differing conceptions of computation, the internal and the external, and introduce the notion of an epistemic embedding of a computation. We argue that no accelerating Turing machine computes the halting function in the internal sense. Finally, we distinguish between two very different conceptions of the Turing machine, the purist conception and the realist conception; and we argue that Turing himself was no subscriber to the purist conception. We conclude that under the realist conception, but not under the purist conception, an accelerating Turing machine is able to compute the halting function in the external sense. We adopt a relatively informal approach throughout, since we take the key issues to be philosophical rather than mathematical. (shrink)

Accelerating Turing machines are Turing machines of a sort able to perform tasks that are commonly regarded as impossible for Turing machines. For example, they can determine whether or not the decimal representation of contains n consecutive 7s, for any n; solve the Turing-machine halting problem; and decide the predicate calculus. Are accelerating Turing machines, then, logically impossible devices? I argue that they are not. There are implications concerning the nature of effective procedures and the theoretical limits of computability. Contrary (...) to a recent paper by Bringsjord, Bello and Ferrucci, however, the concept of an accelerating Turing machine cannot be used to shove up Searle's Chinese room argument. (shrink)

What is the role of chance in scientific discovery? And, more to the point, if chance plays a key role in scientific discovery, what room is left for reason? These are grounding questions in the debates, for instance, over whether there is a distinction to be made between discovery and justification in science, and whether innate genius must play a role in discovery or if there exists some method that can be taught to anyone. While the role of chance has (...) been discussed throughout the history of science, it has resurfaced in recent debates over how science should be funded, and particularly in the field of biomedical research. The word serendipity, for example, has become increasingly... (shrink)

It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both the behaviour of the (...) network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)

Turing’s analysis of computability has recently been challenged; it is claimed that it is circular to analyse the intuitive concept of numerical computability in terms of the Turing machine. This claim threatens the view, canonical in mathematics and cognitive science, that the concept of a systematic procedure or algorithm is to be explicated by reference to the capacities of Turing machines. We defend Turing’s analysis against the challenge of ‘deviant encodings’.Keywords: Systematic procedure; Turing machine; Church–Turing thesis; Deviant encoding; Acceptable encoding; (...) Turing’s analysis of computability; Turing’s Notational Thesis. (shrink)

We describe an emerging field, that of nonclassical computability and nonclassical computing machinery. According to the nonclassicist, the set of well-defined computations is not exhausted by the computations that can be carried out by a Turing machine. We provide an overview of the field and a philosophical defence of its foundations.

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)