Results for 'Knowledge, safety, intuition, artificial intelligence, recognition, interpolation'

998 found
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  1. Seeking safety in knowledge.Jennifer Nagel - 2023 - Proceedings and Addresses of the American Philosophical Association 97:186-214.
    Knowledge demands more than accuracy: epistemologists are broadly agreed that those who know are non-accidentally right, satisfying some kind of safety condition. However, it is hard to formulate any adequate account of safety, and harder still to explain exactly why we care about it. This paper approaches the problem by looking at a concrete human cognitive capacity, face recognition, to see where epistemic safety shows up in it. Drawing on new models in artificial intelligence, and making a case that (...)
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  2. Artificial moral experts: asking for ethical advice to artificial intelligent assistants.Blanca Rodríguez-López & Jon Rueda - 2023 - AI and Ethics.
    In most domains of human life, we are willing to accept that there are experts with greater knowledge and competencies that distinguish them from non-experts or laypeople. Despite this fact, the very recognition of expertise curiously becomes more controversial in the case of “moral experts”. Do moral experts exist? And, if they indeed do, are there ethical reasons for us to follow their advice? Likewise, can emerging technological developments broaden our very concept of moral expertise? In this article, we begin (...)
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  3. 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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  4. We Asked ChatGPT About the Co-Authorship of Artificial Intelligence in Scientific Papers.Ayşe Balat & İlhan Bahşi - 2023 - European Journal of Therapeutics 29 (3):e16-e19.
    Dear Colleagues, -/- A few weeks ago, we published an editorial discussion on whether artificial intelligence applications should be authors of academic articles [1]. We were delighted to receive more than one interesting reply letter to this editorial in a short time [2, 3]. We hope that opinions on this subject will continue to be submitted to our journal. -/- In this editorial, we wanted to publish the answers we received when we asked ChatGPT, one of the artificial (...)
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  5. Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence.Antonio Lieto - 2021 - SRM ACM Student Chapters.
    Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense categorization and (...)
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  6. Artificial Intelligence Ethics and Safety: practical tools for creating "good" models.Nicholas Kluge Corrêa -
    The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...)
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  7. The Pharmacological Significance of Mechanical Intelligence and Artificial Stupidity.Adrian Mróz - 2019 - Kultura I Historia 36 (2):17-40.
    By drawing on the philosophy of Bernard Stiegler, the phenomena of mechanical (a.k.a. artificial, digital, or electronic) intelligence is explored in terms of its real significance as an ever-repeating threat of the reemergence of stupidity (as cowardice), which can be transformed into knowledge (pharmacological analysis of poisons and remedies) by practices of care, through the outlook of what researchers describe equivocally as “artificial stupidity”, which has been identified as a new direction in the future of computer science and (...)
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  8. Artificial Intelligence: Arguments for Catastrophic Risk.Adam Bales, William D'Alessandro & Cameron Domenico Kirk-Giannini - 2024 - Philosophy Compass 19 (2):e12964.
    Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, (...)
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  9. 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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  10. Artificial Intelligence and Neuroscience Research: Theologico-Philosophical Implications for the Christian Notion of the Human Person.Justin Nnaemeka Onyeukaziri - 2023 - Maritain Studies/Etudes Maritainiennes 39:85-103.
    This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences as (...)
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  11. Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?Alex John London - 2022 - Cell Reports Medicine 100622 (3):1-8.
    There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their (...)
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  12. Deontology and Safe Artificial Intelligence.William D'Alessandro - forthcoming - Philosophical Studies.
    The field of AI safety aims to prevent increasingly capable artificially intelligent systems from causing humans harm. Research on moral alignment is widely thought to offer a promising safety strategy: if we can equip AI systems with appropriate ethical rules, according to this line of thought, they'll be unlikely to disempower, destroy or otherwise seriously harm us. Deontological morality looks like a particularly attractive candidate for an alignment target, given its popularity, relative technical tractability and commitment to harm-avoidance principles. I (...)
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  13. Accountability in Artificial Intelligence: What It Is and How It Works.Claudio Novelli, Mariarosaria Taddeo & Luciano Floridi - 2023 - AI and Society 1:1-12.
    Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, (...)
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  14. Artificial Intelligence Implications for Academic Cheating: Expanding the Dimensions of Responsible Human-AI Collaboration with ChatGPT.Jo Ann Oravec - 2023 - Journal of Interactive Learning Research 34 (2).
    Cheating is a growing academic and ethical concern in higher education. This article examines the rise of artificial intelligence (AI) generative chatbots for use in education and provides a review of research literature and relevant scholarship concerning the cheating-related issues involved and their implications for pedagogy. The technological “arms race” that involves cheating-detection system developers versus technology savvy students is attracting increased attention to cheating. AI has added new dimensions to academic cheating challenges as students (as well as faculty (...)
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  15. Dubito Ergo Sum: Exploring AI Ethics.Viktor Dörfler & Giles Cuthbert - 2024 - Hicss 57: Hawaii International Conference on System Sciences, Honolulu, Hi.
    We paraphrase Descartes’ famous dictum in the area of AI ethics where the “I doubt and therefore I am” is suggested as a necessary aspect of morality. Therefore AI, which cannot doubt itself, cannot possess moral agency. Of course, this is not the end of the story. We explore various aspects of the human mind that substantially differ from AI, which includes the sensory grounding of our knowing, the act of understanding, and the significance of being able to doubt ourselves. (...)
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  16. What Can Artificial Intelligence Do for Scientific Realism?Petr Spelda & Vit Stritecky - 2020 - Axiomathes 31 (1):85-104.
    The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence (...)
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  17. 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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  18. The Use of Artificial Intelligence (AI) in Qualitative Research for Theory Development.Prokopis A. Christou - 2023 - The Qualitative Report 28 (9):2739-2755.
    Theory development is an important component of academic research since it can lead to the acquisition of new knowledge, the development of a field of study, and the formation of theoretical foundations to explain various phenomena. The contribution of qualitative researchers to theory development and advancement remains significant and highly valued, especially in an era of various epochal shifts and technological innovation in the form of Artificial Intelligence (AI). Even so, the academic community has not yet fully explored the (...)
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  19. Short-circuiting the definition of mathematical knowledge for an Artificial General Intelligence.Samuel Alexander - 2020 - Cifma.
    We propose that, for the purpose of studying theoretical properties of the knowledge of an agent with Artificial General Intelligence (that is, the knowledge of an AGI), a pragmatic way to define such an agent’s knowledge (restricted to the language of Epistemic Arithmetic, or EA) is as follows. We declare an AGI to know an EA-statement φ if and only if that AGI would include φ in the resulting enumeration if that AGI were commanded: “Enumerate all the EA-sentences which (...)
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  20. An Introduction to Artificial Psychology Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R.Farahani Hojjatollah - 2023 - Springer Cham. Edited by Hojjatollah Farahani, Marija Blagojević, Parviz Azadfallah, Peter Watson, Forough Esrafilian & Sara Saljoughi.
    Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps (...)
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  21. Minding the Future: Artificial Intelligence, Philosophical Visions and Science Fiction.Barry Francis Dainton, Will Slocombe & Attila Tanyi (eds.) - 2021 - Springer.
    Bringing together literary scholars, computer scientists, ethicists, philosophers of mind, and scholars from affiliated disciplines, this collection of essays offers important and timely insights into the pasts, presents, and, above all, possible futures of Artificial Intelligence. This book covers topics such as ethics and morality, identity and selfhood, and broader issues about AI, addressing questions about the individual, social, and existential impacts of such technologies. Through the works of science fiction authors such as Isaac Asimov, Stanislaw Lem, Ann Leckie, (...)
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  22. Persons or datapoints?: Ethics, artificial intelligence, and the participatory turn in mental health research.Joshua August Skorburg, Kieran O'Doherty & Phoebe Friesen - 2024 - American Psychologist 79 (1):137-149.
    This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. (...)
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  23. 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 thesis (...)
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  24. Modelling Argument Recognition and Reconstruction.Joel Katzav & Chris Reed - 2008 - Journal of Pragmatics 40:155-172..
    A growing body of recent work in informal logic investigates the process of argumentation. Among other things, this work focuses on the ways in which individuals attempt to understand written or verbalised arguments in light of the fact that these are often presented in forms that are incomplete and unmarked. One of its aims is to develop general procedures for natural language argument recognition and reconstruction. Our aim here is to draw on this growing body of knowledge in informal logic (...)
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  25. Thoughts on Artificial Intelligence and the Origin of Life Resulting from General Relativity, with Neo-Darwinist Reference to Human Evolution and Mathematical Reference to Cosmology.Rodney Bartlett - manuscript
    When this article was first planned, writing was going to be exclusively about two things - the origin of life and human evolution. But it turned out to be out of the question for the author to restrict himself to these biological and anthropological topics. A proper understanding of them required answering questions like “What is the nature of the universe – the home of life – and how did it originate?”, “How can time travel be removed from fantasy and (...)
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  26. Guest editor's introduction: artificial intelligence.Varol Akman - 2001 - Turkish Journal of Electrical Engineering and Computer Sciences 9 (1).
    Founded in 1993, ELEKTRIK: Turkish Journal of Electrical Engineering and Computer Sciences, has gradually become better known and is fast establishing itself as a research oriented publication outlet with high academic standards. In a modest attempt to advance this trend, this special issue of ELEKTRIK brings together five papers exemplifying the state of the art in artificial intelligence (AI). Written by experts, the papers are especially aimed at readers interested in gaining a better appraisal of the applications side of (...)
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  27. Guilty Artificial Minds: Folk Attributions of Mens Rea and Culpability to Artificially Intelligent Agents.Michael T. Stuart & Markus Kneer - 2021 - Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2).
    While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...)
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  28. Argument Diagramming in Logic, Artificial Intelligence, and Law.Chris Reed, Douglas Walton & Fabrizio Macagno - 2007 - The Knowledge Engineering Review 22 (1):87-109.
    In this paper, we present a survey of the development of the technique of argument diagramming covering not only the fields in which it originated - informal logic, argumentation theory, evidence law and legal reasoning – but also more recent work in applying and developing it in computer science and artificial intelligence. Beginning with a simple example of an everyday argument, we present an analysis of it visualised as an argument diagram constructed using a software tool. In the context (...)
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  29. Unmonitorability of Artificial Intelligence.Roman Yampolskiy - manuscript
    Artificially Intelligent (AI) systems have ushered in a transformative era across various domains, yet their inherent traits of unpredictability, unexplainability, and uncontrollability have given rise to concerns surrounding AI safety. This paper aims to demonstrate the infeasibility of accurately monitoring advanced AI systems to predict the emergence of certain capabilities prior to their manifestation. Through an analysis of the intricacies of AI systems, the boundaries of human comprehension, and the elusive nature of emergent behaviors, we argue for the impossibility of (...)
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  30. Ethics and Artificial Intelligence.Mark Ryan - 2021 - In Encyclopedia of Business and Professional Ethics. pp. 1-5.
    A subdiscipline has emerged around AI ethics, which is comprised of a wide array of individuals: computer scientists, ethicists, cognitive scientists, roboticists, legal professionals, economists, sociologists, gender, and race theorists. This has led to a very interesting branch of research, addressing issues surrounding the development and use of AI. This chapter will give a very brief snapshot of some of the most pertinent ethical concerns. Many of the issues in the Big Data Ethics chapter in this collection are often applicable (...)
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  31. The Rising Tide of Artificial Intelligence in Scientific Journals: A Profound Shift in Research Landscape.Ricardo Grillo - 2023 - European Journal of Therapeutics 29 (3):686-688.
    Dear Editors, -/- I found the content of your editorials to be highly intriguing [1,2]. Scientific journals are witnessing a growing prevalence of publications related to artificial intelligence (AI). Three letters to the editor were recently published in your journal [3-5]. The renowned journal Nature has dedicated approximately 25 publications solely to the subject of ChatGPT. Moreover, a quick search on Pubmed using the term "ChatGPT" yields around 900 articles, with the vast majority originating in 2023. These statistics underscore (...)
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  32.  76
    Integrating Multiple Intelligence and Artificial Intelligence in Language Learning: Enhancing Personalization and Engagement.Edgar Eslit - 2023 - Preprints.
    This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, objectives, research (...)
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  33. Accelerating Artificial Intelligence: Exploring the Implications of Xenoaccelerationism and Accelerationism for AI and Machine Learning.Kaiola liu - 2023 - Dissertation, University of Hawaii
    This article analyzes the potential impacts of Xenoaccelerationism and Accelerationism on the development of artificial intelligence (AI) and machine learning (ML). It examines how these speculative philosophies, which advocate technological acceleration and integration of diverse knowledge, may shape priorities and approaches in AI research and development. The risks and benefits of aligning AI progress with accelerationist values are discussed.
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  34. Acquisition of Autonomy in Biotechnology and Artificial Intelligence.Philippe Gagnon, Mathieu Guillermin, Olivier Georgeon, Juan R. Vidal & Béatrice de Montera - 2020 - In S. Hashimoto N. Callaos (ed.), Proceedings of the 11th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2020, Volume II. Winter Garden: International Institute for Informatics and Systemics. pp. 168-172.
    This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could (...)
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  35. AI or Your Lying Eyes: Some Shortcomings of Artificially Intelligent Deepfake Detectors.Keith Raymond Harris - 2024 - Philosophy and Technology 37 (7):1-19.
    Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, the success of such (...)
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  36. An Enactive Approach to Value Alignment in Artificial Intelligence: A Matter of Relevance.Michael Cannon - 2021 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2021. Springer Cham. pp. 119-135.
    The “Value Alignment Problem” is the challenge of how to align the values of artificial intelligence with human values, whatever they may be, such that AI does not pose a risk to the existence of humans. Existing approaches appear to conceive of the problem as "how do we ensure that AI solves the problem in the right way", in order to avoid the possibility of AI turning humans into paperclips in order to “make more paperclips” or eradicating the human (...)
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  37. Artificial Intelligence and Thomistic Angelology: a Rejoinder.Jude Chua Soo Meng - 2001 - Quodlibet 3.
    My paper analyses the analogy between Computers and the Thomistic separate substances, and argues that Aquinas' account of angels as cognitively intuitive and non-discursive makes the analogical gap between these impossible to bridge. From there, I point the direction away from computers as the way for us to move up the order of cognitive excellence. Instead, the gifts of the Holy Spirit are the way to go, since by them we participate in this intuitivity. I then lay out the ascetical (...)
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  38. 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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  39. Martin Heidegger’s Concept of Understanding (Verstehen): An Inquiry into Artificial Intelligence.Joshua D. F. Hooke - 2023 - Analecta Hermeneutica 15.
    My primary goal in this paper is to demonstrate the inadequacy of Hubert Dreyfus’ use of understanding (Verstehen) for Artificial Intelligence (AI). My complementary goal is to provide a principled account of Martin Heidegger’s concept of understanding (Verstehen). Dreyfus and other verificationists argue that understanding (Verstehen) is socially purposive action and skillful embodied coping. Understanding (Verstehen), conceived of in this way, purportedly challenges cognitive models of Artificial Intelligence (AI) that rely on formal rules, ‘rational’ decisionmaking, and the explicit (...)
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  40. 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 of (...)
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  41. Artificial general intelligence through visual pattern recognition: an analysis of the Phaeaco cognitive architecture.Safal Aryal - manuscript
    In the mid-1960s, Soviet computer scientist Mikhail Moiseevich Bongard created sets of visual puzzles where the objective was to spot an easily justifiable difference between two sides of a single image (for instance, white shapes vs black shapes, etc...). The idea was that these puzzles could be used to teach computers the general faculty of abstraction: perhaps by learning to spot the differences between these sorts of images, a computational agent could learn about inference in general. Considered a global expert (...)
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  42. The potential use of artificial intelligence in the therapy of borderline personality disorder.Judit Szalai - 2021 - Journal of Evaluation in Clinical Practice 27 (3):491-496.
    This paper explores the possibility of AI-based addendum therapy for borderline personality disorder, its potential advantages and limitations. Identity disturbance in this condition is strongly connected to self-narratives, which manifest excessive incoherence, causal gaps, dysfunctional beliefs, and diminished self-attributions of agency. Different types of therapy aim at boosting self-knowledge through self-narratives in BPD. The suggestion of this paper is that human-to-human therapy could be complemented by AI assistance holding out the promise of making patients' self-narratives more coherent through improving the (...)
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  43. Contesti in intelligenza artificiale: una fugace rassegna (Context in artificial intelligence: a fleeting overview).Varol Akman - 2002 - In Carlo Penco (ed.), La Svolta Contestuale. McGraw-Hill.
    The notion of context arises in assorted areas of artificial intelligence (AI), including knowledge representation, natural language processing, intelligent information retrieval, etc. Although the term ‘context’ is frequently employed in descriptions, explanations, and analyses of computer programs in these areas, its meaning is frequently left to the reader’s understanding. -/- My aim in this paper is to offer a swift review of context in AI. I will first identify the role of context in various fields of AI. I will (...)
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  44. 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 (...)
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  45. Do Chatbots Dream of Androids? Prospects for the Technological Development of Artificial Intelligence and Robotics.Albert R. Efimov - 2019 - Philosophical Sciences 62 (7):73-95.
    The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the current article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics, and also determines the main aspects of the impact of these technologies on society and economy, indicating (...)
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  46. Why Machines Will Never Rule the World: Artificial Intelligence without Fear by Jobst Landgrebe & Barry Smith (Book review). [REVIEW]Walid S. Saba - 2022 - Journal of Knowledge Structures and Systems 3 (4):38-41.
    Whether it was John Searle’s Chinese Room argument (Searle, 1980) or Roger Penrose’s argument of the non-computable nature of a mathematician’s insight – an argument that was based on Gödel’s Incompleteness theorem (Penrose, 1989), we have always had skeptics that questioned the possibility of realizing strong Artificial Intelligence (AI), or what has become known by Artificial General Intelligence (AGI). But this new book by Landgrebe and Smith (henceforth, L&S) is perhaps the strongest argument ever made against strong AI. (...)
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  47. Unexplainability and Incomprehensibility of Artificial Intelligence.Roman Yampolskiy - manuscript
    Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to understand how an intelligent system functions for safety and security reasons. In this paper, we describe two complementary impossibility results (Unexplainability and Incomprehensibility), essentially showing that advanced AIs would not be able to accurately explain some of their decisions and for the decisions they could explain people would (...)
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  48. ELEMENTS OF COGNITIVE SCIENCES AND ARTIFICIAL INTELLIGENCE IN GAYATRI MANTRA.Varanasi Ramabrahmam - 2006 - In Proceedings of National seminar on Bharatiya Heritage in Engineering and Technology, May 11-13, 2006, at Department of Metallurgy and Inorganic Chemistry, I.I.Sc., Bangalore, India. pp. 249-254.
    The syllables and series of sounds composing Gayatri Mantra, and the sense and meaning attached to them are analyzed using Upanishadic Wisdom, Advaitha Philosophy and Sabdabrahma Siddhanta. The physical structure of mind as revealed by this analysis is presented. An insight of various phases of mind, their rise and set, their significance and implications to cognitive sciences and natural language comprehension branch of artificial intelligence are discussed. The possible applications of such an insight in the fields of cognitive sciences, (...)
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    Challenges of AI for Promoting Sikhism in the 21st Century (Guest Editorial).Devinder Pal Singh - 2023 - The Sikh Review, Kolkata, WB, India 71 (09):6-8.
    Artificial Intelligence (AI) is a technology that enables machines or computer systems to perform tasks that usually require human intelligence. AI systems can understand and interpret information, make decisions, and solve problems based on patterns and data. They can also improve their performance over time by learning from their experiences. AI is used in various applications, such as enhancing knowledge and understanding, helping as voice assistants, aiding in image recognition, facilitating self-driving cars, and helping diagnose diseases. The appropriate usage (...)
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  50. AI as IA: The use and abuse of artificial intelligence (AI) for human enhancement through intellectual augmentation (IA).Alexandre Erler & Vincent C. Müller - 2023 - In Fabrice Jotterand & Marcello Ienca (eds.), The Routledge Handbook of the Ethics of Human Enhancement. Routledge. pp. 187-199.
    This paper offers an overview of the prospects and ethics of using AI to achieve human enhancement, and more broadly what we call intellectual augmentation (IA). After explaining the central notions of human enhancement, IA, and AI, we discuss the state of the art in terms of the main technologies for IA, with or without brain-computer interfaces. Given this picture, we discuss potential ethical problems, namely inadequate performance, safety, coercion and manipulation, privacy, cognitive liberty, authenticity, and fairness in more detail. (...)
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