I explore a Davidsonian proposal for the reconciliation of two theses. One is the supervenience of the mental on the physical, the other is the anomalism of the mental. The gist of the proposal is that supervenience and anomalism are theses about interpretation. Starting with supervenience, the claim is that it should not be understood in terms of deeper metaphysical relations, but as a constraint on the relations between the applications of physical and mental predicates. Regarding anomalism, the claim is (...) that psychophysical laws have to satisfy certain counterfactual cases, in which an interpreter evaluates her past attributions in the light of new pieces of evidence. The proposed reconciliation is that supervenience entails that an interpreter will always attribute the same mental predicates to two individuals with the same physical states. However, supervenience does not imply that an interpreter cannot revise her past attributions to the two individuals. (shrink)

There is an intensive discussion nowadays about the meaning of effective computability, with implications to the status and provability of the Church–Turing Thesis (CTT). I begin by reviewing what has become the dominant account of the way Turing and Church viewed, in 1936, effective computability. According to this account, to which I refer as the Gandy–Sieg account, Turing and Church aimed to characterize the functions that can be computed by a human computer. In addition, Turing provided a highly convincing argument (...) for CTT by analyzing the processes carried out by a human computer. I then contend that if the Gandy–Sieg account is correct, then the notion of effective computability has changed after 1936. Today computer scientists view effective computability in terms of finite machine computation. My contention is supported by the current formulations of CTT, which always refer to machine computation, and by the current argumentation for CTT, which is different from the main arguments advanced by Turing and Church. I finally turn to discuss Robin Gandy's characterization of machine computation. I suggest that there is an ambiguity regarding the types of machines Gandy was postulating. I offer three interpretations, which differ in their scope and limitations, and conclude that none provides the basis for claiming that Gandy characterized finite machine computation. (shrink)

Iris Marion Young (1949-2006) was one of the most influential and innovative political theorists of her generation who had a significant impact on a wide range of topics such as democratic theory, feminist theory, and justice. She bridged many longstanding divides among political theorists, engaging in Continental and critical theory, but also insisting on the importance of normative argument: her corpus stands as a testament to the fruitfulness of engaging in both abstract theory and the 'real world' of everyday (...) politics. This volume spans the several decades of her work, illustrating her intellectual development over time through three major areas of innovation: Gender: Maintaining that gender is both conceptually and politically meaningful, Young theorized gender in terms of structures that, in combination, position different people we call "women" in different ways, such that some women have some structures in common, without all women sharing all gendered structures in common. Justice: Young's early writings on a critical theory of justice evolved in her later and posthumously published works where she developed an account of justice that brought together her theorization of structure with her concern to respond to contemporary claims of injustice. The Politics of Difference: Young rejected universal and abstract theories of justice and maintained that justice instead required attending to the experiences of people marked by difference. (shrink)

Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform. The representation and algorithmic perspective offers an understanding of how information about the environment is (...) encoded within the mechanism and what are the patterns of organization that enable the parts of the mechanism to produce the phenomenon. The implementation perspective yields an understanding of the neural details of the mechanism and how they constrain function and algorithms. Once we adequately characterize the distinct role of each level of analysis, it is fairly straightforward to see how they relate. (shrink)

It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are the (...) components of the explanandum phenomenon and their causal organization. Moreover, each component in one level of mechanism is constituted and explained by components of an underlying level of mechanism. Hence, it seems, computational variables and functions cannot be mechanistically explained by the medium-dependent states and properties that implement them. How then, do the computational and the implementational integrate to create the mechanistic hierarchy? After explicating the general problem, we further demonstrate it through a concrete example, of reinforcement learning, in the cognitive and neural sciences. We then examine two possible solutions. On one solution, the mechanistic hierarchy embeds at the same levels computational and implementational properties. This picture fits with the view that computational explanations are mechanistic sketches. On the other solution, there are two separate hierarchies, one computational and another implementational, which are related by the implementation relation. This picture fits with the view that computational explanations are functional and autonomous explanations. It is less clear how these solutions fit with the view that computational explanations are full-fledged mechanistic explanations. Finally, we argue that both pictures are consistent with the reinforcement learning example, but that scientific practice does not align with the view that computational models are merely mechanistic sketches. (shrink)

Do newborns think-do they know that 'three' is greater than 'two'? Do they prefer 'right' to 'wrong'? What about emotions--do newborns recognize happiness or anger? If they do, then how are our inborn thoughts and feelings encoded in our bodies? Could they persist after we die? Going all the way back to ancient Greece, human nature and the mind-body link are the topics of age-old scholarly debates. But laypeople also have strong opinions about such matters. Most people believe, for example, (...) that newborn babies don't know the difference between right and wrong-such knowledge, they insist, can only be learned. For emotions, they presume the opposite-that our capacity to feel fear, for example, is both inborn and embodied. These beliefs are stories we tell ourselves about what we know and who we are. They reflect and influence our understanding of ourselves and others and they guide every aspect of our lives. In a twist that could have come out of a Greek tragedy, Berent proposes that our errors are our fate. These mistakes emanate from the very principles that make our minds tick: our blindness to human nature is rooted in human nature itself. An intellectual journey that draws on philosophy, anthropology, linguistics, cognitive science, and Berent's own cutting-edge research, The Blind Storyteller grapples with a host of provocative questions, from why we are so infatuated with our brains to what happens when we die. The end result is a startling new perspective on our humanity. (shrink)

The semantic view of computation is the claim that semantic properties play an essential role in the individuation of physical computing systems such as laptops and brains. The main argument for the semantic view rests on the fact that some physical systems simultaneously implement different automata at the same time, in the same space, and even in the very same physical properties. Recently, several authors have challenged this argument. They accept the premise of simultaneous implementation but reject the semantic conclusion. (...) In this paper, I aim to explicate the semantic view and to address these objections. I first characterize the semantic view and distinguish it from other, closely related views. Then, I contend that the master argument for the semantic view survives the counter-arguments against it. One counter-argument is that computational individuation is not forced to choose between the implemented automata but rather always picks out a more basic computational structure. My response is that this move might undermine the notion of computational equivalence. Another counter-argument is that while computational individuation is forced to rely on extrinsic features, these features need not be semantic. My reply is that the semantic view better accounts for these extrinsic features than the proposed non-semantic alternatives. (shrink)

What does it mean to say that an object or system computes? What is it about laptops, smartphones, and nervous systems that they are considered to compute, and why does it seldom occur to us to describe stomachs, hurricanes, rocks, or chairs that way? Though computing systems are everywhere today, it is very difficult to answer these questions. The book aims to shed light on the subject by arguing for the semantic view of computation, which states that computingsystems are always (...) accompanied by representations. This view is presented as an alternative to non-semantic views such as the mechanistic account of computation. (shrink)

In seinen Analysen des Bildbewusstseins begreift Edmund Husserl das Bild als eine Herausforderung phänomenologischen Fragens. Diese Herausforderung begründet sich durch seine spezifische Gegenstands- und Erfahrungsstruktur, die das Bild als ein besonderes unter den Phänomenen auszeichnet, als ein Phänomen, das einen Unterschied zwischen wirklicher und vorgestellter Welt einführt und hierin Differenzbewusstsein konstituiert. Vor allem mit Blick auf das Thema der Zeit erweist sich die Auseinandersetzung mit der differentiellen Natur des Bildes als folgenreich. Iris Laners systematische Studie widmet sich der Aufgabe, (...) den heuristischen Wert der philosophischen Auseinandersetzung mit dem Bild für die Beantwortung der komplexen Frage nach der Zeit in und nach der Phänomenologie zu bestimmen. Damit unterstreicht sie nicht nur die Bedeutung des Bildes als Phänomen, sondern erörtert dieses auch als grundlegendes Konzept des Denkens. (shrink)

According to Marr, a computational-level theory consists of two elements, the what and the why . This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: ( a ) that the Why element plays an explanatory role in computational-level theories, ( b ) that its goal is to explain why the computed function (specified by the What element) is appropriate for a given visual task, and ( c ) that the (...) explanation consists in showing that the functional relations between the representing cells are similar to the “external” mathematical relations between the entities that these cells represent. *Received September 2009; revised January 2010. †To contact the author, please write to: Departments of Philosophy and Cognitive Science, The Hebrew University, Jerusalem 91905, Israel; e-mail: shagrir@cc.huji.ac.il. (shrink)

The paper presents an extended argument for the claim that mental content impacts the computational individuation of a cognitive system (section 2). The argument starts with the observation that a cognitive system may simultaneously implement a variety of different syntactic structures, but that the computational identity of a cognitive system is given by only one of these implemented syntactic structures. It is then asked what are the features that determine which of implemented syntactic structures is the computational structure of the (...) system, and it is contended that these features are certain aspects of mental content. The argument helps (section 3) to reassess the thesis known as computational externalism, namely, the thesis that computational theories of cognition make essential reference to features in the individual's environment. It is suggested that the familiar arguments for computational externalism?which rest on thought experiments and on exegesis of Marr's theories of vision?are unconvincing, but that they can be improved. A reconstruction of the visex/audex thought experiment is offered in section 3.1. An outline of a novel interpretation of Marr's theories of vision is presented in section 3.2. The corrected arguments support the claim that computational theories of cognition are intentional. Computational externalism is still pending, however, upon the thesis that psychological content is extrinsic. (shrink)

The view that the brain is a sort of computer has functioned as a theoretical guideline both in cognitive science and, more recently, in neuroscience. But since we can view every physical system as a computer, it has been less than clear what this view amounts to. By considering in some detail a seminal study in computational neuroscience, I first suggest that neuroscientists invoke the computational outlook to explain regularities that are formulated in terms of the information content of electrical (...) signals. I then indicate why computational theories have explanatory force with respect to these regularities:in a nutshell, they underscore correspondence relations between formal/mathematical properties of the electrical signals and formal/mathematical properties of the represented objects. I finally link my proposal to the philosophical thesis that content plays an essential role in computational taxonomy. (shrink)

In Representation Reconsidered , William Ramsey suggests that the notion of structural representation is posited by classical theories of cognition, but not by the ‘newer accounts’ (e.g. connectionist modeling). I challenge the assertion about the newer accounts. I argue that the newer accounts also posit structural representations; in fact, the notion plays a key theoretical role in the current computational approaches in cognitive neuroscience. The argument rests on a close examination of computational work on the oculomotor system.

It is often indeterminate what function a given computational system computes. This phenomenon has been referred to as “computational indeterminacy” or “multiplicity of computations.” In this paper, we argue that what has typically been considered and referred to as the challenge of computational indeterminacy in fact subsumes two distinct phenomena, which are typically bundled together and should be teased apart. One kind of indeterminacy concerns a functional characterization of the system’s relevant behavior. Another kind concerns the manner in which the (...) abstract states are interpreted. We discuss the similarities and differences between the two kinds of computational indeterminacy, their implications for certain accounts of “computational individuation” in the literature, and their relevance to different levels of description within the computational system. We also examine the inter-relationships between our proposed accounts of the two kinds of indeterminacy and the main accounts of “computational implementation.”. (shrink)

In this classic work of feminist political thought, Iris Marion Young challenges the prevailing reduction of social justice to distributive justice.

The idea of perfection.--On God and Good.--The sovereignty of good over other concepts.

The mechanistic view of computation contends that computational explanations are mechanistic explanations. Mechanists, however, disagree about the precise role that the environment – or the so-called “contextual level” – plays for computational explanations. We advance here two claims: Contextual factors essentially determine the computational identity of a computing system ; this means that specifying the “intrinsic” mechanism is not sufficient to fix the computational identity of the system. It is not necessary to specify the causal-mechanistic interaction between the system and (...) its context in order to offer a complete and adequate computational explanation. While the first claim has been discussed before, the second has been practically ignored. After supporting these claims, we discuss the implications of our contextualist view for the mechanistic view of computational explanation. Our aim is to show that some versions of the mechanistic view are consistent with the contextualist view, whilst others are not. (shrink)

The mechanistic view of computation contends that computational explanations are mechanistic explanations. Mechanists, however, disagree about the precise role that the environment – or the so-called “contextual level” – plays for computational explanations. We advance here two claims: Contextual factors essentially determine the computational identity of a computing system ; this means that specifying the “intrinsic” mechanism is not sufficient to fix the computational identity of the system. It is not necessary to specify the causal-mechanistic interaction between the system and (...) its context in order to offer a complete and adequate computational explanation. While the first claim has been discussed before, the second has been practically ignored. After supporting these claims, we discuss the implications of our contextualist view for the mechanistic view of computational explanation. Our aim is to show that some versions of the mechanistic view are consistent with the contextualist view, whilst others are not. (shrink)

The mechanistic view of computation contends that computational explanations are mechanistic explanations. Mechanists, however, disagree about the precise role that the environment – or the so-called “contextual level” – plays for computational explanations. We advance here two claims: Contextual factors essentially determine the computational identity of a computing system ; this means that specifying the “intrinsic” mechanism is not sufficient to fix the computational identity of the system. It is not necessary to specify the causal-mechanistic interaction between the system and (...) its context in order to offer a complete and adequate computational explanation. While the first claim has been discussed before, the second has been practically ignored. After supporting these claims, we discuss the implications of our contextualist view for the mechanistic view of computational explanation. Our aim is to show that some versions of the mechanistic view are consistent with the contextualist view, whilst others are not. (shrink)

According to Marr, a computational-level theory consists of two elements, the what and the why. This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: that the Why element plays an explanatory role in computational-level theories, that its goal is to explain why the computed function is appropriate for a given visual task, and that the explanation consists in showing that the functional relations between the representing cells are similar to (...) the “external” mathematical relations between the entities that these cells represent. (shrink)

A key component of scientific inquiry, especially inquiry devoted to developing mechanistic explanations, is delineating the phenomenon to be explained. The task of delineating phenomena, however, has not been sufficiently analyzed, even by the new mechanistic philosophers of science. We contend that Marr’s characterization of what he called the computational level provides a valuable resource for understanding what is involved in delineating phenomena. Unfortunately, the distinctive feature of Marr’s computational level, his dual emphasis on both what is computed and why (...) it is computed, has not been appreciated in philosophical discussions of Marr. Accordingly we offer a distinctive account of CL. This then allows us to develop two important points about delineating phenomena. First, the accounts of phenomena that figure in explanatory practice are typically not qualitative but precise, formal or mathematical, representations. Second, delineating phenomena requires consideration of the demands the environment places on the mechanism—identifying, as Marr put it, the basis of the computed function in the world. As valuable as Marr’s account of CL is in characterizing phenomena, we contend that ultimately he did not go far enough. Determining the relevant demands of the environment on the mechanism often requires detailed empirical investigation. Moreover, often phenomena are reconstituted in the course of inquiry on the mechanism itself. (shrink)

Theodore Sider distinguishes two notions of global supervenience: strong global supervenience and weak global supervenience. He then discusses some applications to general metaphysical questions. Most interestingly, Sider employs the weak notion in order to undermine a familiar argument against coincident distinct entities. In what follows, I reexamine the two notions and distinguish them from a third, intermediate, notion (intermediate global supervenience). I argue that (a) weak global supervenience is not an adequate notion of dependence; (b) weak global supervenience does not (...) capture certain assumptions about coincidence relations; (c) these assumptions are better accommodated by the stronger notion of intermediate global supervenience; (d) intermediate global supervenience, however, is also not an adequate notion of dependence; and (e) strong global supervenience is an adequate notion of dependence. It also fits in with anti-individualism about the mental. It does not, however, serve to rebut arguments against coincident entities. (shrink)

I feel there are demons around.' Everyone is thinking about Julius King. For comfortable, long-married Hilda and Rupert, he is a mystery. For Morgan, Hilda's tormented sister, he is an obsession. For Morgan's abandoned husband, Tallis, he is the source of ruin. For Simon and Axel, deeply in love, he stirs up jealousy and unease. What is Julius thinking about? He's thinking about Hilda, Rupert, Morgan, Tallis, Simon and Axel, and they will not all survive his malevolent attention. WITH AN (...) INTRODUCTION BY GARTH GREENWELL VINTAGE CLASSICS MURDOCH: Funny, subversive, fearless and fiercely intelligent, Iris Murdoch was one of the great writers of the twentieth century. To celebrate her centenary Vintage Classics presents special editions of her greatest and most timeless novels. (shrink)

The decline of religion and ever increasing influence of science pose acute ethical issues for us all. Can we reject the literal truth of the Gospels yet still retain a Christian morality? Can we defend any 'moral values' against the constant encroachments of technology? Indeed, are we in danger of losing most of the qualities which make us truly human? Here, drawing on a novelist's insight into art, literature and abnormal psychology, Iris Murdoch conducts an ongoing debate with major (...) writers, thinkers and theologians—from Augustine to Wittgenstein, Shakespeare to Sartre, Plato to Derrida—to provide fresh and compelling answers to these crucial questions. (shrink)

Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the analog-model. The term ‘analog-model’ (...) does not mean continuous, non-discrete or non-digital. It means that the functional performance of the system simulates mathematical relations in some other system, between what is being represented. The brain-as-computer view is invoked to demonstrate that the internal cellular activity is appropriate for the pertinent information-processing task.Keywords: Computation; Computational neuroscience; Analog computers; Representation; Simulation. (shrink)

Iris Murdoch was one of the great philosophers and novelists of the twentieth century and The Sovereignty of Good is her most important and enduring philosophical work. She argues that philosophy has focused, mistakenly, on what it is right to do rather than good to be and that only by restoring the notion of ‘vision’ to moral thinking can this distortion be corrected. This brilliant work shows why Iris Murdoch remains essential reading: a vivid and uncompromising style, a (...) commitment to forceful argument, and a courage to go against the grain. With a foreword by Mary Midgley. (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)

Putnam (Representations and reality. MIT Press, Cambridge, 1988) and Searle (The rediscovery of the mind. MIT Press, Cambridge, 1992) famously argue that almost every physical system implements every finite computation. This universal implementation claim, if correct, puts at the risk of triviality certain functional and computational views of the mind. Several authors have offered theories of implementation that allegedly avoid the pitfalls of universal implementation. My aim in this paper is to suggest that these theories are still consistent with a (...) weaker result, which is the nomological possibility of systems that simultaneously implement different complex automata. Elsewhere I (Shagrir in J Cogn Sci, 2012) argue that this simultaneous implementation result challenges a computational sufficiency thesis (articulated by Chalmers in J Cogn Sci, 2012). My focus here is on theories of implementation. After presenting the basic simultaneous implementation construction, I argue that these theories do not avoid the simultaneous implementation result. The conclusion is that the idea that the implementation of the right kind of automaton suffices for a possession of a mind is dubious. (shrink)

An underlying assumption in computational approaches in cognitive and brain sciences is that the nervous system is an input–output model of the world: Its input–output functions mirror certain relations in the target domains. I argue that the input–output modelling assumption plays distinct methodological and explanatory roles. Methodologically, input–output modelling serves to discover the computed function from environmental cues. Explanatorily, input–output modelling serves to account for the appropriateness of the computed function to the explanandum information-processing task. I compare very briefly the (...) modelling explanation to mechanistic and optimality explanations, noting that in both cases the explanations can be seen as complementary rather than contrastive or competing. (shrink)

We describe a possible physical device that computes a function that cannot be computed by a Turing machine. The device is physical in the sense that it is compatible with General Relativity. We discuss some objections, focusing on those which deny that the device is either a computer or computes a function that is not Turing computable. Finally, we argue that the existence of the device does not refute the Church–Turing thesis, but nevertheless may be a counterexample to Gandy's thesis.

Muḥammad Mahdī ibn Abī Z̲arr Narāqī, -1794 or 1795. Jāmiʻ al-saʻādāt - Criticism and interpretation; Islamic ethics.

This latest work from one of the world's leading political philosophers will appeal to audiences from a variety of fields, including philosophy, political science, women's studies, ethnic studies, sociology, and communications studies.

The paper criticizes standard functionalist arguments for multiple realization. It focuses on arguments in which psychological states are conceived as computational, which is precisely where the multiple realization doctrine has seemed the strongest. It is argued that a type-type identity thesis between computational states and physical states is no less plausible than a multiple realization thesis. The paper also presents, more tentatively, positive arguments for a picture of local reduction.

Iris Murdoch was one of the great philosophers and novelists of the twentieth century and The Sovereignty of Good is her most important and enduring philosophical work. She argues that philosophy has focused, mistakenly, on what it is right to do rather than good to be and that only by restoring the notion of ‘vision’ to moral thinking can this distortion be corrected. This brilliant work shows why Iris Murdoch remains essential reading: a vivid and uncompromising style, a (...) commitment to forceful argument, and a courage to go against the grain. With a foreword by Mary Midgley. (shrink)

In her long-awaited Responsibility for Justice, Young discusses our responsibilities to address "structural" injustices in which we among many are implicated, often by virtue of participating in a market, such as buying goods produced in sweatshops, or participating in booming housing markets that leave many homeless.

Iris Murdoch once observed: 'philosophy is often a matter of finding occasions on which to say the obvious'. What was obvious to Murdoch, and to all those who read her work, is that Good transcends everything - even God. Throughout her distinguished and prolific writing career, she explored questions of Good and Bad, myth and morality. The framework for Murdoch's questions - and her own conclusions - can be found here.

The acclaimed author of The Good Apprentice draws on the entire history of philosophy--and particularly on Plato and Kant--to formulate her own model of morality and demonstrate how thoroughly it is bound up with our daily lives. "An utterly absorbing book".--The Wall Street Journal.

What are the limits of physical computation? In his ‘Church’s Thesis and Principles for Mechanisms’, Turing’s student Robin Gandy proved that any machine satisfying four idealised physical ‘principles’ is equivalent to some Turing machine. Gandy’s four principles in effect define a class of computing machines (‘Gandy machines’). Our question is: What is the relationship of this class to the class of all (ideal) physical computing machines? Gandy himself suggests that the relationship is identity. We do not share this view. We (...) will point to interesting examples of (ideal) physical machines that fall outside the class of Gandy machines and compute functions that are not Turing-machine computable. (shrink)

Iris Murdoch once observed: 'philosophy is often a matter of finding occasions on which to say the obvious'. What was obvious to Murdoch, and to all those who read her work, is that Good transcends everything - even God. Throughout her distinguished and prolific writing career, she explored questions of Good and Bad, myth and morality. The framework for Murdoch's questions - and her own conclusions - can be found here.

This paper challenges two orthodox theses: (a) that computational processes must be algorithmic; and (b) that all computed functions must be Turing-computable. Section 2 advances the claim that the works in computability theory, including Turing's analysis of the effective computable functions, do not substantiate the two theses. It is then shown (Section 3) that we can describe a system that computes a number-theoretic function which is not Turing-computable. The argument against the first thesis proceeds in two stages. It is first (...) shown (Section 4) that whether a process is algorithmic depends on the way we describe the process. It is then argued (Section 5) that systems compute even if their processes are not described as algorithmic. The paper concludes with a suggestion for a semantic approach to computation. (shrink)