About this topic
Summary Computers are currently intended as general purpose, programmable devices that carry out algorithmic instructions by way of arithmetic and logical operations. The philosophical literature on computers include the varied spectrum of theoretical, scientific, and technological issues that computers induce. Under theoretical issues are of particular importance those related to computability theory (such as the Church-Turing thesis), complexity, the limits of the computable, the relations between the mind and computers. Under the scientific problems of philosophical relevance are those related to computer-based mathematics, computer-generated arts, the explanation of computational events, pedagogy and human-computer interaction. Under the technological aspects of philosophical importance fall the design and correctness of programs, the nature of simulations, the representation and implementation of data and the nature and semantics of programming languages. 
Key works The philosophical relevance of computers is currently investigated in the large body of work that falls under the Philosophy of Computer Science, see Turner 2013
Introductions See Piccinini 2008 for an explication of the notion of computer according to the mechanistic account of computing mechanisms. For other issues see Turner 2013.
Related categories

47 found
  1. Computer: A History of the Information Machine. [REVIEW]Jon Agar - 1998 - British Journal for the History of Science 31 (3):361-375.
  2. Computers — Utensils or Epaulets? The Application Perspective Revisited.Gro Bjerknes & Tone Bratteteig - 1988 - AI and Society 2 (3):258-266.
    This paper is a discussion about how the Application Perspective works in practice.1 We talk about values and attitudes to system development and computer systems, and we illustrate how they have been carried out in practice by examples from the Florence project.2 The metaphors ‘utensil’ and ‘epaulet’ refer to questions about how we conceive the computer system we are to design in the system development process. Our experience is that, in the scientific community, technical challenges mean making computer systems that (...)
  3. Imaginary Computational Systems: Queer Technologies and Transreal Aesthetics. [REVIEW]Zach Blas & Micha Cárdenas - 2013 - AI and Society 28 (4):559-566.
  4. Layers of Models in Computer Simulations.Thomas Boyer-Kassem - 2014 - International Studies in the Philosophy of Science 28 (4):417-436.
    I discuss here the definition of computer simulations, and more specifically the views of Humphreys, who considers that an object is simulated when a computer provides a solution to a computational model, which in turn represents the object of interest. I argue that Humphreys's concepts are not able to analyse fully successfully a case of contemporary simulation in physics, which is more complex than the examples considered so far in the philosophical literature. I therefore modify Humphreys's definition of simulation. I (...)
  5. The History of Early Computer Switching.Arthur W. Burks & Alice R. Burks - 1988 - Grazer Philosophische Studien 32:3-36.
    We distinguish scanning switches, which only enumerate states, from function switches which transform input states into output states. For the latter we introduce a logical network symbolism. Our history of early computer switching begins with the suggestions of Ramon Lull and Gottfried Leibniz, surveys the evolution of mechanical scanning switches and the first mechanical function switches, and then describes the first electromechanical function switches. The main themes of the present paper are that William S. Jevons built the first substantial function (...)
  6. A History of Modern Computing.Paul E. Ceruzzi - 2003 - MIT Press.
    Ceruzzi pens a history of computing from the development of the first electronic digital computer to the Web and dot-com crash.
  7. On Effective Procedures.Carol E. Cleland - 2002 - Minds and Machines 12 (2):159-179.
    Since the mid-twentieth century, the concept of the Turing machine has dominated thought about effective procedures. This paper presents an alternative to Turing's analysis; it unifies, refines, and extends my earlier work on this topic. I show that Turing machines cannot live up to their billing as paragons of effective procedure; at best, they may be said to provide us with mere procedure schemas. I argue that the concept of an effective procedure crucially depends upon distinguishing procedures as definite courses (...)
  8. Effective Procedures and Computable Functions.Carol E. Cleland - 1995 - Minds and Machines 5 (1):9-23.
    Horsten and Roelants have raised a number of important questions about my analysis of effective procedures and my evaluation of the Church-Turing thesis. They suggest that, on my account, effective procedures cannot enter the mathematical world because they have a built-in component of causality, and, hence, that my arguments against the Church-Turing thesis miss the mark. Unfortunately, however, their reasoning is based upon a number of misunderstandings. Effective mundane procedures do not, on my view, provide an analysis of ourgeneral concept (...)
  9. Is the Church-Turing Thesis True?Carol E. Cleland - 1993 - Minds and Machines 3 (3):283-312.
    The Church-Turing thesis makes a bold claim about the theoretical limits to computation. It is based upon independent analyses of the general notion of an effective procedure proposed by Alan Turing and Alonzo Church in the 1930''s. As originally construed, the thesis applied only to the number theoretic functions; it amounted to the claim that there were no number theoretic functions which couldn''t be computed by a Turing machine but could be computed by means of some other kind of effective (...)
  10. Accelerating Turing Machines.B. Jack Copeland - 2002 - Minds and Machines 12 (2):281-300.
    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 (...)
  11. Hypercomputation.B. Jack Copeland - 2002 - Minds and Machines 12 (4):461-502.
  12. What is Computation?B. Jack Copeland - 1996 - Synthese 108 (3):335-59.
    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 (...)
  13. Physical Computation: How General Are Gandy's Principles for Mechanisms?B. Jack Copeland & Oron Shagrir - 2007 - Minds and Machines 17 (2):217-231.
    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 (...)
  14. Even Turing Machines Can Compute Uncomputable Functions.Jack Copeland - unknown
    Accelerated Turing machines are Turing machines that perform tasks commonly regarded as impossible, such as computing the halting function. The existence of these notional machines has obvious implications concerning the theoretical limits of computability.
  15. The Case for Continuous Auditing of Management Information Systems.Robert E. Davis - 2012 - Effective Auditing for Corporates: Key Developments in Practice and Procedures (Key Concepts).
    In the wake of the recent financial crisis, increasing the effectiveness of auditing has weighed heavily on the minds of those responsible for governance. When a business is profitable and paying healthy dividends to its stockholders, fraudulent activities and accounting irregularities can go unnoticed. However, when revenue and cash flow decline, internal costs and operations may be scrutinized more diligently, and discrepancies can emerge as a result. Effective Auditing for Corporates provides you with proactive advice to ...
  16. Physical Computation: A Mechanistic Account. [REVIEW]Joe Dewhurst - 2016 - Philosophical Psychology 29 (5):795-797.
    Physical Computation is the summation of Piccinini’s work on computation and mechanistic explanation over the past decade. It draws together material from papers published during that time, but also provides additional clarifications and restructuring that make this the definitive presentation of his mechanistic account of physical computation. This review will first give a brief summary of the account that Piccinini defends, followed by a chapter-by-chapter overview of the book, before finally discussing one aspect of the account in more critical detail.
  17. Three Paradigms of Computer Science.Amnon H. Eden - 2007 - Minds and Machines 17 (2):135-167.
    We examine the philosophical disputes among computer scientists concerning methodological, ontological, and epistemological questions: Is computer science a branch of mathematics, an engineering discipline, or a natural science? Should knowledge about the behaviour of programs proceed deductively or empirically? Are computer programs on a par with mathematical objects, with mere data, or with mental processes? We conclude that distinct positions taken in regard to these questions emanate from distinct sets of received beliefs or paradigms within the discipline: – The rationalist (...)
  18. Brain and Mind Operational Architectonics and Man-Made “Machine” Consciousness.Andrew A. Fingelkurts, Alexander A. Fingelkurts & Carlos F. H. Neves - 2009 - Cognitive Processing 10 (2):105-111.
    To build a true conscious robot requires that a robot’s “brain” be capable of supporting the phenomenal consciousness as human’s brain enjoys. Operational Architectonics framework through exploration of the temporal structure of information flow and inter-area interactions within the network of functional neuronal populations [by examining topographic sharp transition processes in the scalp electroencephalogram (EEG) on the millisecond scale] reveals and describes the EEG architecture which is analogous to the architecture of the phenomenal world. This suggests that the task of (...)
  19. The Construction of Personal Identities Online.Luciano Floridi - 2011 - Minds and Machines 21 (4):477-479.
    The Construction of Personal Identities Online Content Type Journal Article Category Introduction Pages 1-3 DOI 10.1007/s11023-011-9254-y Authors Luciano Floridi, Department of Philosophy, University of Hertfordshire, de Havilland Campus, Hatfield, Hertfordshire, AL10 9AB UK Journal Minds and Machines Online ISSN 1572-8641 Print ISSN 0924-6495.
  20. Information Processing as an Account of Concrete Digital Computation.Nir Fresco - 2013 - Philosophy and Technology 26 (1):31-60.
    It is common in cognitive science to equate computation (and in particular digital computation) with information processing. Yet, it is hard to find a comprehensive explicit account of concrete digital computation in information processing terms. An information processing account seems like a natural candidate to explain digital computation. But when ‘information’ comes under scrutiny, this account becomes a less obvious candidate. Four interpretations of information are examined here as the basis for an information processing account of digital computation, namely Shannon (...)
  21. An Analysis of the Criteria for Evaluating Adequate Theories of Computation.Nir Fresco - 2008 - Minds and Machines 18 (3):379-401.
    This paper deals with the question: What are the criteria that an adequate theory of computation has to meet? 1. Smith's answer: it has to meet the empirical criterion (i.e. doing justice to computational practice), the conceptual criterion (i.e. explaining all the underlying concepts) and the cognitive criterion (i.e. providing solid grounds for computationalism). 2. Piccinini's answer: it has to meet the objectivity criterion (i.e. identifying computation as a matter of fact), the explanation criterion (i.e. explaining the computer's behaviour), the (...)
  22. Notationality and the Information Processing Mind.Vinod Goel - 1991 - Minds and Machines 1 (2):129-166.
    Cognitive science uses the notion of computational information processing to explain cognitive information processing. Some philosophers have argued that anything can be described as doing computational information processing; if so, it is a vacuous notion for explanatory purposes.An attempt is made to explicate the notions of cognitive information processing and computational information processing and to specify the relationship between them. It is demonstrated that the resulting notion of computational information processing can only be realized in a restrictive class of dynamical (...)
  23. An ATP of a Relational Proof System for Order of Magnitude Reasoning with Negligibility, Non-Closeness and Distance.Joanna Golinska-Pilarek, Angel Mora & Emilio Munoz Velasco - 2008 - In Tu-Bao Ho & Zhi-Hua Zhou (eds.), PRICAI 2008: Trends in Artificial Intelligence. Springer. pp. 128--139.
    We introduce an Automatic Theorem Prover (ATP) of a dual tableau system for a relational logic for order of magnitude qualitative reasoning, which allows us to deal with relations such as negligibility, non-closeness and distance. Dual tableau systems are validity checkers that can serve as a tool for verification of a variety of tasks in order of magnitude reasoning, such as the use of qualitative sum of some classes of numbers. In the design of our ATP, we have introduced some (...)
  24. Eric Winsberg: Science in the Age of Computer Simulation. [REVIEW]Stefan Gruner - 2013 - Minds and Machines 23 (2):251-254.
  25. Cognitive Technology and Pragmatics: Analogies and (Non-)Alignments. [REVIEW]Hartmut Haberland - 1996 - AI and Society 10 (3-4):303-308.
    This paper presents some considerations about the relationship between languages and computer systems from a pragmatic, user-centered point of view.
  26. Opinions and Outlooks on Morphological Computation.Helmut Hauser, Rudolf M. Füchslin & Rolf Pfeifer (eds.) - 2014 - E-Book.
    Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon (...)
  27. Trade-Offs in Exploiting Body Morphology for Control: From Simple Bodies and Model-Based Control to Complex Ones with Model-Free Distributed Control Schemes.Matej Hoffmann & Vincent C. Müller - 2014 - In Helmut Hauser, Rudolf M. Füchslin & Rolf Pfeifer (eds.), Opinions and Outlooks on Morphological Computation. E-Book. pp. 185-194.
    Tailoring the design of robot bodies for control purposes is implicitly performed by engineers, however, a methodology or set of tools is largely absent and optimization of morphology (shape, material properties of robot bodies, etc.) is lag- ging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or "soft" bodies. These carry substantial potential regarding their exploitation for control – sometimes referred to as "mor- phological computation" in the sense of offloading computation (...)
  28. Universal Intelligence: A Definition of Machine Intelligence.Shane Legg & Marcus Hutter - 2007 - Minds and Machines 17 (4):391-444.
    A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...)
  29. Justified Belief in a Digital Age: On the Epistemic Implications of Secret Internet Technologies.Boaz Miller & Isaac Record - 2013 - Episteme 10 (02):117 - 134.
    People increasingly form beliefs based on information gained from automatically filtered Internet ‎sources such as search engines. However, the workings of such sources are often opaque, preventing ‎subjects from knowing whether the information provided is biased or incomplete. Users’ reliance on ‎Internet technologies whose modes of operation are concealed from them raises serious concerns about ‎the justificatory status of the beliefs they end up forming. Yet it is unclear how to address these concerns ‎within standard theories of knowledge and justification. (...)
  30. A Simplicity Criterion for Physical Computation.Tyler Millhouse - forthcoming - British Journal for the Philosophy of Science.
    The aim of this paper is to offer a formal criterion for physical computation that allows us to objectively distinguish between competing computational interpretations of a physical system. The criterion construes a computational interpretation as an ordered pair of functions mapping (1) states of a physical system to states of an abstract machine, and (2) inputs to this machine to interventions in this physical system. This interpretation must ensure that counterfactuals true of the abstract machine have appropriate counterparts which are (...)
  31. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models of (...)
  32. Computing and Philosophy: Selected Papers From IACAP 2014.Vincent C. Müller (ed.) - 2016 - Springer.
    This volume offers very selected papers from the 2014 conference of the “International Association for Computing and Philosophy” (IACAP) - a conference tradition of 28 years. - - - Table of Contents - 0 Vincent C. Müller: - Editorial - 1) Philosophy of computing - 1 Çem Bozsahin: - What is a computational constraint? - 2 Joe Dewhurst: - Computing Mechanisms and Autopoietic Systems - 3 Vincenzo Fano, Pierluigi Graziani, Roberto Macrelli and Gino Tarozzi: - Are Gandy Machines really local? (...)
  33. What is Morphological Computation? On How the Body Contributes to Cognition and Control.Vincent C. Müller & Matej Hoffmann - 2017 - Artificial Life 23 (1):1-24.
    The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) morphology that (...)
  34. DDoS Protection With IPtables.Constantin Oesterling - 2016 - InfoSec:15.
    Research on the most effective Linux iptables rules to mitigate Distributed Denial of Service (DDoS) attacks.
  35. Computation in Physical Systems.Gualtiero Piccinini - 2010 - Stanford Encyclopedia of Philosophy.
  36. Computers.Gualtiero Piccinini - 2008 - Pacific Philosophical Quarterly 89 (1):32–73.
    I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...)
  37. Some Neural Networks Compute, Others Don't.Gualtiero Piccinini - 2008 - Neural Networks 21 (2-3):311-321.
    I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
    the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
    Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
    compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well fall into this last class.
  38. Computing Mechanisms.Gualtiero Piccinini - 2007 - Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...)
  39. Paul E. Ceruzzi. Internet Alley: High Technology in Tysons Corner, 1945-2005. [REVIEW]Isaac Record & Andrew Munro - 2008 - Spontaneous Generations 2 (1):251.
  40. Realismo científico, computacionalismo y la máxima pragmática.Ricardo Restrepo - 2013 - In Douglas Anderson, Ricardo Restrepo, Victor Hugo Chica & Diana Patricia Carmona (eds.), El pragmatismo norteamericano. IAEN.
    Se identifica el argumento de que la teoría de que hay propiedades computacionales suficientes para propiedades mentales es una teoría o falsa o vacía, ya que las propiedades computacionales no son empíricamente descubriles, intrínsecas ni causales, como sí lo son las propiedades mentales. Es un argumento que se puede destilar de los problemas que John Searle imputa a la ciencia cognitiva computacional, pero encuentra su correlato antecedente en el argumento que Max Newman utilizó para refutar el estructuralismo físico de Bertrand (...)
  41. What is Computer Science About?Oron Shagrir - 1999 - The Monist 82 (1):131-149.
  42. Your Digital Afterlives: Computational Theories of Life After Death.Eric Steinhart - 2014 - Palgrave.
    Our digital technologies have inspired new ways of thinking about old religious topics. Digitalists include computer scientists, transhumanists, singularitarians, and futurists. Digitalists have worked out novel and entirely naturalistic ways of thinking about bodies, minds, souls, universes, gods, and life after death. Your Digital Afterlives starts with three digitalist theories of life after death. It examines personality capture, body uploading, and promotion to higher levels of simulation. It then examines the idea that reality itself is ultimately a system of self-surpassing (...)
  43. On the Plurality of Gods.Eric Steinhart - 2013 - Religious Studies 49 (3):289-312.
    Ordinal polytheism is motivated by the cosmological and design arguments. It is also motivated by Leibnizian–Lewisian modal realism. Just as there are many universes, so there are many gods. Gods are necessary concrete grounds of universes. The god-universe relation is one-to-one. Ordinal polytheism argues for a hierarchy of ranks of ever more perfect gods, one rank for every ordinal number. Since there are no maximally perfect gods, ordinal polytheism avoids many of the familiar problems of monotheism. It links theology with (...)
  44. Infinitely Complex Machines.Eric Steinhart - 2007 - In Intelligent Computing Everywhere. Springer. pp. 25-43.
    Infinite machines (IMs) can do supertasks. A supertask is an infinite series of operations done in some finite time. Whether or not our universe contains any IMs, they are worthy of study as upper bounds on finite machines. We introduce IMs and describe some of their physical and psychological aspects. An accelerating Turing machine (an ATM) is a Turing machine that performs every next operation twice as fast. It can carry out infinitely many operations in finite time. Many ATMs can (...)
  45. Supermachines and Superminds.Eric Steinhart - 2003 - Minds and Machines 13 (1):155-186.
    If the computational theory of mind is right, then minds are realized by machines. There is an ordered complexity hierarchy of machines. Some finite machines realize finitely complex minds; some Turing machines realize potentially infinitely complex minds. There are many logically possible machines whose powers exceed the Church–Turing limit (e.g. accelerating Turing machines). Some of these supermachines realize superminds. Superminds perform cognitive supertasks. Their thoughts are formed in infinitary languages. They perceive and manipulate the infinite detail of fractal objects. They (...)
  46. The Philosophy of Computer Science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
  47. Chains of Reference in Computer Simulations.Franck Varenne - 2013 - FMSH Working Papers 51:1-32.
    This paper proposes an extensionalist analysis of computer simulations (CSs). It puts the emphasis not on languages nor on models, but on symbols, on their extensions, and on their various ways of referring. It shows that chains of reference of symbols in CSs are multiple and of different kinds. As they are distinct and diverse, these chains enable different kinds of remoteness of reference and different kinds of validation for CSs. Although some methodological papers have already underlined the role of (...)