Computers

Why are we so many? Or, in other words, Why is our species so successful? The ultimate cause of our success as species is that we, Homo sapiens, are the first and the only Turing complete species. Turing completeness is the capacity of some hardware to compute by software whatever hardware can compute. To reach the answer, I propose to see evolution and computing from the problem solving point of view. Then, solving more problems is evolutionarily better, computing is for (...) solving problems, and software is much cheaper than hardware, resulting that Turing completeness is evolutionarily disruptive. This conclusion, together with the fact that we are the only Turing complete species, is the reason that explains why we are so many. Most of our unique cognitive characteristics as humans can be derived from being Turing complete, as for example our complete language and our problem solving creativity. (shrink)

One of the central questions in the epistemology of conversational AIs is how to classify the beliefs acquired from them. Two promising candidates are instrument-based and testimony-based beliefs. However, the category of instrument-based beliefs faces an intrinsic problem, and a challenge arises in its application. On the other hand, relying solely on the category of testimony-based beliefs does not encompass the totality of our practice of using conversational AIs. To address these limitations, I propose a novel classification of beliefs that (...) shifts the focus from the properties of the conversational AIs themselves to how recipients perceive AI output, specifically whether they take the output at face value. The proposed categories are beliefs by regarding as instruments and beliefs by regarding as testifiers. By using these complementary categories, a more comprehensive understanding of beliefs acquired from conversational AIs can be achieved while avoiding the problems associated with the traditional classification. (shrink)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts (...) of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (shrink)

One determining characteristic of contemporary sociopolitical systems is their power over increasingly large and diverse populations. This raises questions about power relations between heterogeneous individuals and increasingly dominant and homogenizing system objectives. This article crosses epistemic boundaries by integrating computer engineering and a historicalphilosophical approach making the general organization of individuals within large-scale systems and corresponding individual homogenization intelligible. From a versatile archeological-genealogical perspective, an analysis of computer and social architectures is conducted that reinterprets Foucault’s disciplines and political anatomy to (...) establish the notion of politics for a purely technical system. This permits an understanding of system organization as modern technology with application to technical and social systems alike. Connecting to Heidegger’s notions of the enframing (Gestell) and a more primal truth (anfänglicheren Wahrheit), the recognition of politics in differently developing systems then challenges the immutability of contemporary organization. Following this critique of modernity and within the conceptualization of system organization, Derrida’s democracy to come (à venir) is then reformulated more abstractly as organizations to come. Through the integration of the discussed concepts, the framework of Large-Scale Systems Composed of Homogeneous Individuals (LSSCHI) is proposed, problematizing the relationships between individuals, structure, activity, and power within large-scale systems. The LSSCHI framework highlights the conflict of homogenizing system-level objectives and individual heterogeneity, and outlines power relations and mechanisms of control shared across different social and technical systems. (shrink)

Una imagen muy generalizada a la hora de entender el software de computador es la que lo representa como una “caja negra”: no importa realmente saber qué partes lo componen internamente, sino qué resultados se obtienen de él según ciertos valores de entrada. Al hacer esto, muchos problemas filosóficos son ocultados, negados o simplemente mal entendidos. Este artículo discute tres unidades de análisis del software de computador, esto es, las especificaciones, los algoritmos y los procesos computacionales. El objetivo central es (...) entender las prácticas cientficas e ingenieriles detrás de cada unidad de software, así como analizar su metodología, ontología y epistemología. (shrink)

There is an existing debate regarding the view that technological instruments, devices, or machines can assert ‎or testify. A standard view in epistemology is that only humans can testify. However, the notion of quasi-‎testimony acknowledges that technological devices can assert or testify under some conditions, without ‎denying that humans and machines are not the same. Indeed, there are four relevant differences between ‎humans and instruments. First, unlike humans, machine assertion is not imaginative or playful. Second, ‎machine assertion is prescripted and (...) context restricted. As such, computers currently cannot easily switch ‎contexts or make meaningful relevant assertions in contexts for which they were not programmed. Third, ‎while both humans and computers make errors, they do so in different ways. Computers are very sensitive to ‎small errors in input, which may cause them to make big errors in output. Moreover, automatic error control ‎is based on finding irregularities in data without trying to establish whether they make sense. Fourth, ‎testimony is produced by a human with moral worth, while quasi-testimony is not. Ultimately, the notion of ‎quasi-testimony can serve as a bridge between different philosophical fields that deal with instruments and ‎testimony as sources of knowledge, allowing them to converse and agree on a shared description of reality, ‎while maintaining their distinct conceptions and ontological commitments about knowledge, humans, and ‎nonhumans.‎. (shrink)

Engineers fine-tune the design of robot bodies for control purposes, however, a methodology or set of tools is largely absent, and optimization of morphology (shape, material properties of robot bodies, etc.) is lagging 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 ”morphological computation”. In this article, we briefly review different notions of computation by physical systems and (...) propose the dynamical systems framework as the most useful in the context of describing and eventually designing the interactions of controllers and bodies. Then, we look at the pros and cons of simple vs. complex bodies, critically reviewing the attractive notion of ”soft” bodies automatically taking over control tasks. We address another key dimension of the design space—whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. (shrink)

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 (...) facilitates control, (2) morphology that facilitates perception and the rare cases of (3) morphological computation proper, such as ‘reservoir computing.’ where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control – how it contributes to the overall ‘orchestration’ of intelligent behaviour. (shrink)

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.

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? (...) - 4 Doukas Kapantais: - A refutation of the Church-Turing thesis according to some interpretation of what the thesis says - 5 Paul Schweizer: - In What Sense Does the Brain Compute? - 2) Philosophy of computer science & discovery - 6 Mark Addis, Peter Sozou, Peter C R Lane and Fernand Gobet: - Computational Scientific Discovery and Cognitive Science Theories - 7 Nicola Angius and Petros Stefaneas: - Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach. - 8 Selmer Bringsjord, John Licato, Daniel Arista, Naveen Sundar Govindarajulu and Paul Bello: - Introducing the Doxastically Centered Approach to Formalizing Relevance Bonds in Conditionals - 9 Orly Stettiner: - From Silico to Vitro: - Computational Models of Complex Biological Systems Reveal Real-world Emergent Phenomena - 3) Philosophy of cognition & intelligence - 10 Douglas Campbell: - Why We Shouldn’t Reason Classically, and the Implications for Artificial Intelligence - 11 Stefano Franchi: - Cognition as Higher Order Regulation - 12 Marcello Guarini: - Eliminativisms, Languages of Thought, & the Philosophy of Computational Cognitive Modeling - 13 Marcin Miłkowski: - A Mechanistic Account of Computational Explanation in Cognitive Science and Computational Neuroscience - 14 Alex Tillas: - Internal supervision & clustering: - A new lesson from ‘old’ findings? - 4) Computing & society - 15 Vasileios Galanos: - Floridi/Flusser: - Parallel Lives in Hyper/Posthistory - 16 Paul Bello: - Machine Ethics and Modal Psychology - 17 Marty J. Wolf and Nir Fresco: - My Liver Is Broken, Can You Print Me a New One? - 18 Marty J. Wolf, Frances Grodzinsky and Keith W. Miller: - Robots, Ethics and Software – FOSS vs. Proprietary Licenses. (shrink)

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 (...) allow for several successive layers of computational models, and I discuss the relations that exist between these models, the computer, and the object under study. An aim of my proposal is to clarify the distinction between computational models and numerical methods, and to better understand the representational and the computational functions of models in simulations. (shrink)

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 (...) system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others. (shrink)

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 (...) computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)

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. (...) To shed light on the problem, we introduce a ‎novel conceptual framework that clarifies the relations between justified belief, epistemic responsibility, ‎action, and the technological resources available to a subject. We argue that justified belief is subject to ‎certain epistemic responsibilities that accompany the subject’s particular decision-taking circumstances, ‎and that one typical responsibility is to ascertain, so far as one can, whether the information upon which ‎the judgment will rest is biased or incomplete. What this responsibility comprises is partly determined by ‎the inquiry-enabling technologies available to the subject. We argue that a subject’s beliefs that are ‎formed based on Internet-filtered information are less justified than they would be if she either knew how ‎filtering worked or relied on additional sources, and that the subject may have the epistemic ‎responsibility to take measures to enhance the justificatory status of such beliefs.‎. (shrink)

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 (...) counterpart theory, mathematics and computer science. And it entails that the system of universes has an attractive axiological structure. (shrink)

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 (...) these various relationships of reference in CSs and of cross-validations, this diversity is still overlooked in the epistemological literature on CSs. As a consequence, a particular outcome of this analytical view is an ability to classify existing epistemological theses on CSs according to what their authors choose to select and put at the forefront: either the extensions of symbols, or the symbol-types, or the symbol-tokens, or the internal denotational hierarchies of the CS or the reference of these hierarchies to external denotational hierarchies. Through the adoption of this extensionalist view, it also becomes possible to explain more precisely the reasons why some complete reduction of CSs to classical epistemic paradigms such as “experiment” or “theoretical argument” remains doubtful. On this last point, in particular, this paper is in agreement with what many epistemologists already have acknowledged. (shrink)

Information and communication technologies (ICTs) are building a new habitat (infosphere) in which future generations, living in advanced information societies, will spend an increasing amount of time. This paper introduces a series of articles that explore what constitutes a personal identity online (PIO) and how, as well as to what extent, individuals can learn to create, manage and perceive their PIOs in order to facilitate a healthy and rewarding online experience (onlife).

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 (...) be connected together to form networks of infinitely powerful agents. A network of ATMs can also be thought of as the control system for an infinitely complex robot. We describe a robot with a dense network of ATMs for its retinas, its brain, and its motor controllers. Such a robot can perform psychological supertasks - it can perceive infinitely detailed objects in all their detail; it can formulate infinite plans; it can make infinitely precise movements. An endless hierarchy of IMs might realize a deep notion of intelligent computing everywhere. (shrink)

What is it for a sound or gesture to have a meaning, and how does it come to have one? In this paper, a range of simulations are used to extend the tradition of theories of meaning as use. The authors work throughout with large spatialized arrays of sessile individuals in an environment of wandering food sources and predators. Individuals gain points by feeding and lose points when they are hit by a predator and are not hiding. They can also (...) make sounds heard by immediate neighbours in the array, and can respond to sounds from immediate neighbours. No inherent meaning for these sounds is built into the simulation; under what circumstances they are sent, if any, and what the response to them is, if any, vary initially with the strategies randomized across the array. These sounds do take on a specific function for communities of individuals, however, with any of three forms of strategy change: direct imitation of strategies of successful neighbours, a localized genetic algorithm in which strategies are ‘crossed’ with those of successful neighbours, and neural net training on the behaviour of successful neighbours. Starting from an array randomized across a large number of strategies, and using any of these modes of strategy change, communities of ‘communicators’ emerge. Within these evolving communities the sounds heard from immediate neighbours, initially arbitrary across the array, come to be used for very specific communicative functions. ‘Communicators’ make a particular sound on feeding and respond to that same sound from neighbours by opening their mouths; they make a different sound when hit with a predator and respond to that sound by hiding. Robustly and persistently, even in simple computer models of communities of self-interested agents, something suggestively like signalling emerges and spreads. Keywords: meaning, communication, genetic algorithms, neural networks. (shrink)

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 (...) have infinitely complex bodies. Transfinite games anchor their social relations. (shrink)

This is a review of Survey of the State of the Art in Human Language Technology, [editorial board: Ronald Cole (editor-in-chief), Joseph Mariani, Hans Uszkoreit, Annie Zaenen, Victor Zue], Cambridge University Press (Studies in Natural Language Processing) and Giardini Editori e Stampatori in Pisa (Linguistica Computazionale, volumes XII-XII1), managing editors: Giovanni Battista Varile and Antonio Zampolli, Cambridge University Press, 1997.

Recently, there have been some attempts towards developing programming languages based on situation theory. These languages employ situation-theoretic constructs with varying degrees of divergence from the ontology of the theory. In this paper, we review three of these programming languages.

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Digital computers carry out algorithms coded in high level programs. These abstract entities determine what happens at the physical level: they control whether electrons flow through specific transistors at specific times or not, entailing downward causation in both the logical and implementation hierarchies. This paper explores how this is possible in the light of the alleged causal completeness of physics at the bottom level, and highlights the mechanism that enables strong emergence (the manifest causal effectiveness of application programs) to occur. (...) Although synchronic emergence of higher levels from lower levels is manifestly true, diachronic emergence is generically not the case; indeed we give specific examples where it cannot occur because of the causal effectiveness of higher level variables. (shrink)