Results for 'artificial inteligence'

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  1. Artificial Intelligence, Control and Legitimacy.Olga Gil - manuscript
    In this work, a general framework for the analysis of governance of artificial intelligence is presented. A dashboard developed for this analysis comes from the perspective of political theory. This dashboard allows eventual comparisons between democratic and non democratic regimes, useful for countries in the global south and western countries. The dashboard allows us to assess the key features that determine the governance model for artificial intelligence at the national level, for local governments and for other participant actors. (...)
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  2. Zastosowanie koncepcji kapitału społecznego w badaniach ludologicznych. Przykład branży gier komputerowych.Andrzej Klimczuk - 2010 - Homo Ludens 2:51--59.
    More and more people around the world are using computer (video) games. The development of the gaming industry means increasing of its complexity in all aspects. Not only is the content represented in games continuously differentiating, but we also see the increasing diversity among their creators, users, researchers and the public. This article aims to draw attention to the possibility of using the concept of social capital in ludologists’ research as well as in improving the quality of games and of (...)
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  3. Philosophizing with AI: happiness.Daniel Durante - manuscript
    A few years ago, I wrote a short text illustrating a problematic situation regarding the judgment of whether a particular fictional person, Bento, led a happy life or not. I frequently use this text in my introductory classes as a didactic resource to explain the nature of philosophy, its role in our understanding of the world, and to demonstrate its main challenge: the aporetic nature of philosophical questions. These questions do not yield unanimous or incontrovertible solutions; they always demand choice (...)
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  4. (1 other version)불일치, 결정 불가능, 임의, 계산 가능 및 불완전한 의미는 무엇입니까? '고델의 길 : 결정 불가능한 세상으로의 착취'에 대한 검토 (Godel's Way: Exploits into an undecidable world) by Gregory Chaitin, Francisco A Doria, Newton C.A. da Costa 160p (2012).Michael Richard Starks - 2020 - In 지구상의 지옥에 오신 것을 환영합니다 : 아기, 기후 변화, 비트 코인, 카르텔, 중국, 민주주의, 다양성, 역학, 평등, 해커, 인권, 이슬람, 자유주의, 번영, 웹, 혼돈, 기아, 질병, 폭력, 인공 지능, 전쟁. Las Vegas, NV USA: Reality Press. pp. 187-203.
    'Godel's Way'에서 세 명의 저명한 과학자들은 부정성, 불완전성, 임의성, 계산성 및 파라불일치와 같은 문제에 대해 논의합니다. 나는 완전히 다른 해결책을 가지고 두 가지 기본 문제가 있다는 비트 겐슈타인의 관점에서 이러한 문제에 접근. 과학적 또는 경험적 문제가 있다, 관찰 하 고 철학적 문제 언어를 어떻게 이해할 수 있는 (수학 및 논리에 특정 질문을 포함) 에 대 한 조사 해야 하는 세계에 대 한 사실,우리가 실제로 특정 컨텍스트에서 단어를 사용 하는 방법을 보고 하 여 결정 될 필요가. 우리가 어떤 언어 게임을 하고 (...)
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  5. Artificial consciousness and the consciousness-attention dissociation.Harry Haroutioun Haladjian & Carlos Montemayor - 2016 - Consciousness and Cognition 45:210-225.
    Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. (...)
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  6. Artificial Qualia, Intentional Systems and Machine Consciousness.Robert James M. Boyles - 2012 - In Proceedings of the Research@DLSU Congress 2012: Science and Technology Conference. pp. 110a–110c.
    In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, in (...)
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  7. Artificial moral agents are infeasible with foreseeable technologies.Patrick Chisan Hew - 2014 - Ethics and Information Technology 16 (3):197-206.
    For an artificial agent to be morally praiseworthy, its rules for behaviour and the mechanisms for supplying those rules must not be supplied entirely by external humans. Such systems are a substantial departure from current technologies and theory, and are a low prospect. With foreseeable technologies, an artificial agent will carry zero responsibility for its behavior and humans will retain full responsibility.
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  8. 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 or (...)
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  9. 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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  10. Artificial Neural Network for Forecasting Car Mileage per Gallon in the City.Mohsen Afana, Jomana Ahmed, Bayan Harb, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 124:51-59.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...)
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  11. 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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  12. Is Artificial General Intelligence Impossible?William J. Rapaport - 2024 - Cosmos+Taxis 12 (5+6):5-22.
    In their Why Machines Will Never Rule the World, Landgrebe and Smith (2023) argue that it is impossible for artificial general intelligence (AGI) to succeed, on the grounds that it is impossible to perfectly model or emulate the “complex” “human neurocognitive system”. However, they do not show that it is logically impossible; they only show that it is practically impossible using current mathematical techniques. Nor do they prove that there could not be any other kinds of theories than those (...)
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  13. Leveraging Artificial Intelligence for Strategic Business Decision-Making: Opportunities and Challenges.Mohammed Hazem M. Hamadaqa, Mohammad Alnajjar, Mohammed N. Ayyad, Mohammed A. Al-Nakhal, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):16-23.
    Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, (...)
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  14. Artificial Intelligence in Agriculture: Enhancing Productivity and Sustainability.Mohammed A. Hamed, Mohammed F. El-Habib, Raed Z. Sababa, Mones M. Al-Hanjor, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Engineering and Information Systems (IJEAIS) 8 (8):1-8.
    Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. (...)
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  15. Artificial Intelligence and the Body: Dreyfus, Bickhard, and the Future of AI.Daniel Susser - 2013 - In Vincent Müller (ed.), Philosophy and Theory of Artificial Intelligence. Springer. pp. 277-287.
    For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the (...)
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  16. Artificial Forms of Life.Sebastian Sunday Grève - 2023 - Philosophies 8 (5).
    The logical problem of artificial intelligence—the question of whether the notion sometimes referred to as ‘strong’ AI is self-contradictory—is, essentially, the question of whether an artificial form of life is possible. This question has an immediately paradoxical character, which can be made explicit if we recast it (in terms that would ordinarily seem to be implied by it) as the question of whether an unnatural form of nature is possible. The present paper seeks to explain this paradoxical kind (...)
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  17. Guilty Artificial Minds: Folk Attributions of Mens Rea and Culpability to Artificially Intelligent Agents.Michael T. Stuart & Markus Https://Orcidorg 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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  18. The Artificial Sublime.Regina Rini - manuscript
    Generative AI systems like ChatGPT and Midjourney can produce prose or images. But can they produce art? I argue that this question, though natural and intriguing, is the wrong one to ask. A better question is this: can generative AI yield distinct or novel forms of aesthetic value? And I argue that the answer is yes. Generative AI can be used to put us in contact with the artificial sublime – a type of aesthetic value that Kant famously argues (...)
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  19. Artificial Gametes and Human Reproduction in the 21st Century: An Ethical Analysis.A. Villalba - 2024 - Reproductive Sciences.
    Artificial gametes, derived from stem cells, have the potential to enable in vitro fertilization of embryos. Currently, artificial gametes are only being generated in laboratory animals; however, considerable efforts are underway to develop artificial gametes using human cell sources. These artificial gametes are being proposed as a means to address infertility through assisted reproductive technologies. Nonetheless, the availability of artificial gametes obtained from adult organisms can potentially expand the possibilities of reproduction. Various groups, such as (...)
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  20. Understanding Artificial Agency.Leonard Dung - forthcoming - Philosophical Quarterly.
    Which artificial intelligence (AI) systems are agents? To answer this question, I propose a multidimensional account of agency. According to this account, a system's agency profile is jointly determined by its level of goal-directedness and autonomy as well as is abilities for directly impacting the surrounding world, long-term planning and acting for reasons. Rooted in extant theories of agency, this account enables fine-grained, nuanced comparative characterizations of artificial agency. I show that this account has multiple important virtues and (...)
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  21. 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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  22. On the morality of artificial agents.Luciano Floridi & J. W. Sanders - 2004 - Minds and Machines 14 (3):349-379.
    Artificial agents (AAs), particularly but not only those in Cyberspace, extend the class of entities that can be involved in moral situations. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil). In this paper, we clarify the concept of agent and go on to separate the concerns of morality and responsibility of agents (...)
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  23. (1 other version)Artificial evil and the foundation of computer ethics.L. Floridi & J. Sanders - 2000 - Etica E Politica 2 (2).
    Moral reasoning traditionally distinguishes two types of evil: moral and natural. The standard view is that ME is the product of human agency and so includes phenomena such as war, torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE. Recently, as a result of developments in autonomous agents in cyberspace, (...)
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  24. Affective Artificial Agents as sui generis Affective Artifacts.Marco Facchin & Giacomo Zanotti - 2024 - Topoi 43 (3).
    AI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and (...)
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  25. May Artificial Intelligence take health and sustainability on a honeymoon? Towards green technologies for multidimensional health and environmental justice.Cristian Moyano-Fernández, Jon Rueda, Janet Delgado & Txetxu Ausín - 2024 - Global Bioethics 35 (1).
    The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green honeymoon (...)
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  26. 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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  27. Developing Artificial Human-Like Arithmetical Intelligence (and Why).Markus Pantsar - 2023 - Minds and Machines 33 (3):379-396.
    Why would we want to develop artificial human-like arithmetical intelligence, when computers already outperform humans in arithmetical calculations? Aside from arithmetic consisting of much more than mere calculations, one suggested reason is that AI research can help us explain the development of human arithmetical cognition. Here I argue that this question needs to be studied already in the context of basic, non-symbolic, numerical cognition. Analyzing recent machine learning research on artificial neural networks, I show how AI studies could (...)
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  28. Artificial Intelligence, Creativity, and the Precarity of Human Connection.Lindsay Brainard - forthcoming - Oxford Intersections: Ai in Society.
    There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. My central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they must (...)
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  29. 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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  30. Sustainability of Artificial Intelligence: Reconciling human rights with legal rights of robots.Ammar Younas & Rehan Younas - forthcoming - In Zhyldyzbek Zhakshylykov & Aizhan Baibolot (eds.), Quality Time 18. International Alatoo University Kyrgyzstan. pp. 25-28.
    With the advancement of artificial intelligence and humanoid robotics and an ongoing debate between human rights and rule of law, moral philosophers, legal and political scientists are facing difficulties to answer the questions like, “Do humanoid robots have same rights as of humans and if these rights are superior to human rights or not and why?” This paper argues that the sustainability of human rights will be under question because, in near future the scientists (considerably the most rational people) (...)
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  31. Artificial Intelligence and Legal Disruption: A New Model for Analysis.John Danaher, Hin-Yan Liu, Matthijs Maas, Luisa Scarcella, Michaela Lexer & Leonard Van Rompaey - forthcoming - Law, Innovation and Technology.
    Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (...)
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  32. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions.Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith & Simone Stumpf - 2024 - Information Fusion 106 (June 2024).
    As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from (...)
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  33. Artificial Wombs, Birth, and "Birth": A Response to Romanis.Nicholas Colgrove - 2019 - Journal of Medical Ethics:medethics-2019-105845.
    Recently, I argued that human subjects in artificial wombs (AWs) “share the same moral status as newborns” and so, deserve the same treatment and protections as newborns. This thesis rests on two claims: (A) “Subjects of partial ectogenesis—those that develop in utero for at time before being transferred to AWs—are newborns,” and (B) “Subjects of complete ectogenesis—those who develop in AWs entirely—share the same moral status as newborns.” In response, Elizabeth Chloe Romanis argued that the subject in an AW (...)
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  34. 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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  35. Artificial Intelligence Systems, Responsibility and Agential Self-Awareness.Lydia Farina - 2022 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2021. Berlin: Springer. pp. 15-25.
    This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing on a (...)
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  36. Artificial intelligence: opportunities and implications for the future of decision making.U. K. Government & Office for Science - 2016
    Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these (...)
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  37. Artificial Speech and Its Authors.Philip J. Nickel - 2013 - Minds and Machines 23 (4):489-502.
    Some of the systems used in natural language generation (NLG), a branch of applied computational linguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams’ account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence embedded in (...)
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  38. Artificial Neural Network for Predicting Car Performance Using JNN.Awni Ahmed Al-Mobayed, Youssef Mahmoud Al-Madhoun, Mohammed Nasser Al-Shuwaikh & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (9):139-145.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...)
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  39. Why We Should Create Artificial Offspring: Meaning and the Collective Afterlife.John Danaher - 2018 - Science and Engineering Ethics 24 (4):1097-1118.
    This article argues that the creation of artificial offspring could make our lives more meaningful. By ‘artificial offspring’ I mean beings that we construct, with a mix of human and non-human-like qualities. Robotic artificial intelligences are paradigmatic examples of the form. There are two reasons for thinking that the creation of such beings could make our lives more meaningful and valuable. The first is that the existence of a collective afterlife—i.e. a set of human-like lives that continue (...)
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  40. Artificial Evil and the Foundation of Computer Ethics.Luciano Floridi & J. W. Sanders - 2001 - Springer Netherlands. Edited by Luciano Floridi & J. W. Sanders.
    Moral reasoning traditionally distinguishes two types of evil:moral (ME) and natural (NE). The standard view is that ME is the product of human agency and so includes phenomena such as war,torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE. Recently, as a result of developments in autonomous agents in cyberspace, (...)
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  41. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation (...)
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  42. Selección artificial, selección sexual, selección natural.Santiago Ginnobili - 2011 - Metatheoria – Revista de Filosofía E Historia de la Ciencia 2 (1):61-78.
    En On the Origin of Species Darwin distingue explícitamente entre tres tipos de selección: la selección natural, la artificial y la sexual. En este trabajo, a partir de un estudio más sistemático que historiográfico, se intenta encontrar la relación entre estos tres tipos de selección en la obra de Darwin. Si bien la distinción entre estos distintos mecanismos es de suma importancia en la obra de Darwin, la tesis de este trabajo es que tanto la selección artificial como (...)
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  43. Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained (...)
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  44. Artificial Knowing Otherwise.Os Keyes & Kathleen Creel - 2022 - Feminist Philosophy Quarterly 8 (3).
    While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new (...)
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  45. Artificial reproduction, the 'welfare principle', and the common good.David Oderberg & J. A. Laing - unknown
    This article challenges the view most recently expounded by Emily Jackson that ‘decisional privacy’ ought to be respected in the realm of artificial reproduction (AR). On this view, it is considered an unjust infringement of individual liberty for the state to interfere with individual or group freedom artificially to produce a child. It is our contention that a proper evaluation of AR and of the relevance of welfare will be sensitive not only to the rights of ‘commissioning parties’ to (...)
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  46. Artificial in its own right.Keith Elkin - manuscript
    Artificial Cells, , Artificial Ecologies, Artificial Intelligence, Bio-Inspired Hardware Systems, Computational Autopoiesis, Computational Biology, Computational Embryology, Computational Evolution, Morphogenesis, Cyborgization, Digital Evolution, Evolvable Hardware, Cyborgs, Mathematical Biology, Nanotechnology, Posthuman, Transhuman.
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  47. (1 other version)Artificial intelligence crime: an interdisciplinary analysis of foreseeable threats and solutions.Thomas C. King, Nikita Aggarwal, Mariarosaria Taddeo & Luciano Floridi - 2019 - 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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  48. 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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  49. The Total Artificial Heart and the Dilemma of Deactivation.Ben Bronner - 2016 - Kennedy Institute of Ethics Journal 26 (4):347-367.
    It is widely believed to be permissible for a physician to discontinue any treatment upon the request of a competent patient. Many also believe it is never permissible for a physician to intentionally kill a patient. I argue that the prospect of deactivating a patient’s artificial heart presents us with a dilemma: either the first belief just mentioned is false or the second one is. Whichever horn of the dilemma we choose has significant implications for contemporary medical ethics.
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  50. (1 other version)Artificial virtuous agents: from theory to machine implementation.Jakob Stenseke - 2021 - AI and Society:1-20.
    Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, (...)
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