Results for 'Dean J. Machin'

981 found
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  1. Finding Our Way through Phenotypes.Andrew R. Deans, Suzanna E. Lewis, Eva Huala, Salvatore S. Anzaldo, Michael Ashburner, James P. Balhoff, David C. Blackburn, Judith A. Blake, J. Gordon Burleigh, Bruno Chanet, Laurel D. Cooper, Mélanie Courtot, Sándor Csösz, Hong Cui, Barry Smith & Others - 2015 - PLoS Biol 13 (1):e1002033.
    Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that (...)
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  2. The Oxford handbook of metaphysics.Michael J. Loux & Dean W. Zimmerman (eds.) - 2003 - New York: Oxford University Press.
    The Oxford Handbook of Metaphysics offers the most authoritative and compelling guide to this diverse and fertile field of philosophy. Twenty-four of the world's most distinguished specialists provide brand-new essays about 'what there is': what kinds of things there are, and what relations hold among entities falling under various categories. They give the latest word on such topics as identity, modality, time, causation, persons and minds, freedom, and vagueness. The Handbook's unrivaled breadth and depth make it the definitive reference work (...)
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  3. Enkinaesthesia: the fundamental challenge for machine consciousness.Susan A. J. Stuart - 2011 - International Journal of Machine Consciousness 3 (1):145-162.
    In this short paper I will introduce an idea which, I will argue, presents a fundamental additional challenge to the machine consciousness community. The idea takes the questions surrounding phenomenology, qualia and phenomenality one step further into the realm of intersubjectivity but with a twist, and the twist is this: that an agent’s intersubjective experience is deeply felt and necessarily co-affective; it is enkinaesthetic, and only through enkinaesthetic awareness can we establish the affective enfolding which enables first the perturbation, and (...)
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  4. The Machine Conception of the Organism in Development and Evolution: A Critical Analysis.Daniel J. Nicholson - 2014 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 48:162-174.
    This article critically examines one of the most prevalent metaphors in modern biology, namely the machine conception of the organism (MCO). Although the fundamental differences between organisms and machines make the MCO an inadequate metaphor for conceptualizing living systems, many biologists and philosophers continue to draw upon the MCO or tacitly accept it as the standard model of the organism. This paper analyses the specific difficulties that arise when the MCO is invoked in the study of development and evolution. In (...)
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  5. Organisms ≠ Machines.Daniel J. Nicholson - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):669-678.
    The machine conception of the organism (MCO) is one of the most pervasive notions in modern biology. However, it has not yet received much attention by philosophers of biology. The MCO has its origins in Cartesian natural philosophy, and it is based on the metaphorical redescription of the organism as a machine. In this paper I argue that although organisms and machines resemble each other in some basic respects, they are actually very different kinds of systems. I submit that the (...)
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  6. Is the Cell Really a Machine?Daniel J. Nicholson - 2019 - Journal of Theoretical Biology 477:108–126.
    It has become customary to conceptualize the living cell as an intricate piece of machinery, different to a man-made machine only in terms of its superior complexity. This familiar understanding grounds the conviction that a cell's organization can be explained reductionistically, as well as the idea that its molecular pathways can be construed as deterministic circuits. The machine conception of the cell owes a great deal of its success to the methods traditionally used in molecular biology. However, the recent introduction (...)
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  7. Reconceptualizing the Organism: From Complex Machine to Flowing Stream.Daniel J. Nicholson - 2018 - In Daniel J. Nicholson & John Dupré (eds.), Everything Flows: Towards a Processual Philosophy of Biology. Oxford, United Kingdom: Oxford University Press.
    This chapter draws on insights from non-equilibrium thermodynamics to demonstrate the ontological inadequacy of the machine conception of the organism. The thermodynamic character of living systems underlies the importance of metabolism and calls for the adoption of a processual view, exemplified by the Heraclitean metaphor of the stream of life. This alternative conception is explored in its various historical formulations and the extent to which it captures the nature of living systems is examined. Following this, the chapter considers the metaphysical (...)
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  8. (1 other version)Wittgenstein and the Problem of Machine Consciousness.J. C. Nyíri - 1989 - Grazer Philosophische Studien 33 (1):375-394.
    For any given society, its particular technology of communication has far-reaching consequences, not merely as regards social organization, but on the epistemic level as well. Plato's name-theory of meaning represents the transition from the age of primary orality to that of literacy; Wittgenstein's use-theory of meaning stands for the transition from the age of literacy to that of a second orality (audiovisual communication, electronic information processing). On the basis of a use-theory of meaning the problem of machine consciousness, to which (...)
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  9. Machine Intelligence, New Interfaces, and the Art of the Soluble.Michael J. Lyons - 2017 - Arxiv.
    Position: (1) Partial solutions to machine intelligence can lead to systems which may be useful creating interesting and expressive musical works. (2) An appropriate general goal for this field is augmenting human expression. (3) The study of the aesthetics of human augmentation in musical performance is in its infancy. -/- CHI 2015 Workshop on Collaborating with Intelligent Machines: Interfaces for Creative Sound, April 18, 2015, Seoul, Republic of Korea.
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  10. Ghosting Inside the Machine: Student Cheating, Online Education and the Omertà of Institutional Liars.Shane J. Ralston - 2021 - In Alison MacKenzie, Jennifer Rose & Ibrar Bhatt (eds.), The Epistemology of Deceit in the Postdigital Era: Dupery by Design. Springer. pp. 251-264.
    'Ghosting' or the unethical practice of having someone other than the student registered in the course take the student's exams, complete their assignments and write their essays has become a common method of cheating in today's online higher education learning environment. Internet-based teaching technology and deceit go hand-in-hand because the technology establishes a set of perverse incentives for students to cheat and institutions to either tolerate or encourage this highly unethical form of behavior. For students, cheating becomes an increasingly attractive (...)
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  11. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...)
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  12. Speech Emotion Recognition using Machine Learning and Librosa.Sivashree S. Pavithra J. - 2025 - International Journal of Advanced Research in Education and Technology 12 (1):224-228.
    Emotion recognition from speech is an important aspect of human-computer interaction (HCI) systems, allowing machines to better understand human emotions and respond accordingly. This paper explores the use of machine learning techniques to recognize emotions in speech signals. We leverage the librosa library for feature extraction from audio files and train multiple machine learning models, including Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbors (k-NN), to classify speech emotions. The aim is to create an automated system capable of (...)
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  13. Widening Access to Applied Machine Learning With TinyML.Vijay Reddi, Brian Plancher, Susan Kennedy, Laurence Moroney, Pete Warden, Lara Suzuki, Anant Agarwal, Colby Banbury, Massimo Banzi, Matthew Bennett, Benjamin Brown, Sharad Chitlangia, Radhika Ghosal, Sarah Grafman, Rupert Jaeger, Srivatsan Krishnan, Maximilian Lam, Daniel Leiker, Cara Mann, Mark Mazumder, Dominic Pajak, Dhilan Ramaprasad, J. Evan Smith, Matthew Stewart & Dustin Tingley - 2022 - Harvard Data Science Review 4 (1).
    Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...)
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  14. Is Artificial General Intelligence Impossible?William J. Rapaport - 2024 - Cosmos+Taxis 12 (5+6):5-22.
    In their Why Machines Will Never Rule the World, Landgrebe and Smith (2023) argue that it is impossible for artificial general intelligence (AGI) to succeed, on the grounds that it is impossible to perfectly model or emulate the “complex” “human neurocognitive system”. However, they do not show that it is logically impossible; they only show that it is practically impossible using current mathematical techniques. Nor do they prove that there could not be any other kinds of theories than those in (...)
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  15. The Machine Speaks: Conversational AIs and the importance of effort to relationships of meaning.Anna Hartford & Dan J. Stein - 2024 - JMIR Mental Health 11.
    The focus of debates about conversational AIs (CAIs) has largely been on social and ethical concerns that arise when we speak to machines. What is gained and what is lost when we replace our human interlocutors—including our human therapists— with AIs? Here, we focus instead on a distinct and growing phenomenon: letting machines speak for us. What is at stake when we replace our own efforts at interpersonal engagement with CAIs? The purpose of these technologies is, in part, to remove (...)
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  16. Should machines be tools or tool-users? Clarifying motivations and assumptions in the quest for superintelligence.Dan J. Bruiger - manuscript
    Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping point for singularity), projecting (...)
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  17. Instrumental Divergence.J. Dmitri Gallow - 2024 - Philosophical Studies:1-27.
    The thesis of instrumental convergence holds that a wide range of ends have common means: for instance, self preservation, desire preservation, self improvement, and resource acquisition. Bostrom contends that instrumental convergence gives us reason to think that "the default outcome of the creation of machine superintelligence is existential catastrophe". I use the tools of decision theory to investigate whether this thesis is true. I find that, even if intrinsic desires are randomly selected, instrumental rationality induces biases towards certain kinds of (...)
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  18. Agricultural technologies as living machines: toward a biomimetic conceptualization of technology.V. Blok & H. G. J. Gremmen - 2018 - Ethics, Policy and Environment 21 (2):246-263.
    Smart Farming Technologies raise ethical issues associated with the increased corporatization and industrialization of the agricultural sector. We explore the concept of biomimicry to conceptualize smart farming technologies as ecological innovations which are embedded in and in accordance with the natural environment. Such a biomimetic approach of smart farming technologies takes advantage of its potential to mitigate climate change, while at the same time avoiding the ethical issues related to the industrialization of the agricultural sector. We explore six principles of (...)
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  19. Excavating “Excavating AI”: The Elephant in the Gallery.Michael J. Lyons - 2020 - arXiv 2009:1-15.
    Two art exhibitions, “Training Humans” and “Making Faces,” and the accompanying essay “Excavating AI: The politics of images in machine learning training sets” by Kate Crawford and Trevor Paglen, are making substantial impact on discourse taking place in the social and mass media networks, and some scholarly circles. Critical scrutiny reveals, however, a self-contradictory stance regarding informed consent for the use of facial images, as well as serious flaws in their critique of ML training sets. Our analysis underlines the non-negotiability (...)
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  20. National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge.Daniel L. Rubin, Suzanna E. Lewis, Chris J. Mungall, Misra Sima, Westerfield Monte, Ashburner Michael, Christopher G. Chute, Ida Sim, Harold Solbrig, M. A. Storey, Barry Smith, John D. Richter, Natasha Noy & Mark A. Musen - 2006 - Omics: A Journal of Integrative Biology 10 (2):185-198.
    The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create (...)
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  21. (1 other version)Review of: Death or Disability?: The ‘Carmentis Machine’ and Decision-Making for Critically Ill Children. [REVIEW]J. Paul Kelleher - forthcoming - Mind.
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  22. The Concept of Mechanism in Biology.Daniel J. Nicholson - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (1):152-163.
    The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in the philosophy of biology, (...)
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  23.  70
    Student Dropout Analysis for School Education.J. Siva Prashanth - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (1):1-12.
    This project explores the issue of high dropout rates in school education. We utilize a machine learning-driven approach to analyze data on student demographics, academic performance, attendance, and socioeconomic factors. By identifying at-risk students early, we aim to provide targeted interventions that will reduce dropout rates. This document outlines the structure, methodology, and findings of the project, leveraging techniques such as data preprocessing, model training, hyperparameter tuning, and risk stratification.
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  24. Consciousness: A Four-fold taxonomy.J. Jonkisz - 2012 - Journal of Consciousness Studies 19 (11-12):55-82.
    This paper argues that the many and various conceptions of consciousness propounded by cognitive scientists and philosophers can all be understood as constituted with reference to four fundamental sorts of criterion: epistemic (concerned with kinds of consciousness), semantic (dealing with orders of consciousness), physiological (reflecting states of consciousness), and pragmatic (seeking to capture types of consciousness). The resulting four-fold taxonomy, intended to be exhaustive, suggests that all of the distinct varieties of consciousness currently encountered in cognitive neuroscience, the philosophy of (...)
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  25. “Excavating AI” Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset.Michael J. Lyons - 2021 - arXiv 2107:1-20.
    Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay “Excavating AI: The Politics of Images in Machine Learning Training Sets.” The present article recounts the (...)
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  26. Artificial Speech and Its Authors.Philip J. Nickel - 2013 - Minds and Machines 23 (4):489-502.
    Some of the systems used in natural language generation (NLG), a branch of applied computational linguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams’ account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence embedded in (...)
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  27. On Being the Right Size, Revisited: The Problem with Engineering Metaphors in Molecular Biology.Daniel J. Nicholson - 2020 - In Sune Holm & Maria Serban (eds.), Philosophical Perspectives on the Engineering Approach in Biology: Living Machines? New York: Routledge. pp. 40-68.
    In 1926, Haldane published an essay titled 'On Being the Right Size' in which he argued that the structure, function, and behavior of an organism are strongly conditioned by the physical forces that exert the greatest impact at the scale at which it exists. This chapter puts Haldane’s insight to work in the context of contemporary cell and molecular biology. Owing to their minuscule size, cells and molecules are subject to very different forces than macroscopic organisms. In a sense, macroscopic (...)
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  28. Syntax, Semantics, and Computer Programs.William J. Rapaport - 2020 - Philosophy and Technology 33 (2):309-321.
    Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.
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  29. Computers Are Syntax All the Way Down: Reply to Bozşahin.William J. Rapaport - 2019 - Minds and Machines 29 (2):227-237.
    A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.
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  30. The Role of Administrative Procedures and Regulations in Enhancing the Performance of The Educational Institutions - The Islamic University in Gaza is A Model.Ashraf A. M. Salama, Youssef M. Abu Amuna, Mazen J. Al Shobaki & Samy S. Abu-Naser - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (2):14-27.
    The study aimed to identify the role of administrative procedures and systems in enhancing the performance of the educational institutions in the Islamic University in Gaza. To achieve the research objectives, the researchers used the analytical descriptive approach to collect information. The researchers used the questionnaire distributed to three categories of employees at the Islamic University (senior management, faculty members, their assistants and members of the administrative board). A random sample of 314 employees was selected and 276 questionnaires were retrieved (...)
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  31. On the morality of artificial agents.Luciano Floridi & J. W. Sanders - 2004 - Minds and Machines 14 (3):349-379.
    Artificial agents (AAs), particularly but not only those in Cyberspace, extend the class of entities that can be involved in moral situations. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil). In this paper, we clarify the concept of agent and go on to separate the concerns of morality and responsibility of agents (most (...)
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  32. Diagnosis of Blood Cells Using Deep Learning.Ahmed J. Khalil & Samy S. Abu-Naser - 2022 - Dissertation, University of Tehran
    In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...)
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  33. Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing.William J. Rapaport - 2012 - International Journal of Signs and Semiotic Systems 2 (1):32-71.
    In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...)
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  34. Of (zombie) mice and animats.S. J. Nasuto & J. M. Bishop - 2013 - In Vincent Müller (ed.), Philosophy and Theory of Artificial Intelligence. Springer. pp. 85-107.
    The Chinese Room Argument purports to show that‘ syntax is not sufficient for semantics’; an argument which led John Searle to conclude that ‘programs are not minds’ and hence that no computational device can ever exhibit true understanding. Yet, although this controversial argument has received a series of criticisms, it has withstood all attempts at decisive rebuttal so far. One of the classical responses to CRA has been based on equipping a purely computational device with a physical robot body. This (...)
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  35.  64
    Developing Software to Translate other Texts and Resource Materials from English to other Indian Regional Languages.J. Sai Charan - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (1):1-10.
    In an increasingly interconnected world, language barriers continue to hinder effective communication across diverse populations. BharathLingo addresses this challenge by offering a user-friendly text translation platform specifically designed to facilitate translation between English and multiple Indian regional languages such as Hindi, Telugu, Bengali, Tamil, and more. Developed using Flask and powered by machine translation algorithms, BharathLingo allows users to input text manually or upload files for translation, delivering instant and accurate translations. The platform’s seamless interface and commitment to privacy make (...)
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  36. CASTANEDA, Hector-Neri (1924–1991).William J. Rapaport - 2005 - In John R. Shook (ed.), The Dictionary of Modern American Philosophers, 1860-1960. Thoemmes Press.
    H´ector-Neri Casta˜neda-Calder´on (December 13, 1924–September 7, 1991) was born in San Vicente Zacapa, Guatemala. He attended the Normal School for Boys in Guatemala City, later called the Military Normal School for Boys, from which he was expelled for refusing to fight a bully; the dramatic story, worthy of being filmed, is told in the “De Re” section of his autobiography, “Self-Profile” (1986). He then attended a normal school in Costa Rica, followed by studies in philosophy at the University of San (...)
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  37.  51
    Online Personalized Learning Remediation/Tutoring Tool: A Teacher Recommendation System.D. J. Abhiram - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (5):1-16.
    Online education will be paired by developing intelligent systems that can provide personalization to the learner. To that extent ,this paper is proposing the design for an Online Personalized Learning Remediation/Tutoring Tool to help learners find the most suitable teachers for certain topics. The tool relies on a dataset of teacher profiles, comprising the subjects taught, video links, ratings, and experience, so that using machine learning techniques, it could recommend top educators. Applying feature extraction using CountVectorizer and recommendation based on (...)
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  38. Yes, She Was!: Reply to Ford’s “Helen Keller Was Never in a Chinese Room”.William J. Rapaport - 2011 - Minds and Machines 21 (1):3-17.
    Ford’s Helen Keller Was Never in a Chinese Room claims that my argument in How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room fails because Searle and I use the terms ‘syntax’ and ‘semantics’ differently, hence are at cross purposes. Ford has misunderstood me; this reply clarifies my theory.
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  39. Counterfactuals of Freedom and the Luck Objection to Libertarianism.Robert J. Hartman - 2017 - Journal of Philosophical Research 42 (1):301-312.
    Peter van Inwagen famously offers a version of the luck objection to libertarianism called the ‘Rollback Argument.’ It involves a thought experiment in which God repeatedly rolls time backward to provide an agent with many opportunities to act in the same circumstance. Because the agent has the kind of freedom that affords her alternative possibilities at the moment of choice, she performs different actions in some of these opportunities. The upshot is that whichever action she performs in the actual-sequence is (...)
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  40. In Defense of Truth: Skepticism, Morality, and The Matrix.Barry Smith & J. Erion Gerald - 2002 - In W. Irwin (ed.), Philosophy and The Matrix. Open Court. pp. 16-27.
    The Matrix exposes us to the uncomfortable worries of philosophical skepticism in an especially compelling way. However, with a bit more reflection, we can see why we need not share the skeptic’s doubts about the existence of the world. Such doubts are appropriate only in the very special context of the philosophical seminar. When we return to normal life we see immediately that they are groundless. Furthermore, we see also the drastic mistake that Cypher commits in turning his back upon (...)
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  41. Do submarines swim? Methodological dualism and anthropomorphizing AlphaGo.Vincent J. Carchidi - 2022 - AI and Society 39 (775-787):1-13.
    The victories of the Go-playing artificial intelligence “AlphaGo” against professional player Lee Sedol in 2016 had a profound impact on public and academic perceptions of AI. This event shocked observers, as the ability of a machine to defeat a world champion human in a highly complex game seemed to indicate that a machine had achieved human-like—or more than human—intelligence. But why was AlphaGo so readily anthropomorphized by academic and non-academic audiences alike? Drawing from existing analyses of reactions to and arguments (...)
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  42. How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room.William J. Rapaport - 2006 - Minds and Machines 16 (4):381-436.
    A computer can come to understand natural language the same way Helen Keller did: by using “syntactic semantics”—a theory of how syntax can suffice for semantics, i.e., how semantics for natural language can be provided by means of computational symbol manipulation. This essay considers real-life approximations of Chinese Rooms, focusing on Helen Keller’s experiences growing up deaf and blind, locked in a sort of Chinese Room yet learning how to communicate with the outside world. Using the SNePS computational knowledge-representation system, (...)
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  43. Persons: Human and Divine.Daniel J. Hill & Greg Welty - 2009 - Ars Disputandi 9:1566-5399.
    This is a book review of Peter van Inwagen and Dean Zimmerman (eds.), Persons: Human and Divine (Oxford: Oxford Univ. Press, 2007).
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  44. Because mere calculating isn't thinking: Comments on Hauser's Why Isn't My Pocket Calculator a Thinking Thing?.William J. Rapaport - 1993 - Minds and Machines 3 (1):11-20.
    Hauser argues that his pocket calculator (Cal) has certain arithmetical abilities: it seems Cal calculates. That calculating is thinking seems equally untendentious. Yet these two claims together provide premises for a seemingly valid syllogism whose conclusion - Cal thinks - most would deny. He considers several ways to avoid this conclusion, and finds them mostly wanting. Either we ourselves can't be said to think or calculate if our calculation-like performances are judged by the standards proposed to rule out Cal; or (...)
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  45. Preface to Where Does I Come From? Special Issue on Subjectivity and the Debate over Computational Cognitive Science.Mary Galbraith & William J. Rapaport - 1995 - Minds and Machines 5 (4):513-515.
    For centuries, philosophers studying the great mysteries of human subjectivity have focused on the mind/body problem and the difference between human beings and animals. Now a new ontological question takes center stage: to what extent can a manufactured object (a computer) exhibit qualities of mind? There have been passionate exchanges between those who believe that a "manufactured mind" is possible and those who believe that mind cannot exist except as a living, socially situated, embodied person. As with earlier arguments, this (...)
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  46. Peeking Inside the Black Box: A New Kind of Scientific Visualization.Michael T. Stuart & Nancy J. Nersessian - 2018 - Minds and Machines 29 (1):87-107.
    Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...)
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  47. AI-Driven Innovations in Agriculture: Transforming Farming Practices and Outcomes.Jehad M. Altayeb, Hassam Eleyan, Nida D. Wishah, Abed Elilah Elmahmoum, Ahmed J. Khalil, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Applied Research (Ijaar) 8 (9):1-6.
    Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...)
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  48. AI-Driven Learning: Advances and Challenges in Intelligent Tutoring Systems.Amjad H. Alfarra, Lamis F. Amhan, Msbah J. Mosa, Mahmoud Ali Alajrami, Faten El Kahlout, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Applied Research (Ijaar) 8 (9):24-29.
    Abstract: The incorporation of Artificial Intelligence (AI) into educational technology has dramatically transformed learning through Intelligent Tutoring Systems (ITS). These systems utilize AI to offer personalized, adaptive instruction tailored to each student's needs, thereby improving learning outcomes and engagement. This paper examines the development and impact of ITS, focusing on AI technologies such as machine learning, natural language processing, and adaptive algorithms that drive their functionality. Through various case studies and applications, it illustrates how ITS have revolutionized traditional educational methods (...)
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  49.  81
    From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation.Juan Manuel Durán, David van der Vloed, Arnout Ruifrok & Rolf J. F. Ypma - 2024 - Forensic Science International: Synergy 9.
    Techniques from artificial intelligence (AI) can be used in forensic evidence evaluation and are currently applied in biometric fields. However, it is generally not possible to fully understand how and why these algorithms reach their conclusions. Whether and how we should include such ‘black box’ algorithms in this crucial part of the criminal law system is an open question that has not only scientific but also ethical, legal, and philosophical angles. Ideally, the question should be debated by people with diverse (...)
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  50. Self-Absorption in the Digital Era: A Review of "Self-Improvement Technologies of the Soul in the Age of Artificial Intelligence" by Mark Coeckelbergh. [REVIEW]James J. Hughes - 2024 - Journal of Ethics and Emerging Technologies 33 (1).
    Mark Coeckelbergh is a Belgian philosopher who specializes in the philosophy of technology. His work primarily explores the intersection of technology and society, specifically the philosophical implications of emerging technologies such as AI and robotics. He has written on whether machines can be moral agents and how ethical frameworks should be applied to autonomous machines. He has a broad philosophical perspective drawing on classical sources, Eastern philosophy, Marxism, Foucault, phenomenology, and the postmodernists. In this short text, he brings his remarkable (...)
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