Results for 'Knowing machines'

972 found
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  1. A Machine That Knows Its Own Code.Samuel A. Alexander - 2014 - Studia Logica 102 (3):567-576.
    We construct a machine that knows its own code, at the price of not knowing its own factivity.
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  2. Artificial knowing: gender and the thinking machine.John Sullins - 1999 - Acm Sigcas Computers and Society 29 (1):47-48.
    A book Review of Artificial Knowing Gender and the Thinking Machine, by Alison Adam, Routledge: Taylor and Francis, 1998.
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  3. Measuring the intelligence of an idealized mechanical knowing agent.Samuel Alexander - 2020 - Lecture Notes in Computer Science 12226.
    We define a notion of the intelligence level of an idealized mechanical knowing agent. This is motivated by efforts within artificial intelligence research to define real-number intelligence levels of compli- cated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent to be the supremum of the computable ordinals that have codes the agent knows to (...)
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  4. Why Machine-Information Metaphors are Bad for Science and Science Education.Massimo Pigliucci & Maarten Boudry - 2011 - Science & Education 20 (5-6):471.
    Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- (...)
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  5. Machine intelligence: a chimera.Mihai Nadin - 2019 - AI and Society 34 (2):215-242.
    The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that conceived (...)
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  6. Artificial Knowing Otherwise.Os Keyes & Kathleen Creel - 2022 - Feminist Philosophy Quarterly 8 (3).
    While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new (...)
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  7. Fast-Collapsing Theories.Samuel A. Alexander - 2013 - Studia Logica (1):1-21.
    Reinhardt’s conjecture, a formalization of the statement that a truthful knowing machine can know its own truthfulness and mechanicalness, was proved by Carlson using sophisticated structural results about the ordinals and transfinite induction just beyond the first epsilon number. We prove a weaker version of the conjecture, by elementary methods and transfinite induction up to a smaller ordinal.
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  8. Time Travel and Time Machines.Douglas Kutach - 2013 - In Adrian Bardon & Heather Dyke (eds.), A Companion to the Philosophy of Time. Malden, MA: Wiley-Blackwell. pp. 301–314.
    Thinking about time travel is an entertaining way to explore how to understand time and its location in the broad conceptual landscape that includes causation, fate, action, possibility, experience, and reality. It is uncontroversial that time travel towards the future exists, and time travel to the past is generally recognized as permitted by Einstein’s general theory of relativity, though no one knows yet whether nature truly allows it. Coherent time travel stories have added flair to traditional debates over the metaphysical (...)
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  9. Can We Think That Machines Are Conscious? A Survey of Philosophical Problems Facing the Attribution of Consciousness to Machines.Parker Settecase - forthcoming - Journal of Artificial Intelligence and Consciousness 11 (01):35-50.
    In this paper I’ll examine whether we could be justified in attributing consciousness to artificial intelligent systems. First, I’ll give a brief history of the concept of artificial intelligence (AI) and get clear on the terms I’ll be using. Second, I’ll briefly review the kinds of AI programs on offer today, identifying which research program I think provides the best candidate for machine consciousness. Lastly, I’ll consider the three most plausible ways of knowing whether a machine is conscious: (1) (...)
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  10. Deepfake detection by human crowds, machines, and machine-informed crowds.Matthew Groh, Ziv Epstein, Chaz Firestone & Rosalind Picard - 2022 - Proceedings of the National Academy of Sciences 119 (1):e2110013119.
    The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s prediction (...)
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  11. How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  12. The Animal for which Animality is an Issue: nietzsche, agamben, and the anthropological machine.Mathew Abbott - 2011 - Angelaki 16 (4):87-99.
    There is congruence between Nietzsche’s philosophy of life and the biopolitical philosophy of Giorgio Agamben. For both philosophers the human animal possesses a divided relationship to its being alive. For both philosophers this division is of a political nature, such that membership in political community as we know it is conditional on the human animal’s alienation from its biological being. Both philosophers are also concerned with the possibility of transformation and, because of the connection they establish between politics and animality, (...)
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  13. Performance vs. competence in human–machine comparisons.Chaz Firestone - 2020 - Proceedings of the National Academy of Sciences 41.
    Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when (...)
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  14. MInd and Machine: at the core of any Black Box there are two (or more) White Boxes required to stay in.Lance Nizami - 2020 - Cybernetics and Human Knowing 27 (3):9-32.
    This paper concerns the Black Box. It is not the engineer’s black box that can be opened to reveal its mechanism, but rather one whose operations are inferred through input from (and output to) a companion observer. We are observers ourselves, and we attempt to understand minds through interactions with their host organisms. To this end, Ranulph Glanville followed W. Ross Ashby in elaborating the Black Box. The Black Box and its observer together form a system having different properties than (...)
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  15. And Then the Hammer Broke: Reflections on Machine Ethics from Feminist Philosophy of Science.Andre Ye - forthcoming - Pacific University Philosophy Conference.
    Vision is an important metaphor in ethical and political questions of knowledge. The feminist philosopher Donna Haraway points out the “perverse” nature of an intrusive, alienating, all-seeing vision (to which we might cry out “stop looking at me!”), but also encourages us to embrace the embodied nature of sight and its promises for genuinely situated knowledge. Current technologies of machine vision – surveillance cameras, drones (for war or recreation), iPhone cameras – are usually construed as instances of the former rather (...)
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  16. Prognostic System for Heart Disease using Machine Learning: A Review.R. Senthilkumar - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):33-38.
    In today’s world it became difficult for daily routine check-up. The Heart disease system is an end user support and online consultation project. Here the motto behind it is to make a person to know about their heart related problem and according to it formulate them how much vital the disease is. It will be easy to access and keep track of their respective health. Thus, it’s important to predict the disease as earliest. Attributes such as Bp, Cholesterol, Diabetes are (...)
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  17. The use of scripture in the beast machine controversy.Lloyd Strickland - 2015 - In David Beck (ed.), Knowing Nature in Early Modern Europe. Brookfield, Vermont: Pickering & Chatto. pp. 65-82.
    The impression we are often given by historians of philosophy is that the readiness of medieval philosophers to appeal to authorities, such as The Bible, the Church, and Aristotle, was not shared by many early modern philosophers, for whom there was a marked preference to look for illumination via experience, the exercise of reason, or a combination of the two. Although this may be accurate, broadly speaking, it is notable that, in spite of the waning enthusiasm for deferring to traditional (...)
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  18. Review of The Emotion Machine by Marvin Minsky (2007).Michael Starks - 2016 - In Suicidal Utopian Delusions in the 21st Century: Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2017 2nd Edition Feb 2018. Las Vegas, USA: Reality Press. pp. 627.
    Dullest book by a major scientist I have ever read. I suppose if you know almost nothing about cognition or AI research you might find this book useful. For anyone else it is a horrific bore. There are hundreds of books in cog sci, robotics, AI, evolutionary psychology and philosophy offering far more info and insight on cognition than this one. Minsky is a top rate senior scientist but it barely shows here. He has alot of good references but they (...)
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  19. The Ghosts I Do Know: Rhythm, Dickinson, Crane.Dustin Hellberg - 2014 - Consciousness, Literature and the Arts 15 (3).
    This paper will examine poetry and rhythm in relation to biological and evolutionary models in order to develop a hypothetical methodology by which certain aspects of literature may be examined through an evolutionary lens. It is by no means an attempt at a finalizing or totalizing way of examining literature, but as such attempts have largely been ignored or assaulted, there is a rather large niche to fill. Hence this article will attempt to redefine literature as a ‘Third Level Darwin (...)
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  20. Cosmos is a (fatalistic) state machine: Objective theory (cosmos, objective reality, scientific image) vs. Subjective theory (consciousness, subjective reality, manifest image).Xiaoyang Yu - manuscript
    As soon as you believe an imagination to be nonfictional, this imagination becomes your ontological theory of the reality. Your ontological theory (of the reality) can describe a system as the reality. However, actually this system is only a theory/conceptual-space/imagination/visual-imagery of yours, not the actual reality (i.e., the thing-in-itself). An ontological theory (of the reality) actually only describes your (subjective/mental) imagination/visual-imagery/conceptual-space. An ontological theory of the reality, is being described as a situation model (SM). There is no way to prove/disprove (...)
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  21. Glanville’s ‘Black Box’: what can an Observer know?Lance Nizami - 2020 - Revista Italiana di Filosofia Del Linguaggio 14 (2):47-62.
    A ‘Black Box’ cannot be opened to reveal its mechanism. Rather, its operations are inferred through input from (and output to) an ‘observer’. All of us are observers, who attempt to understand the Black Boxes that are Minds. The Black Box and its observer constitute a system, differing from either component alone: a ‘greater’ Black Box to any further-external-observer. To Glanville (1982), the further-external-observer probes the greater-Black-Box by interacting directly with its core Black Box, ignoring that Box’s immediate observer. In (...)
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  22. Arriagada Bruneau, G. (2021). “Living with Robots: What every anxious human needs to know”. Ruth Aylett and Patricia A. Vargas, MIT Press, 2021. [REVIEW]Gabriela Arriagada Bruneau - 2021 - Journal of Ethics and Emerging Technologies 31:1-4.
    This book takes us to explore the 'life of robots' and presents us with a refreshing narrative that demystifies their recurrent anthropomorphic understanding. General ideas of what robots are and what they can do often lack knowledge about the limitations, functionality, and complexity needed to turn a robot into a fully operational machine. In this book, the authors portray a grounded and accessible description of current research developing robots. They are insightful, yet still allow the reader to understand basic processes (...)
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  23. Heidegger’s Metaphysics, a Theory of Human Perception: Neuroscience Anticipated, Thesis of Violent Man, Doctrine of the Logos.Hermann G. W. Burchard - 2020 - Philosophy Study 10 (11).
    In this essay, our goal is to discover science in Martin Heidegger's Introduction to Metaphysics, lecture notes for his 1935 summer semester course, because, after all, his subject is metaphysica generalis, or ontology, and this could be construed as a theory of the human brain. Here, by means of verbatim quotes from his text, we attempt to show that indeed these lectures can be viewed as suggestion for an objective scientific theory of human perception, the human capacity for deciphering phenomena, (...)
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  24. Varieties of Artificial Moral Agency and the New Control Problem.Marcus Arvan - 2022 - Humana.Mente - Journal of Philosophical Studies 15 (42):225-256.
    This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral error; and (3) 'Human-Like (...)
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  25. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  26. Life and consciousness – The Vedāntic view.Bhakti Niskama Shanta - 2015 - Communicative and Integrative Biology 8 (5):e1085138.
    In the past, philosophers, scientists, and even the general opinion, had no problem in accepting the existence of consciousness in the same way as the existence of the physical world. After the advent of Newtonian mechanics, science embraced a complete materialistic conception about reality. Scientists started proposing hypotheses like abiogenesis (origin of first life from accumulation of atoms and molecules) and the Big Bang theory (the explosion theory for explaining the origin of universe). How the universe came to be what (...)
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  27.  60
    As máquinas podem cuidar?E. M. Carvalho - 2024 - O Que Nos Faz Pensar 31 (53):6-24.
    Applications and devices of artificial intelligence are increasingly common in the healthcare field. Robots fulfilling some caregiving functions are not a distant future. In this scenario, we must ask ourselves if it is possible for machines to care to the extent of completely replacing human care and if such replacement, if possible, is desirable. In this paper, I argue that caregiving requires know-how permeated by affectivity that is far from being achieved by currently available machines. I also maintain (...)
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  28. (1 other version)Neutrosophic Transport and Assignment Issues.Florentin Smarandache - 2023 - Infinite Study.
    We all know that problems of transportation and allocation appear frequently in practical life. We need to transfer materials from production centers to consumption centers to secure the areas’ need for the transported material or allocate machines or people to do a specific job at the lowest cost, or in the shortest time. We know that the cost factors Time is one of the most important factors that decision-makers care about because it plays an “important” role in many of (...)
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  29. 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 (...)
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  30. The best memories: Identity, narrative, and objects.Richard Heersmink & Christopher Jade McCarroll - 2019 - In Timothy Shanahan & Paul Smart (eds.), Blade Runner 2049: A Philosophical Exploration. Abingdon, UK: Routledge. pp. 87-107.
    Memory is everywhere in Blade Runner 2049. From the dead tree that serves as a memorial and a site of remembrance (“Who keeps a dead tree?”), to the ‘flashbulb’ memories individuals hold about the moment of the ‘blackout’, when all the electronic stores of data were irretrievably erased (“everyone remembers where they were at the blackout”). Indeed, the data wiped out in the blackout itself involves a loss of memory (“all our memory bearings from the time, they were all damaged (...)
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  31. Towards Pedagogy supporting Ethics in Analysis.Marie Oldfield - 2022 - Journal of Humanistic Mathematics 12 (2).
    Over the past few years we have seen an increasing number of legal proceedings related to inappropriately implemented technology. At the same time career paths have diverged from the foundation of statistics out to Data Scientist, Machine Learning and AI. All of these new branches being fundamentally branches of statistics and mathematics. This has meant that formal training has struggled to keep up with what is required in the plethora of new roles. Mathematics as a taught subject is still based (...)
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  32.  55
    Some Points on Research.Subhasis Chattopadhyay - 2024 - Indian Catholic Matters.
    Research is increasing becoming AI dependent and is being done for fulfilment of various academic requirements. Researchers are spending a lot of time 'reinventing the wheel' and use word-padding to trick themselves and their examiners/peers happy. Often bibligraphies are longer than the research papers just to impress others. Often researchers do not know how to cita and rely solely on machine-created bibliographies which are insufficient bibligraphies. They tend to follow the letter of the law, discarding the spirit of the law. (...)
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  33. Mad Speculation and Absolute Inhumanism: Lovecraft, Ligotti, and the Weirding of Philosophy.Ben Woodard - 2011 - Continent 1 (1):3-13.
    continent. 1.1 : 3-13. / 0/ – Introduction I want to propose, as a trajectory into the philosophically weird, an absurd theoretical claim and pursue it, or perhaps more accurately, construct it as I point to it, collecting the ground work behind me like the Perpetual Train from China Mieville's Iron Council which puts down track as it moves reclaiming it along the way. The strange trajectory is the following: Kant's critical philosophy and much of continental philosophy which has followed, (...)
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  34. Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - 2022 - In Keya Maitra & Jennifer McWeeny (eds.), Feminist Philosophy of Mind. New York, NY, United States of America: Oxford University Press, Usa.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we (...)
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  35. 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 masterminds (...)
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  36. Une théorie morale peut-elle être cognitivement trop exigeante?Nicolas Delon - 2015 - Implications Philosophiques.
    Starting from the typical case of utilitarianism, I distinguish three ways a moral theory may be deemed (over-)demanding: practical, epistemic, and cognitive. I focus on the latter, whose specific nature has been overlooked. Taking animal ethics as a case study, I argue that knowledge of human cognition is critical to spelling out moral theories (including their implications) that are accessible and acceptable to the greatest number of agents. In a nutshell: knowing more about our cognitive apparatus with a view (...)
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  37. A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers.Lorna Green - manuscript
    June 2022 A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers We are in a unique moment of our history unlike any previous moment ever. Virtually all human economies are based on the destruction of the Earth, and we are now at a place in our history where we can foresee if we continue on as we are, our own extinction. As I write, the planet is in deep trouble, heat, fires, great storms, and record flooding, (...)
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  38. What is Distinctive About Human Thought? (An Inaugural Lecture Given at the University of Cambridge, December 2010).Tim Crane - manuscript
    Descartes famously argued that animals were mere machines, without thought or consciousness. Few would now share this view. But if other animals have conscious lives, what are they like, how do they differ from ours, and how would we ever know anything about them? This lecture will address this question by looking at the kinds of thoughts we might share with animals, and looking at philosophical and empirical arguments for how our thoughts might differ from theirs.
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  39. An Ecological Approach to Cognitive Science.John T. Sanders - 1996 - Electronic Journal of Analytic Philosophy 1996 (Spring).
    Cognitive science is ready for a major reconceptualization. This is not at all because efforts by its practitioners have failed, but rather because so much progress has been made. The need for reconceptualization arises from the fact that this progress has come at greater cost than necessary, largely because of more or less philosophical (at least metatheoretical) straightjackets still worn - whether wittingly or not - by those doing the work. These bonds are extremely hard to break. Even some of (...)
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  40. UNDERSTANDING HUMAN CONSCIOUSNESS AND MENTAL FUNCTIONS: A LIFE-SCIENTIFIC PERSPECTIVE OF BRAHMAJNAANA.Varanasi Ramabrahmam - 2011 - In In the Proceedings of 4th National Conference on Vedic Science with Theme of "Ancient Indian Life Science and Related Technologies" on 23rd, 24th, and 25th December 2011 Atbangalore Conducted by National Institute of Vedic Science Bang.
    A biophysical and biochemical perspective of Brahmajnaana will be advanced by viewing Upanishads and related books as “Texts of Science on human mind”. A biological and cognitive science insight of Atman and Maya, the results of breathing process; constituting and responsible for human consciousness and mental functions will be developed. The Advaita and Dvaita phases of human mind, its cognitive and functional states will be discussed. These mental activities will be modeled as brain-wave modulation and demodulation processes. The energy-forms and (...)
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  41.  67
    For the trickster, the theme is stronger than fear.Albert Efimov - 2024 - Економіка Та Суспільство 99 (3):8-20.
    This interview continues Albert Efimov’s series of discussions with scholars about the current state of artificial intelligence, its applications across various fields and tasks, and the ethical and social implications of its development. In the conversation regarding humanity’s place in the modern world, A.G. Asmolov discussed the importance of maintaining diversity within complex systems and managing complexity during their analysis. The dialogue clarified the role of the «contrarian,» the future anthropologist’s work, and how metaphor will drive scientific progress in the (...)
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  42. Humanity's Future: How Technology Will Change Us.Jay Friedenberg - 2014 - Humanity+ Press.
    This book is a collection of essays written on a variety of topics relevant to the future of humankind. The chapters are organized foundationally starting with how it is we can know and understand reality. This is followed by descriptions of future technologies and the new science that will drive them. Then we take a look at ourselves, how smart we are and how intelligent our machines may become. The final sections paint a larger picture, examining civilization with a (...)
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  43. Cybernetics for the 21st Century Vol.1 Epistemological Reconstruction.Yuk Hui (ed.) - 2024 - Hong Kong: Hanart Press.
    Cybernetics for the 21st Century Vol.1 is dedicated to the epistemological reconstruction of cybernetics, consisting of a series of historical and critical reflections on the subject – which according to Martin Heidegger marked the completion of Western metaphysics. In this anthology, historians, philosophers, sociologists and media studies scholars explore the history of cybernetics from Leibniz to artificial intelligence and machine learning, as well as the development of twentieth-century cybernetics in various geographical regions in the world, from the USA to the (...)
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  44. Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy.Dresp-Langley Birgitta - 2023 - Queios.
    The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. This position paper takes the stand that, in the light of all we currently know about brain evolution (...)
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  45. A MACRO-SHIFTED FUTURE: PREFERRED OR ACCIDENTALLY POSSIBLE IN THE CONTEXT OF ADVANCES IN ARTIFICIAL INTELLIGENCE SCIENCE AND TECHNOLOGY.Albert Efimov - 2023 - In Наука и феномен человека в эпоху цивилизационного Макросдвига. Moscow: pp. 748.
    This article is devoted to the topical aspects of the transformation of society, science, and man in the context of E. László’s work «Macroshift». The author offers his own attempt to consider the attributes of macroshift and then use these attributes to operationalize further analysis, highlighting three essential elements: the world has come to a situation of technological indistinguishability between the natural and the artificial, to machines that know everything about humans. Antiquity aspired to beauty and saw beauty in (...)
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  46. Diagrammatic Modelling of Causality and Causal Relations.Sabah Al-Fedaghi - manuscript
    It has been stated that the notion of cause and effect is one object of study that sciences and engineering revolve around. Lately, in software engineering, diagrammatic causal inference methods (e.g., Pearl’s model) have gained popularity (e.g., analyzing causes and effects of change in software requirement development). This paper concerns diagrammatical (graphic) models of causal relationships. Specifically, we experiment with using the conceptual language of thinging machines (TMs) as a tool in this context. This would benefit works on causal (...)
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  47. Ethical Implications of Alzheimer’s Disease Prediction in Asymptomatic Individuals Through Artificial Intelligence.Frank Ursin, Cristian Timmermann & Florian Steger - 2021 - Diagnostics 11 (3):440.
    Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward (...)
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  48. Information Theory is abused in neuroscience.Lance Nizami - 2019 - Cybernetics and Human Knowing 26 (4):47-97.
    In 1948, Claude Shannon introduced his version of a concept that was core to Norbert Wiener's cybernetics, namely, information theory. Shannon's formalisms include a physical framework, namely a general communication system having six unique elements. Under this framework, Shannon information theory offers two particularly useful statistics, channel capacity and information transmitted. Remarkably, hundreds of neuroscience laboratories subsequently reported such numbers. But how (and why) did neuroscientists adapt a communications-engineering framework? Surprisingly, the literature offers no clear answers. To therefore first answer (...)
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  49. Finding structure in a meditative state.Bas Rasmussen - manuscript
    I have been experimenting with meditation for a long time, but just recently I seem to have come across another being in there. It may just be me looking at me, but whatever it is, it is showing me some really interesting arrangements of colored balls. At first, I thought it was just random colors and shapes, but it became very ordered. It was like this being (me?) was trying to talk to me but couldn’t, so was showing me some (...)
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  50. 'Techno-Risk - The Perils of Learning and Sharing Everything' from a Criminal Information Sharing Perspective.John Sliter - manuscript
    The author has extensive law enforcement experience and the paper is intended to provoke thought on the use of technology as it pertains to information sharing between the police and the private sector. -/- As the world edges closer and closer to the convergence of man and machine, the human capacity to retrieve information is increasing by leaps and bounds. We are on the verge of knowing everything and anything there is to know, and literally in the blink of (...)
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