Results for 'computers in philosophy'

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  1. Computational modeling in philosophy: introduction to a topical collection.Simon Scheller, Christoph Merdes & Stephan Hartmann - 2022 - Synthese 200 (2):1-10.
    Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the (...)
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  2. European Computing and Philosophy.Gordana Dodig-Crnkovic - 2009 - The Reasoner 3 (9):18-19.
    European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can (...)
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  3. Computing and philosophy: Selected papers from IACAP 2014.Vincent C. Müller (ed.) - 2016 - Cham: 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 (...)
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  4. Philosophy of Mind Is (in Part) Philosophy of Computer Science.Darren Abramson - 2011 - Minds and Machines 21 (2):203-219.
    In this paper I argue that whether or not a computer can be built that passes the Turing test is a central question in the philosophy of mind. Then I show that the possibility of building such a computer depends on open questions in the philosophy of computer science: the physical Church-Turing thesis and the extended Church-Turing thesis. I use the link between the issues identified in philosophy of mind and philosophy of computer science to respond (...)
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  5. Old and New Problems in Philosophy of Measurement.Eran Tal - 2013 - Philosophy Compass 8 (12):1159-1173.
    The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program (...)
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  6. Counting with Cilia: The Role of Morphological Computation in Basal Cognition Research.Wiktor Rorot - 2022 - Entropy 24 (11):1581.
    “Morphological computation” is an increasingly important concept in robotics, artificial intelligence, and philosophy of the mind. It is used to understand how the body contributes to cognition and control of behavior. Its understanding in terms of "offloading" computation from the brain to the body has been criticized as misleading, and it has been suggested that the use of the concept conflates three classes of distinct processes. In fact, these criticisms implicitly hang on accepting a semantic definition of what constitutes (...)
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  7. (1 other version)Platonic Computer— the Universal Machine That Bridges the “Inverse Explanatory Gap” in the Philosophy of Mind.Simon X. Duan - 2022 - Filozofia i Nauka 10:285-302.
    The scope of Platonism is extended by introducing the concept of a “Platonic computer” which is incorporated in metacomputics. The theoretical framework of metacomputics postulates that a Platonic computer exists in the realm of Forms and is made by, of, with, and from metaconsciousness. Metaconsciousness is defined as the “power to conceive, to perceive, and to be self-aware” and is the formless, con-tentless infinite potentiality. Metacomputics models how metaconsciousness generates the perceived actualities including abstract entities and physical and nonphysical realities. (...)
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  8. What is Mind in Philosophy: An Introduction.R. L. Tripathi - 2024 - International Journal of Scientific Research in Enginnering and Management 6 (12):17.
    The exploration of the mind is a fundamental pursuit spanning philosophy and psychology, with implications reaching into diverse practical realms. This paper delves into the intricacies of mental states, examining historical perspectives from ancient philosophers to modern theorists. Philosophical inquiries into intentionality, consciousness, and the nature of mental phenomena are scrutinized, alongside empirical investigations by psychologists. The discourse navigates through contrasting theories such as dualism, materialism, and functionalism, shedding light on the challenges of reconciling subjective experiences with objective observations. (...)
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  9. Modeling Epistemology: Examples and Analysis in Computational Philosophy of Science.Patrick Grim - 2019 - In A. Del Barrio, C. J. Lynch, F. J. Barros & X. Hu (eds.), IEEE SpringSim Proceedings 2019. IEEE. pp. 1-12.
    What structure of scientific communication and cooperation, between what kinds of investigators, is best positioned to lead us to the truth? Against an outline of standard philosophical characteristics and a recent turn to social epistemology, this paper surveys highlights within two strands of computational philosophy of science that attempt to work toward an answer to this question. Both strands emerge from abstract rational choice theory and the analytic tradition in philosophy of science rather than postmodern sociology of science. (...)
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  10. Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains? Towards a Media Sociology of Machine Learning.Rainer Mühlhoff - 2019 - New Media and Society 1.
    Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and social-theoretical critique, (...)
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  11. Philosophy of computing and information: 5 Questions.Luciano Floridi - 2008 - Copenhagen, Denmark: Automatic Press/VIP.
    Computing and information, and their philosophy in the broad sense, play a most important scientific, technological and conceptual role in our world. This book collects together, for the first time, the views and experiences of some of the visionary pioneers and most influential thinkers in such a fundamental area of our intellectual development.
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  12. Transparency in Complex Computational Systems.Kathleen A. Creel - 2020 - Philosophy of Science 87 (4):568-589.
    Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...
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  13. Lightning in a Bottle: Complexity, Chaos, and Computation in Climate Science.Jon Lawhead - 2014 - Dissertation, Columbia University
    Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...)
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  14. A Dialogue Concerning ‘Doing Philosophy with and within Computer Games’ – or: Twenty rainy minutes in Krakow.Michelle Westerlaken & Stefano Gualeni - 2017 - Proceedings of the 2017 International Conference of the Philosophy of Computer Games.
    ‘Philosophical dialogue’ indicates both a form of philosophical inquiry and its corresponding literary genre. In its written form, it typically features two or more characters who engage in a discussion concerning morals, knowledge, as well as a variety of topics that can be widely labelled as ‘philosophical’. Our philosophical dialogue takes place in Krakow, Poland. It is a rainy morning and two strangers are waiting at a tram stop. One of them is dressed neatly, and cannot stop fidgeting with his (...)
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  15. Computer verification for historians of philosophy.Landon D. C. Elkind - 2022 - Synthese 200 (3):1-28.
    Interactive theorem provers might seem particularly impractical in the history of philosophy. Journal articles in this discipline are generally not formalized. Interactive theorem provers involve a learning curve for which the payoffs might seem minimal. In this article I argue that interactive theorem provers have already demonstrated their potential as a useful tool for historians of philosophy; I do this by highlighting examples of work where this has already been done. Further, I argue that interactive theorem provers can (...)
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  16. Computational Thought Experiments for a More Rigorous Philosophy and Science of the Mind.Iris Oved, Nikhil Krishnaswamy, James Pustejovsky & Joshua Hartshorne - 2024 - In Larissa Samuelson, Stefan Frank, Mariya Toneva, Allyson Mackey & Eliot Hazeltine (eds.), Proceedings of the 46th Annual Conference of the Cognitive Science Society. pp. 601-609.
    We offer philosophical motivations for a method we call Virtual World Cognitive Science (VW CogSci), in which researchers use virtual embodied agents that are embedded in virtual worlds to explore questions in the field of Cognitive Science. We focus on questions about mental and linguistic representation and the ways that such computational modeling can add rigor to philosophical thought experiments, as well as the terminology used in the scientific study of such representations. We find that this method forces researchers to (...)
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  17. Philosophy and Science, the Darwinian-Evolved Computational Brain, a Non-Recursive Super-Turing Machine & Our Inner-World-Producing Organ.Hermann G. W. Burchard - 2016 - Open Journal of Philosophy 6 (1):13-28.
    Recent advances in neuroscience lead to a wider realm for philosophy to include the science of the Darwinian-evolved computational brain, our inner world producing organ, a non-recursive super- Turing machine combining 100B synapsing-neuron DNA-computers based on the genetic code. The whole system is a logos machine offering a world map for global context, essential for our intentional grasp of opportunities. We start from the observable contrast between the chaotic universe vs. our orderly inner world, the noumenal cosmos. So (...)
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  18. Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines.Gordana Dodig-Crnkovic - 2020 - Philosophies 5 (3):17-32.
    The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models (...)
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  19. Ghost in the Machine: A Philosophical Analysis of the Relationship Between Brain-Computer Interface Applications and their Users.Richard Heersmink - 2009 - Dissertation, University of Twente.
    This Master’s thesis explores the relationship between Brain-Computer Interfaces (BCIs) and their human users from a functional, epistemological and phenomenological perspective. The analysis has four steps. I start out with a technical description of BCI systems in which I conceptually analyze different types of BCI applications. This results in the development of a taxonomy of applications which is the point of departure for further philosophical analysis. Thereafter, I explore the functional relationship between BCI applications and their users. That is to (...)
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  20. Philosophy of Probability: Foundations, Epistemology, and Computation.Sylvia Wenmackers - 2011 - Dissertation, University of Groningen
    This dissertation is a contribution to formal and computational philosophy. -/- In the first part, we show that by exploiting the parallels between large, yet finite lotteries on the one hand and countably infinite lotteries on the other, we gain insights in the foundations of probability theory as well as in epistemology. Case 1: Infinite lotteries. We discuss how the concept of a fair finite lottery can best be extended to denumerably infinite lotteries. The solution boils down to the (...)
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  21. Epistemic issues in computational reproducibility: software as the elephant in the room.Alexandre Hocquet & Frédéric Wieber - 2021 - European Journal for Philosophy of Science 11 (2):1-20.
    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 (...)
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  22. The Computational Search for Unity: Synthesis in Generative AI.M. Beatrice Fazi - 2024 - Journal of Continental Philosophy 5 (1):31-56.
    The outputs of generative artificial intelligence (generative AI) are often called “synthetic” to imply that they are not natural but artificial. Against that use of the term, this article focuses on a different denotation of synthesis, stressing the unifying and compositional aspects of anything synthetic. The case of large language models (LLMs) is used as an example to address synthesis philosophically alongside notions of representation in contemporary computational systems. It is argued that synthesis in generative AI should be understood as (...)
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  23. Open problems in the philosophy of information.Luciano Floridi - 2004 - Metaphilosophy 35 (4):554-582.
    The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's (...)
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  24. Computers Aren’t Syntax All the Way Down or Content All the Way Up.Cem Bozşahin - 2018 - Minds and Machines 28 (3):543-567.
    This paper argues that the idea of a computer is unique. Calculators and analog computers are not different ideas about computers, and nature does not compute by itself. Computers, once clearly defined in all their terms and mechanisms, rather than enumerated by behavioral examples, can be more than instrumental tools in science, and more than source of analogies and taxonomies in philosophy. They can help us understand semantic content and its relation to form. This can be (...)
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  25. Logic in mathematics and computer science.Richard Zach - forthcoming - In Filippo Ferrari, Elke Brendel, Massimiliano Carrara, Ole Hjortland, Gil Sagi, Gila Sher & Florian Steinberger (eds.), Oxford Handbook of Philosophy of Logic. Oxford, UK: Oxford University Press.
    Logic has pride of place in mathematics and its 20th century offshoot, computer science. Modern symbolic logic was developed, in part, as a way to provide a formal framework for mathematics: Frege, Peano, Whitehead and Russell, as well as Hilbert developed systems of logic to formalize mathematics. These systems were meant to serve either as themselves foundational, or at least as formal analogs of mathematical reasoning amenable to mathematical study, e.g., in Hilbert’s consistency program. Similar efforts continue, but have been (...)
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  26. Apriori Knowledge in an Era of Computational Opacity: The Role of AI in Mathematical Discovery.Eamon Duede & Kevin Davey - forthcoming - Philosophy of Science.
    Can we acquire apriori knowledge of mathematical facts from the outputs of computer programs? People like Burge have argued (correctly in our opinion) that, for example, Appel and Haken acquired apriori knowledge of the Four Color Theorem from their computer program insofar as their program simply automated human forms of mathematical reasoning. However, unlike such programs, we argue that the opacity of modern LLMs and DNNs creates obstacles in obtaining apriori mathematical knowledge from them in similar ways. We claim though (...)
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  27. New developments in the philosophy of AI.Vincent C. Müller - 2016 - In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence. Cham: Springer.
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.
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  28. What is this thing called Philosophy of Science? A computational topic-modeling perspective, 1934–2015.Christophe Malaterre, Jean-François Chartier & Davide Pulizzotto - 2019 - Hopos: The Journal of the International Society for the History of Philosophy of Science 9 (2):215-249.
    What is philosophy of science? Numerous manuals, anthologies or essays provide carefully reconstructed vantage points on the discipline that have been gained through expert and piecemeal historical analyses. In this paper, we address the question from a complementary perspective: we target the content of one major journal of the field—Philosophy of Science—and apply unsupervised text-mining methods to its complete corpus, from its start in 1934 until 2015. By running topic-modeling algorithms over the full-text corpus, we identified 126 key (...)
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  29. Descriptive Complexity, Computational Tractability, and the Logical and Cognitive Foundations of Mathematics.Markus Pantsar - 2021 - Minds and Machines 31 (1):75-98.
    In computational complexity theory, decision problems are divided into complexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in the complexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. In cognitive science and philosophy, this tractability result has been used to argue that only functions in P can feasibly work as (...)
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  30. Psychological and Computational Models of Language Comprehension: In Defense of the Psychological Reality of Syntax.David Pereplyotchik - 2011 - Croatian Journal of Philosophy 11 (1):31-72.
    In this paper, I argue for a modified version of what Devitt calls the Representational Thesis. According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational models of comprehension (...)
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  31. Understanding the Interaction Between Philosophy and Science in Contemporary Times—An Interview with Professor JIANG Yi.Yi Jiang & Lv Xue - 2024 - Journal of Human Cognition 8 (1):39-58.
    The relationship between philosophy and science in contemporary times is closer than ever. From the methodology perspective, scientific and philosophical research has a clear sequential relationship. It is highlighted in the following aspects: 1. the methodology of scientific research, including theoretical assumptions and data modeling, parallels with apparent similarities in conceptual analysis and logical deduction in philosophy;2. consistency of analytical argumentation methods in scientific research and philosophical research;3. naturalism is currently a research approach that both scientific and philosophical (...)
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  32. Mind and Machine: A Philosophical Examination of Matt Carter’s “Minds & Computers: An Introduction to the Philosophy of Artificial Intelligence”.R. L. Tripathi - 2024 - Open Access Journal of Data Science and Artificial Intelligence 2 (1):3.
    In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. Carter contrasts (...)
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  33. Epistemological and phenomenological issues in the use of brain-computer interfaces.Richard Heersmink - 2011 - In C. Ess & R. Hagengruber (eds.), Proceedings of the International Association for Computing and Philosophy 2011 (pp. 98-102). MV-Wissenschaft.
    Brain-computer interfaces (BCIs) are an emerging and converging technology that translates the brain activity of its user into command signals for external devices, ranging from motorized wheelchairs, robotic hands, environmental control systems, and computer applications. In this paper I functionally decompose BCI systems and categorize BCI applications with similar functional properties into three categories, those with (1) motor, (2) virtual, and (3) linguistic applications. I then analyse the relationship between these distinct BCI applications and their users from an epistemological and (...)
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  34. (1 other version)What is the Philosophy of Information?Luciano Floridi - 2002 - Metaphilosophy 33 (1‐2):123-145.
    Computational and information‐theoretic research in philosophy has become increasingly fertile and pervasive, giving rise to a wealth of interesting results. In consequence, a new and vitally important field has emerged, the philosophy of information (PI). This essay is the first attempt to analyse the nature of PI systematically. PI is defined as the philosophical field concerned with the critical investigation of the conceptual nature and basic principles of information, including its dynamics, utilisation, and sciences, and the elaboration and (...)
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  35. Understanding the Interaction Between Philosophy and Science in Contemporary Times—An Interview with Professor JIANG Yi.Yi Jiang & Lv Xue - 2024 - Journal of Human Cognition 8 (1):39-58.
    The relationship between philosophy and science in contemporary times is closer than ever. From the methodology perspective, scientific and philosophical research has a clear sequential relationship. It is highlighted in the following aspects: 1. the methodology of scientific research, including theoretical assumptions and data modeling, parallels with apparent similarities in conceptual analysis and logical deduction in philosophy;2. consistency of analytical argumentation methods in scientific research and philosophical research;3. naturalism is currently a research approach that both scientific and philosophical (...)
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  36. Content aggregation, visualization and emergent properties in computer simulations.Gordana Dodig-Crnkovic, Juan M. Durán & D. Slutej - 2010 - In Kai-Mikael Jää-Aro & Thomas Larsson (eds.), SIGRAD 2010 – Content aggregation and visualization. Linköping University Electronic Press. pp. 77-83.
    With the rapidly growing amounts of information, visualization is becoming increasingly important, as it allows users to easily explore and understand large amounts of information. However the field of information visualiza- tion currently lacks sufficient theoretical foundations. This article addresses foundational questions connecting information visualization with computing and philosophy studies. The idea of multiscale information granula- tion is described based on two fundamental concepts: information (structure) and computation (process). A new information processing paradigm of Granular Computing enables stepwise increase (...)
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  37. Methodological Advances in Experimental Philosophy.Eugen Fischer & Mark Curtis (eds.) - 2019 - London: Bloomsbury Press.
    Until recently, experimental philosophy has been associated with the questionnaire-based study of intuitions; however, experimental philosophers now adapt a wide range of empirical methods for new philosophical purposes. New methods include paradigms for behavioural experiments from across the social sciences as well as computational methods from the digital humanities that can process large bodies of text and evidence. This book offers an accessible overview of these exciting innovations. The volume brings together established and emerging research leaders from several areas (...)
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  38. The Effectiveness of Embedded Values Analysis Modules in Computer Science Education: An Empirical Study.Matthew Kopec, Meica Magnani, Vance Ricks, Roben Torosyan, John Basl, Nicholas Miklaucic, Felix Muzny, Ronald Sandler, Christo Wilson, Adam Wisniewski-Jensen, Cora Lundgren, Kevin Mills & Mark Wells - 2023 - Big Data and Society 10 (1).
    Embedding ethics modules within computer science courses has become a popular response to the growing recognition that CS programs need to better equip their students to navigate the ethical dimensions of computing technologies like AI, machine learning, and big data analytics. However, the popularity of this approach has outpaced the evidence of its positive outcomes. To help close that gap, this empirical study reports positive results from Northeastern’s program that embeds values analysis modules into CS courses. The resulting data suggest (...)
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  39. Scientific knowledge in the age of computation.Sophia Efstathiou, Rune Nydal, Astrid LÆgreid & Martin Kuiper - 2019 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 34 (2):213-236.
    With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management : second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli, Efstathiou and Hislop in our analysis of the use of (...)
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  40. Komputer, Kecerdasan Buatan dan Internet: Filsafat Hubert L. Dreyfus tentang Produk Industri 3.0 dan Industri 4.0 (Computer, Artificial Intelligence and Internet: Dreyfus’s Philosophy on the Product of 3.0 and 4.0 Industries).Zainul Maarif - 2019 - Prosiding Paramadina Research Day.
    The content of this paper is an elaboration of Hubert L. Dreyfus’s philosophical critique of Artificial Intelligence (AI), computers and the internet. Hubert L. Dreyfus (1929-2017) is Ua SA philosopher and alumni of Harvard University who teach at the Massachusetts Institute of Technology (MIT) and University of California, Berkeley. He is a phenomenological philosopher who criticize computer researchers and the artificial intelligence community. In 1965, Dreyfus wrote an article for Rand Corporation titled “Alchemy and Artificial Intelligence” which criticizes the (...)
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  41. (1 other version)Computing Nature.Gordana Dodig-Crncovic & Raffaela Giovagnoli - 2013 - Springer.
    The articles in this volume present a selection of works from the Symposium on Natu-ral/Unconventional Computing at AISB/IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. This book is about nature considered as the totality of physical existence, the universe. By physical we mean all phenomena - objects and processes - that are possible to (...)
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  42. Cognitive Computation sans Representation.Paul Schweizer - 2017 - In Thomas M. Powers (ed.), Philosophy and Computing: Essays in epistemology, philosophy of mind, logic, and ethics. Cham: Springer. pp. 65-84.
    The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational content is (...)
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  43. Dial P for Philosophy (Review of Mary Midgley's Utopias, Dolphins and Computers.). [REVIEW]Ray Scott Percival - 1997 - New Scientist (2066).
    Mary Midgley's book Utopias, Dolphins and Computers will be needed to recharge our more philosophical approach to life as new problems present themselves to humanity at an accelerated rate. The most dangerous attitude to these challenges, Midgley argues, is an anti-intellectualism that fails to see that all approaches presuppose tacit or hidden assumptions, that is a philosophy. One part of our tacit philosophy that is now breaking up is the social contract, according to Mary Midgley in Utopias, (...)
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  44. Inter-level relations in computer science, biology, and psychology.Fred Boogerd, Frank Bruggeman, Catholijn Jonker, Huib Looren de Jong, Allard Tamminga, Jan Treur, Hans Westerhoff & Wouter Wijngaards - 2002 - Philosophical Psychology 15 (4):463–471.
    Investigations into inter-level relations in computer science, biology and psychology call for an *empirical* turn in the philosophy of mind. Rather than concentrate on *a priori* discussions of inter-level relations between 'completed' sciences, a case is made for the actual study of the way inter-level relations grow out of the developing sciences. Thus, philosophical inquiries will be made more relevant to the sciences, and, more importantly, philosophical accounts of inter-level relations will be testable by confronting them with what really (...)
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  45. Wolpert, Chaitin und Wittgenstein über Unmöglichkeit, Unvollständigkeit, das Lügner-Paradoxon, Theismus, die Grenzen der Berechnung, ein nicht-quantenmechanisches Unsicherheitsprinzip und das Universum als Computer – der ultimative Satz in Turing Machine Theory (überarbeitet 2019).Michael Richard Starks - 2020 - In Willkommen in der Hölle auf Erden: Babys, Klimawandel, Bitcoin, Kartelle, China, Demokratie, Vielfalt, Dysgenie, Gleichheit, Hacker, Menschenrechte, Islam, Liberalismus, Wohlstand, Internet, Chaos, Hunger, Krankheit, Gewalt, Künstliche Intelligenz, Krieg. Reality Press. pp. 186-190.
    Ich habe viele kürzliche Diskussionen über die Grenzen der Berechnung und das Universum als Computer gelesen, in der Hoffnung, einige Kommentare über die erstaunliche Arbeit des Polymath Physikers und Entscheidungstheoretikers David Wolpert zu finden, aber habe kein einziges Zitat gefunden und so präsentiere ich diese sehr kurze Zusammenfassung. Wolpert bewies einige verblüffende Unmöglichkeit oder Unvollständigkeit Theoreme (1992 bis 2008-siehe arxiv dot org) über die Grenzen der Schlussfolgerung (Berechnung), die so allgemein sind, dass sie unabhängig von dem Gerät, das die Berechnung, (...)
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  46. Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - 2021 - Philosophy of Science 88 (2):213-233.
    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and uncertainty quantification. Seeing this trade-off for the important epistemic issue (...)
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  47. Computer simulation and the features of novel empirical data.Greg Lusk - 2016 - Studies in History and Philosophy of Science Part A 56:145-152.
    In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining whether, and under (...)
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  48. 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 (...)
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  49. Supervenience and computational explanation in vision theory.Peter Morton - 1993 - Philosophy of Science 60 (1):86-99.
    According to Marr's theory of vision, computational processes of early vision rely for their success on certain "natural constraints" in the physical environment. I examine the implications of this feature of Marr's theory for the question whether psychological states supervene on neural states. It is reasonable to hold that Marr's theory is nonindividualistic in that, given the role of natural constraints, distinct computational theories of the same neural processes may be justified in different environments. But to avoid trivializing computational explanations, (...)
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  50. Computers, Dynamical Systems, Phenomena, and the Mind.Marco Giunti - 1992 - Dissertation, Indiana University
    This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical (...)
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