Results for 'Intelligence'

931 found
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  1. Applying Intelligence to the Reflexes: Embodied Skills and Habits Between Dreyfus and Descartes.John Sutton, Doris McIlwain, Wayne Christensen & Andrew Geeves - 2011 - Journal of the British Society for Phenomenology 42 (1):78-103.
    ‘There is no place in the phenomenology of fully absorbed coping’, writes Hubert Dreyfus, ‘for mindfulness. In flow, as Sartre sees, there are only attractive and repulsive forces drawing appropriate activity out of an active body’1. Among the many ways in which history animates dynamical systems at a range of distinctive timescales, the phenomena of embodied human habit, skilful movement, and absorbed coping are among the most pervasive and mundane, and the most philosophically puzzling. In this essay we examine both (...)
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  2. Artificial Intelligence as a Means to Moral Enhancement.Michał Klincewicz - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):171-187.
    This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism (...)
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  3. Mandevillian Intelligence: From Individual Vice to Collective Virtue.Paul Smart - 2018 - In Joseph Adam Carter, Andy Clark, Jesper Kallestrup, Spyridon Orestis Palermos & Duncan Pritchard (eds.), Socially-Extended Epistemology. Oxford, UK: Oxford University Press. pp. 253–274.
    Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive shortcomings, limitations and biases play a positive functional role in yielding various forms of collective cognitive success. When this idea is transposed to the epistemological domain, mandevillian intelligence emerges as the idea that individual forms of intellectual vice may, on occasion, support the epistemic performance of some form of multi-agent ensemble, such as a socio-epistemic system, a collective doxastic agent, or an epistemic group agent. (...)
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  4. Artificial Intelligence and Patient-Centered Decision Making.Jens Christian Bjerring & Jacob Busch - forthcoming - Philosophy and Technology:1-23.
    Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: ​the details of their contents, calculations, (...)
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  5. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. (...)
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  6. Intelligence Via Ultrafilters: Structural Properties of Some Intelligence Comparators of Deterministic Legg-Hutter Agents.Samuel Alexander - 2019 - Journal of Artificial General Intelligence 10 (1):24-45.
    Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose (...)
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  7. Epistemological Intelligence.Steven James Bartlett - 2017 - Willamette University Faculty Research Website.
    The monograph’s twofold purpose is to recognize epistemological intelligence as a distinguishable variety of human intelligence, one that is especially important to philosophers, and to understand the challenges posed by the psychological profile of philosophers that can impede the development and cultivation of the skills associated with epistemological intelligence.
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  8. Beneficial Artificial Intelligence Coordination by Means of a Value Sensitive Design Approach.Steven Umbrello - 2019 - Big Data and Cognitive Computing 3 (1):5.
    This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used (...)
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  9. Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward Zalta (ed.), Stanford Encyclopedia of Philosophy. Palo Alto, Cal.: CSLI, Stanford University. pp. 1-70.
    Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and (...)
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  10. Shortcuts to Artificial Intelligence.Nello Cristianini - forthcoming - In Marcello Pelillo & Teresa Scantamburlo (eds.), Machines We Trust. MIT Press.
    The current paradigm of Artificial Intelligence emerged as the result of a series of cultural innovations, some technical and some social. Among them are apparently small design decisions, that led to a subtle reframing of the field’s original goals, and are by now accepted as standard. They correspond to technical shortcuts, aimed at bypassing problems that were otherwise too complicated or too expensive to solve, while still delivering a viable version of AI. Far from being a series of separate (...)
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  11. Classification of Global Catastrophic Risks Connected with Artificial Intelligence.Alexey Turchin & David Denkenberger - 2020 - AI and Society 35 (1):147-163.
    A classification of the global catastrophic risks of AI is presented, along with a comprehensive list of previously identified risks. This classification allows the identification of several new risks. We show that at each level of AI’s intelligence power, separate types of possible catastrophes dominate. Our classification demonstrates that the field of AI risks is diverse, and includes many scenarios beyond the commonly discussed cases of a paperclip maximizer or robot-caused unemployment. Global catastrophic failure could happen at various levels (...)
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  12. 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 (...)
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  13. On Controllability of Artificial Intelligence.Roman Yampolskiy - manuscript
    Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization. In order to reap the benefits and avoid pitfalls of such powerful technology it is important to be able to control it. However, possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established. In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI can’t be fully controlled. (...)
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  14. Integration of Intelligence Data Through Semantic Enhancement.David Salmen, Tatiana Malyuta, Alan Hansen, Shaun Cronen & Barry Smith - 2011 - In Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS). CEUR, Vol. 808.
    We describe a strategy for integration of data that is based on the idea of semantic enhancement. The strategy promises a number of benefits: it can be applied incrementally; it creates minimal barriers to the incorporation of new data into the semantically enhanced system; it preserves the existing data (including any existing data-semantics) in their original form (thus all provenance information is retained, and no heavy preprocessing is required); and it embraces the full spectrum of data sources, types, models, and (...)
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  15. The Nature of "Intelligence" and the Principles of Cognition.C. Spearman - 1924 - Journal of Philosophy 21 (11):294-301.
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  16. Ontology for the Intelligence Analyst.Barry Smith - 2012 - CrossTalk 14 (Nov/Dec):18-25.
    As available intelligence data and information expand in both quantity and variety, new techniques must be deployed for search and analytics. One technique involves the semantic enhancement of data through the creation of what are called ‘ontologies’ or ‘controlled vocabularies.’ When multiple different bodies of heterogeneous data are tagged by means of terms from common ontologies, then these data become linked together in ways which allow more effective retrieval and integration. We describe a simple case study to show how (...)
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  17. Invisible Influence: Artificial Intelligence and the Ethics of Adaptive Choice Architectures.Daniel Susser - 2019 - AIES: AAAI/ACM Conference on AI, Ethics, and Society 1.
    For several years, scholars have (for good reason) been largely preoccupied with worries about the use of artificial intelligence and machine learning (AI/ML) tools to make decisions about us. Only recently has significant attention turned to a potentially more alarming problem: the use of AI/ML to influence our decision-making. The contexts in which we make decisions—what behavioral economists call our choice architectures—are increasingly technologically-laden. Which is to say: algorithms increasingly determine, in a wide variety of contexts, both the sets (...)
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  18. Horizontal Integration of Warfighter Intelligence Data: A Shared Semantic Resource for the Intelligence Community.Barry Smith, Tatiana Malyuta, William S. Mandrick, Chia Fu, Kesny Parent & Milan Patel - 2012 - In Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), CEUR. pp. 1-8.
    We describe a strategy that is being used for the horizontal integration of warfighter intelligence data within the framework of the US Army’s Distributed Common Ground System Standard Cloud (DSC) initiative. The strategy rests on the development of a set of ontologies that are being incrementally applied to bring about what we call the ‘semantic enhancement’ of data models used within each intelligence discipline. We show how the strategy can help to overcome familiar tendencies to stovepiping of (...) data, and describe how it can be applied in an agile fashion to new data resources in ways that address immediate needs of intelligence analysts. (shrink)
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  19. First Steps Towards an Ethics of Robots and Artificial Intelligence.John Tasioulas - 2019 - Journal of Practical Ethics 7 (1):61-95.
    This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition (...)
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  20. The Rise of Artificial Intelligence and the Crisis of Moral Passivity.Berman Chan - 2020 - AI and Society 35 (4):991-993.
    Set aside fanciful doomsday speculations about AI. Even lower-level AIs, while otherwise friendly and providing us a universal basic income, would be able to do all our jobs. Also, we would over-rely upon AI assistants even in our personal lives. Thus, John Danaher argues that a human crisis of moral passivity would result However, I argue firstly that if AIs are posited to lack the potential to become unfriendly, they may not be intelligent enough to replace us in all our (...)
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  21. Fundamental Issues of Artificial Intelligence.Vincent C. Müller (ed.) - 2016 - Springer.
    [Müller, Vincent C. (ed.), (2016), Fundamental issues of artificial intelligence (Synthese Library, 377; Berlin: Springer). 570 pp.] -- This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. (...)
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  22. Incorporating Ethics Into Artificial Intelligence.Amitai Etzioni & Oren Etzioni - 2017 - The Journal of Ethics 21 (4):403-418.
    This article reviews the reasons scholars hold that driverless cars and many other AI equipped machines must be able to make ethical decisions, and the difficulties this approach faces. It then shows that cars have no moral agency, and that the term ‘autonomous’, commonly applied to these machines, is misleading, and leads to invalid conclusions about the ways these machines can be kept ethical. The article’s most important claim is that a significant part of the challenge posed by AI-equipped machines (...)
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  23. Risks of Artificial General Intelligence.Vincent C. Müller (ed.) - 2014 - Taylor & Francis (JETAI).
    Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages (...)
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  24.  47
    Meinongian Semantics and Artificial Intelligence.William J. Rapaport - 2013 - Humana Mente 6 (25):25-52.
    This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.
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  25. Experience, Memory and Intelligence.John T. Sanders - 1985 - The Monist 68 (4):507-521.
    What characterizes most technical or theoretical accounts of memory is their reliance upon an internal storage model. Psychologists and neurophysiologists have suggested neural traces (either dynamic or static) as the mechanism for this storage, and designers of artificial intelligence have relied upon the same general model, instantiated magnetically or electronically instead of neurally, to do the same job. Both psychology and artificial intelligence design have heretofore relied, without much question, upon the idea that memory is to be understood (...)
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  26.  12
    Artificial Intelligence as Solution in Facing the Age of Digital Disruption 4.0.David David - 2020 - JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) 1 (1):107-116.
    Artificial Intelligence is part of the Industrial Revolution 4.0 and already exists today. This shows that the future has come and everyone must prepare for the implementation of Artificial Intelligence to face the transformation of the digital era, especially the world of education. The community service workshop was attended by 66 participants, namely students, teachers, and structural officials of SMK Negeri 2 Singkawang. The workshop was held using demonstration methods, lectures, discussions and question and answer. This workshop provides (...)
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  27.  79
    Intelligence Cycle.Nicolae Sfetcu - manuscript
    The intelligence cycle is a set of processes used to provide useful information for decision-making. The cycle consists of several processes. The related counter-intelligence area is tasked with preventing information efforts from others. A basic model of the process of collecting and analyzing information is called the "intelligence cycle". This model can be applied, and, like all the basic models, it does not reflect the fullness of real-world operations. Through intelligence cycle activities, information is collected and (...)
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  28.  75
    The Intelligence Community.Nicolae Sfetcu - manuscript
    Intelligence services are currently focusing on the fight against terrorism, leaving relatively little resources to monitor other security threats. For this reason, they often ignore external information activities that do not pose immediate threats to their government's interests. Extremely few external services operate globally. Almost all other services focus on immediate neighbors or regions. These services usually depend on relationships with these global services for information on areas beyond their immediate neighborhoods, and often sell their regional expertise for what (...)
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  29. Future Progress in Artificial Intelligence: A Poll Among Experts.Vincent C. Müller & Nick Bostrom - 2014 - AI Matters 1 (1):9-11.
    [This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored (...)
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  30. Understanding Unconscious Intelligence and Intuition: "Blink" and Beyond.Lois Isenman - 2013 - Perspectives in Biology and Medicine 56 (1):148-166.
    The importance of unconscious cognition is seeping into popular consciousness. A number of recent books bridging the academic world and the reading public stress that at least a portion of decision-making depends not on conscious reasoning, but instead on cognition that occurs below awareness. However, these books provide a limited perspective on how the unconscious mind works and the potential power of intuition. This essay is an effort to expand the picture. It is structured around the book that has garnered (...)
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  31.  17
    Intelligence émotionnelle.Sfetcu Nicolae - manuscript
    La relation entre l'intelligence émotionnelle et la personnalité a été prise en compte dans plusieurs modèles d'intelligence émotionnelle, tels que les modèles mixtes de Bar-On et Goleman. Dans ces modèles, les composants de l'intelligence émotionnelle sont similaires à ceux de la théorie de la personnalité. Ce chevauchement est évident dans les comparaisons empiriques des constructions. Même dans le modèle de Mayer et Salovey, des corrélations empiriques significatives avec la personnalité peuvent être mises en évidence. Pour la plupart (...)
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  32.  84
    Intelligence Methodologies.Nicolae Sfetcu - manuscript
    Methodology, in intelligence, consists of the methods used to make decisions about threats, especially in the intelligence analysis discipline. The enormous amount of information collected by intelligence agencies often puts them in the inability to analyze them all. The US intelligence community collects over one billion daily information. The nature and characteristics of the information gathered as well as their credibility also have an impact on the intelligence analysis. Clark proposed a methodology for analyzing information (...)
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  33. What Kind of Kind is Intelligence?Serpico Davide - 2018 - Philosophical Psychology 31 (2):232-252.
    The model of human intelligence that is most widely adopted derives from psychometrics and behavioral genetics. This standard approach conceives intelligence as a general cognitive ability that is genetically highly heritable and describable using quantitative traits analysis. The paper analyzes intelligence within the debate on natural kinds and contends that the general intelligence conceptualization does not carve psychological nature at its joints. Moreover, I argue that this model assumes an essentialist perspective. As an alternative, I consider (...)
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  34. Science is Not Always “Self-Correcting” : Fact–Value Conflation and the Study of Intelligence.Nathan Cofnas - 2016 - Foundations of Science 21 (3):477-492.
    Some prominent scientists and philosophers have stated openly that moral and political considerations should influence whether we accept or promulgate scientific theories. This widespread view has significantly influenced the development, and public perception, of intelligence research. Theories related to group differences in intelligence are often rejected a priori on explicitly moral grounds. Thus the idea, frequently expressed by commentators on science, that science is “self-correcting”—that hypotheses are simply abandoned when they are undermined by empirical evidence—may not be correct (...)
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  35. 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 (...)
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  36.  82
    Epistemic Intelligence Communities. Counterintelligence.Nicolae Sfetcu - manuscript
    Epistemic communities are informal networks of knowledge-based experts who influence decision-makers in defining issues they face, identifying different solutions, and evaluating results. Epistemic communities have the greatest influence in conditions of political uncertainty and visibility, usually following a crisis or triggering event. Counterintelligence is primarily considered an analytical discipline, focusing on the study of intelligence services. The basis of all counterintelligence activities is the study of individual intelligence services, an analytical process to understand the behavior of foreign entities (...)
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  37.  85
    Intelligence Analysis.Nicolae Sfetcu - manuscript
    The analysts are in the field of "knowledge". Intelligence refers to knowledge and the types of problems addressed are knowledge problems. So, we need a concept of work based on knowledge. We need a basic understanding of what we know and how we know, what we do not know, and even what can be known and what is not known. The analysis should provide a useful basis for conceptualizing intelligence functions, of which the most important are "estimation" and (...)
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  38.  45
    Artificial Intelligence, Robots and the Ethics of the Future.Constantin Vica & Cristina Voinea - 2019 - Revue Roumaine de Philosophie 63 (2):223–234.
    The future rests under the sign of technology. Given the prevalence of technological neutrality and inevitabilism, most conceptualizations of the future tend to ignore moral problems. In this paper we argue that every choice about future technologies is a moral choice and even the most technology-dominated scenarios of the future are, in fact, moral provocations we have to imagine solutions to. We begin by explaining the intricate connection between morality and the future. After a short excursion into the history of (...)
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  39. IAO-Intel: An Ontology of Information Artifacts in the Intelligence Domain.Barry Smith, Tatiana Malyuta, Ron Rudnicki, William Mandrick, David Salmen, Peter Morosoff, Danielle K. Duff, James Schoening & Kesny Parent - 2013 - In Proceedings of the Eighth International Conference on Semantic Technologies for Intelligence, Defense, and Security (STIDS), CEUR, vol. 1097. pp. 33-40.
    We describe on-going work on IAO-Intel, an information artifact ontology developed as part of a suite of ontologies designed to support the needs of the US Army intelligence community within the framework of the Distributed Common Ground System (DCGS-A). IAO-Intel provides a controlled, structured vocabulary for the consistent formulation of metadata about documents, images, emails and other carriers of information. It will provide a resource for uniform explication of the terms used in multiple existing military dictionaries, thesauri and metadata (...)
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  40.  45
    What Should We Do About Sheep? The Role of Intelligence in Welfare Considerations.Heather Browning - 2019 - Animal Sentience 4 (25):23.
    Marino & Merskin (2019) demonstrate that sheep are more cognitively complex than typically thought. We should be cautious in interpreting the implications of these results for welfare considerations to avoid perpetuating mistaken beliefs about the moral value of intelligence as opposed to sentience. There are, however, still important ways in which this work can help improve sheeps’ lives.
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  41. Philosophy and Theory of Artificial Intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI (...)
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  42.  25
    Intelligence Ethics and Non-Coercive Interrogation.Michael Skerker - 2007 - Defense Intelligence Journal 16 (1):61-76.
    This paper will address the moral implications of non-coercive interrogations in intelligence contexts. U.S. Army and CIA interrogation manuals define non-coercive interrogation as interrogation which avoids the use of physical pressure, relying instead on oral gambits. These methods, including some that involve deceit and emotional manipulation, would be mostly familiar to viewers of TV police dramas. As I see it, there are two questions that need be answered relevant to this subject. First, under what circumstances, if any, may a (...)
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  43. The Pragmatic Turn in Explainable Artificial Intelligence (XAI).Andrés Páez - 2019 - Minds and Machines 29 (3):441-459.
    In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will (...)
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  44.  15
    Artificial Intelligence: Machine Translation Accuracy in Translating French-Indonesian Culinary Texts.Hasyim Muhammad - 2021 - International Journal of Advanced Computer Science and Applications 12 (3):186-191.
    The use of machine translation as artificial intelligence (AI) keeps increasing and the world’s most popular a translation tool is Google Translate (GT). This tool is not merely used for the benefits of learning and obtaining information from foreign languages through translation but has also been used as a medium of interaction and communication in hospitals, airports and shopping centres. This paper aims to explore machine translation accuracy in translating French-Indonesian culinary texts (recipes). The samples of culinary text were (...)
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  45. Philosophy of Artificial Intelligence: A Course Outline.William J. Rapaport - 1986 - Teaching Philosophy 9 (2):103-120.
    In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the (...)
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  46. Risks of Artificial Intelligence.Vincent C. Müller (ed.) - 2016 - CRC Press - Chapman & Hall.
    Papers from the conference on AI Risk (published in JETAI), supplemented by additional work. --- If the intelligence of artificial systems were to surpass that of humans, humanity would face significant risks. The time has come to consider these issues, and this consideration must include progress in artificial intelligence (AI) as much as insights from AI theory. -- Featuring contributions from leading experts and thinkers in artificial intelligence, Risks of Artificial Intelligence is the first volume of (...)
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  47. Consciousness, Intentionality, and Intelligence: Some Foundational Issues for Artificial Intelligence.Murat Aydede & Guven Guzeldere - 2000 - Journal of Experimental and Theoretical Artificial Intelligence 12 (3):263-277.
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  48. Editorial: Risks of General Artificial Intelligence.Vincent C. Müller - 2014 - Journal of Experimental and Theoretical Artificial Intelligence 26 (3):297-301.
    This is the editorial for a special volume of JETAI, featuring papers by Omohundro, Armstrong/Sotala/O’Heigeartaigh, T Goertzel, Brundage, Yampolskiy, B. Goertzel, Potapov/Rodinov, Kornai and Sandberg. - If the general intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity – so even if we estimate the probability of this event to be fairly low, it is necessary to think about it now. We need to estimate what progress we can expect, (...)
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  49. Turing on the Integration of Human and Machine Intelligence.S. G. Sterrett - 2014
    Abstract Philosophical discussion of Alan Turing’s writings on intelligence has mostly revolved around a single point made in a paper published in the journal Mind in 1950. This is unfortunate, for Turing’s reflections on machine (artificial) intelligence, human intelligence, and the relation between them were more extensive and sophisticated. They are seen to be extremely well-considered and sound in retrospect. Recently, IBM developed a question-answering computer (Watson) that could compete against humans on the game show Jeopardy! There (...)
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  50. One Decade of Universal Artificial Intelligence.Marcus Hutter - 2012 - In Pei Wang & Ben Goertzel (eds.), Theoretical Foundations of Artificial General Intelligence. Springer. pp. 67--88.
    The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning PhD (...)
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