Results for 'intelligence'

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  1. An Intelligent Tutoring System for Cloud Computing.Hasan Abdulla Abu Hasanein & Samy S. Abu Naser - 2017 - International Journal of Academic Research and Development 2 (1):76-80.
    Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, (...)
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  2. Mathematics Intelligent Tutoring System.Nour N. AbuEloun & Samy S. Abu Naser - 2017 - International Journal of Advanced Scientific Research 2 (1):11-16.
    In these days, there is an increasing technological development in intelligent tutoring systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that help students understand the basics of math and that helps a lot of students of all ages to understand the topic because it's important for students of adding and subtracting. Through which the student will be able to study the course and solve related problems. An evaluation (...)
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  3. Artificial Intelligence: Its Scope and Limits.James H. Fetzer - 1990 - Kluwer Academic Publishers.
    1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..
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  4. Intelligence Without Representation.Rodney A. Brooks - 1991 - Artificial Intelligence 47 (1--3):139-159.
    Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and (...)
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  5. Unraveling Trie Enigma of Human Intelligence: Evolutionary Psychology and the Multimodular Mind.Of Intelligence - 2002 - In Robert J. Sternberg & J. Kaufman (eds.), The Evolution of Intelligence. Lawrence Erlbaum. pp. 145.
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  6. Artificial Intelligence: The Very Idea.John Haugeland - 1985 - Cambridge: MIT Press.
    The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...
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  7. Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans.Richard W. Byrne & Andrew Whiten (eds.) - 1988 - Oxford University Press.
    This book presents an alternative to conventional ideas about the evolution of the human intellect.
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  8. Artificial Intelligence and the ‘Good Society’: The US, EU, and UK Approach.Corinne Cath, Sandra Wachter, Brent Mittelstadt, Mariarosaria Taddeo & Luciano Floridi - 2018 - Science and Engineering Ethics 24 (2):505-528.
    In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a (...)
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  9.  60
    Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.Sebastian Laacke, Regina Mueller, Georg Schomerus & Sabine Salloch - 2021 - American Journal of Bioethics 21 (7):4-20.
    The development of artificial intelligence in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders...
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  10. Intelligence Without Representation – Merleau-Ponty's Critique of Mental Representation the Relevance of Phenomenology to Scientific Explanation.Hubert L. Dreyfus - 2002 - Phenomenology and the Cognitive Sciences 1 (4):367-383.
    Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are stored, not as representations in the mind, (...)
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  11.  91
    Practical Intelligence and the Virtues.Daniel C. Russell - 2009 - Oxford University Press.
    This book develops an Aristotelian account of the virtue of practical intelligence or "phronesis"--an excellence of deliberating and making choices--which ...
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  12. Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability.Mark Coeckelbergh - 2020 - Science and Engineering Ethics 26 (4):2051-2068.
    This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which (...)
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  13. The Intelligent Use of Space.David Kirsh - 1995 - Artificial Intelligence 73 (1--2):31-68.
    The objective of this essay is to provide the beginning of a principled classification of some of the ways space is intelligently used. Studies of planning have typically focused on the temporal ordering of action, leaving as unaddressed questions of where to lay down instruments, ingredients, work-in-progress, and the like. But, in having a body, we are spatially located creatures: we must always be facing some direction, have only certain objects in view, be within reach of certain others. How we (...)
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  14. An Intelligent Tutoring System for Teaching Grammar English Tenses.Mohammed I. Alhabbash, Ali O. Mahdi & Samy S. Abu Naser - 2016 - European Academic Research 4 (9):1-15.
    The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design (...)
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  15. Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
    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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  16. Artificial Intelligence—A Personal View.David Marr - 1977 - Artificial Intelligence 9 (September):37-48.
  17. Adaptive Intelligent Tutoring System for Learning Computer Theory.Mohammed A. Al-Nakhal & Samy S. Abu Naser - 2017 - EUROPEAN ACADEMIC RESEARCH 4 (10).
    In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to (...)
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  18. Intelligence Vs. Wisdom: The Love of Money, Machiavellianism, and Unethical Behavior Across College Major and Gender.Thomas Li-Ping Tang & Yuh-Jia Chen - 2008 - Journal of Business Ethics 82 (1):1-26.
    This research investigates the efficacy of business ethics intervention, tests a theoretical model that the love of money is directly or indirectly related to propensity to engage in unethical behavior (PUB), and treats college major (business vs. psychology) and gender (male vs. female) as moderators in multi-group analyses. Results suggested that business students who received business ethics intervention significantly changed their conceptions of unethical behavior and reduced their propensity to engage in theft; while psychology students without intervention had no such (...)
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  19. An Intelligent Tutoring System for Teaching the 7 Characteristics for Living Things.Mohammed A. Hamed & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1):31-35.
    Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them understand this subject easily (...)
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  20. Artificial Intelligence and Scientific Method.Donald Gillies - 1996 - Oxford and New York: Oxford University Press.
    Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gdel, Popper, Penrose, and Lucas, to address the hotly-contested question of whether computers (...)
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  21. Animal Intelligence.George John Romanes - 1882
  22. Intelligence Without Representation – Merleau-Ponty’s Critique of Mental Representation.Hubert L. Dreyfus - 2002 - Phenomenology and the Cognitive Sciences 1 (4):367-83.
    Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in the mind, (...)
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  23.  69
    Artificial Intelligence: A Philosophical Introduction.Jack Copeland - 1993 - Wiley-Blackwell.
    Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. (...)
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  24. Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.Thomas C. King, Nikita Aggarwal, Mariarosaria Taddeo & Luciano Floridi - 2020 - Science and Engineering Ethics 26 (1):89-120.
    Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...)
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  25.  54
    Mandevillian Intelligence.Paul Smart - 2018 - Synthese 195 (9):4169-4200.
    Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch (...)
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  26. 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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  27. An Intelligent Tutoring System for Learning Introduction to Computer Science.Ahmad Marouf, Mohammed K. Abu Yousef, Mohammed N. Mukhaimer & Samy S. Abu-Naser - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (2):1-8.
    The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in computer science (...)
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  28.  67
    Artificial intelligence, transparency, and public decision-making.Karl de Fine Licht & Jenny de Fine Licht - 2020 - AI and Society 35 (4):917-926.
    The increasing use of Artificial Intelligence for making decisions in public affairs has sparked a lively debate on the benefits and potential harms of self-learning technologies, ranging from the hopes of fully informed and objectively taken decisions to fear for the destruction of mankind. To prevent the negative outcomes and to achieve accountable systems, many have argued that we need to open up the “black box” of AI decision-making and make it more transparent. Whereas this debate has primarily focused (...)
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  29. Universal Intelligence: A Definition of Machine Intelligence.Shane Legg & Marcus Hutter - 2007 - Minds and Machines 17 (4):391-444.
    A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of (...) for arbitrary machines. We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines. (shrink)
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  30.  31
    The Intelligent Reflex.John W. Krakauer - 2019 - Philosophical Psychology 32 (5):822-830.
    ABSTRACTThe seeming distinction between motor and cognitive skills has hinged on the fact that the former are automatic and non-propositional, whereas the latter are slow and deliberative. Here, the physiological and behavioral phenomenon of long-latency stretch reflexes is used to show that “knowing-that” can be incorporated into “knowing-how,” either immediately or through learning. The experimental demonstration that slow computations can, with practice, be cached for fast retrieval, without the need for re-computation, dissolves the intellectualist/anti-intellectualist distinction: All complex human tasks, at (...)
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  31.  26
    Artificial Intelligences as Extended Minds. Why Not?Gianfranco Pellegrino & Mirko Daniel Garasic - 2020 - Rivista Internazionale di Filosofia e Psicologia 11 (2):150-168.
    : Artificial intelligences and robots increasingly mimic human mental powers and intelligent behaviour. However, many authors claim that ascribing human mental powers to them is both conceptually mistaken and morally dangerous. This article defends the view that artificial intelligences can have human-like mental powers, by claiming that both human and artificial minds can be seen as extended minds – along the lines of Chalmers and Clark’s view of mind and cognition. The main idea of this article is that the Extended (...)
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  32. Artificial Intelligence as a Socratic Assistant for Moral Enhancement.Francisco Lara & Jan Deckers - 2020 - Neuroethics 13 (3):275-287.
    The moral enhancement of human beings is a constant theme in the history of humanity. Today, faced with the threats of a new, globalised world, concern over this matter is more pressing. For this reason, the use of biotechnology to make human beings more moral has been considered. However, this approach is dangerous and very controversial. The purpose of this article is to argue that the use of another new technology, AI, would be preferable to achieve this goal. Whilst several (...)
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  33. Artificial Intelligence, Values, and Alignment.Iason Gabriel - 2020 - Minds and Machines 30 (3):411-437.
    This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...)
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  34.  82
    Artificial Intelligence Meets Natural Stupidity.Drew McDermott - 1981 - In J. Haugel (ed.), Mind Design. MIT Press. pp. 5-18.
  35. 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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  36. An Intelligent Tutoring System for Teaching Advanced Topics in Information Security.Ali O. Mahdi, Mohammed I. Alhabbash & Samy S. Abu Naser - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (12):1-9.
    Recently there is an increasing technological development in intelligent tutoring systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching information security. This intelligent tutoring systems target the students enrolled in Advanced Topics in Information Security in the faculty of Engineering and Information Technology at Al-Azhar University in Gaza. Through which the student will be able to study the course and solve related problems. An evaluation of the intelligent tutoring systems (...)
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  37. Artificial Intelligence and Black‐Box Medical Decisions: Accuracy Versus Explainability.Alex John London - 2019 - Hastings Center Report 49 (1):15-21.
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  38. Artificial Intelligence and Robot Responsibilities: Innovating Beyond Rights.Hutan Ashrafian - 2015 - Science and Engineering Ethics 21 (2):317-326.
    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals (...)
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  39. Artificial Intelligence, Deepfakes and a Future of Ectypes.Luciano Floridi - 2018 - Philosophy and Technology 31 (3):317-321.
    AI, especially in the case of Deepfakes, has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. And yet digital technologies, in the form of databases and other detection tools also make it easier to spot forgeries and to establish the authenticity of a work. Using the notion of ectypes, this paper discusses current conceptions of authenticity and reproduction and examines how, in the future, these might be adapted for use in (...)
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  40. Artificial Intelligence and its Natural Limits.Karl D. Stephan & Gyula Klima - 2021 - AI and Society (1):9-18.
    An argument with roots in ancient Greek philosophy claims that only humans are capable of a certain class of thought termed conceptual, as opposed to perceptual thought, which is common to humans, the higher animals, and some machines. We outline the most detailed modern version of this argument due to Mortimer Adler, who in the 1960s argued for the uniqueness of the human power of conceptual thought. He also admitted that if conceptual thought were ever manifested by machines, such an (...)
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  41. Intelligent Action Guidance and the Use of Mixed Representational Formats.Joshua Shepherd - 2018 - Synthese 198 (Suppl 17):4143-4162.
    My topic is the intelligent guidance of action. In this paper I offer an empirically grounded case for four ideas: that [a] cognitive processes of practical reasoning play a key role in the intelligent guidance of action, [b] these processes could not do so without significant enabling work done by both perception and the motor system, [c] the work done by perceptual and motor systems can be characterized as the generation of information specialized for action guidance, which in turn suggests (...)
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  42. Artificial Intelligence: A Philosophical Introduction.B. Jack Copeland - 1993 - Cambridge: Blackwell.
    Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John (...)
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  43. Ambient Intelligence and Persuasive Technology: The Blurring Boundaries Between Human and Technology. [REVIEW]Peter-Paul Verbeek - 2009 - NanoEthics 3 (3):231-242.
    The currently developing fields of Ambient Intelligence and Persuasive Technology bring about a convergence of information technology and cognitive science. Smart environments that are able to respond intelligently to what we do and that even aim to influence our behaviour challenge the basic frameworks we commonly use for understanding the relations and role divisions between human beings and technological artifacts. After discussing the promises and threats of these technologies, this article develops alternative conceptions of agency, freedom, and responsibility that (...)
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  44. An Intelligent Tutoring System for Health Problems Related To Addiction of Video Game Playing.Mohran H. Al-Bayed & Samy S. Abu Naser - 2017 - International Journal of Advanced Scientific Research 2 (1):4-10.
    Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...)
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  45.  46
    Artificial Intelligence Ethics Guidelines for Developers and Users: Clarifying Their Content and Normative Implications.Mark Ryan & Bernd Carsten Stahl - 2021 - Journal of Information, Communication and Ethics in Society 19 (1):61-86.
    Purpose The purpose of this paper is clearly illustrate this convergence and the prescriptive recommendations that such documents entail. There is a significant amount of research into the ethical consequences of artificial intelligence. This is reflected by many outputs across academia, policy and the media. Many of these outputs aim to provide guidance to particular stakeholder groups. It has recently been shown that there is a large degree of convergence in terms of the principles upon which these guidance documents (...)
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  46. Epistemological Intelligence.Steven James Bartlett - 2017 - Willamette University Faculty Research Website.
    2022 UPDATE: The approach of this monograph has been updated and developed further in Appendix II, "Epistemological Intelligence," of the author’s 2021 book _Critique of Impure Reason: Horizons of Possibility and Meaning_. The book is available both in a printed edition (under ISBN 978-0-578-88646-6 from Barnes & Noble, Amazon, and other booksellers) and an Open Access eBook edition (available through Philpapers under the book’s title and other philosophy online archives). ●●●●● -/- The monograph’s twofold purpose is to recognize epistemological (...)
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  47.  69
    Artificial intelligence and the value of transparency.Joel Walmsley - 2021 - AI and Society 36 (2):585-595.
    Some recent developments in Artificial Intelligence—especially the use of machine learning systems, trained on big data sets and deployed in socially significant and ethically weighty contexts—have led to a number of calls for “transparency”. This paper explores the epistemological and ethical dimensions of that concept, as well as surveying and taxonomising the variety of ways in which it has been invoked in recent discussions. Whilst “outward” forms of transparency may be straightforwardly achieved, what I call “functional” transparency about the (...)
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  48. Monetary Intelligence and Behavioral Economics: The Enron Effect—Love of Money, Corporate Ethical Values, Corruption Perceptions Index , and Dishonesty Across 31 Geopolitical Entities.Modupe Adewuyi, Bolanle Adetoun, Ningyu Tang, Jingqiu Chen, Anna Manganelli, Luigina Canova, Martina Trontelj, Caroline Urbain, Theresa Tang, Allen Stembridge, Petar Skobic, Elisaveta Sardžoska, Marko Polic, Horia Pitariu, Ruja Pholsward, Francisco Pereira, Mehmet Özbek, AAhad Osman-Gani, Johnsto Osagie, Anthony Nnedum, Richard Mpoyi, Alice Moreira, Eva Malovics, Jian Liang, Kilsun Kim, Ali Kazem, Chin-Kang Jen, Abdul Ibrahim, Consuelo Garcia de la Torre, Linzhi Du, Rosario Correia, Bor-Shiuan Cheng, Mark Borg, Abdulgawi Al-Zubaidi, Michael Allen, Adebowale Akande, Peter Vlerick, Roberto Luna-Arocas, Brigitte Charles-Pauvers, Randy Chiu, Ilya Garber, Fernando Arias-Galicia, Thompson Teo, Vivien Lim, Mahfooz Ansari, Toto Sutarso & Thomas Tang - 2018 - Journal of Business Ethics 148 (4):919-937.
    Monetary intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the dark side of monetary Intelligence and behavioral economics—dishonesty. Dishonesty, a risky prospect, involves cost–benefit analysis of self-interest. We frame good or bad barrels in the environmental context as a proxy of high or low probability of getting caught for dishonesty, respectively. We theorize: The magnitude and (...)
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  49.  13
    Intelligence Without Representation: The Relevance of Phenomenology to Scientific Explanation.Hubert L. Dreyfus - 2002 - Phenomenology and the Cognitive Sciences 1 (4):367-383.
    Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in the mind, (...)
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    Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence.Carlos Zednik - 2021 - Philosophy and Technology 34 (2):265-288.
    Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. Explainable Artificial Intelligence aims to develop analytic techniques that render opaque computing systems transparent, but lacks a normative framework with which to evaluate these techniques’ explanatory successes. The aim of the present discussion is to develop such a framework, paying particular attention to different stakeholders’ distinct explanatory requirements. Building on an analysis of “opacity” (...)
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