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  1. An Essay on Artifical Dispositions and Dispositional Compatibilism.Atilla Akalın - 2024 - Felsefe Dünyasi 79:165-187..
    The rapid pace of technological advancements offers an essential field of research for a deeper understanding of man’s relationship with artifacts of her design. These artifacts designed by humans can have various mental and physical effects on their users. The human interaction with the artifact is not passive; on the contrary, it exhibits a potential that reveals the inner dispositions of human beings and makes them open to new creations. In this article, we will examine the impact of technology on (...)
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  2. Therapeutic Chatbots as Cognitive-Affective Artifacts.J. P. Grodniewicz & Mateusz Hohol - 2024 - Topoi 43 (3):795-807.
    Conversational Artificial Intelligence (CAI) systems (also known as AI “chatbots”) are among the most promising examples of the use of technology in mental health care. With already millions of users worldwide, CAI is likely to change the landscape of psychological help. Most researchers agree that existing CAIs are not “digital therapists” and using them is not a substitute for psychotherapy delivered by a human. But if they are not therapists, what are they, and what role can they play in mental (...)
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  3. What is it for a Machine Learning Model to Have a Capability?Jacqueline Harding & Nathaniel Sharadin - forthcoming - British Journal for the Philosophy of Science.
    What can contemporary machine learning (ML) models do? Given the proliferation of ML models in society, answering this question matters to a variety of stakeholders, both public and private. The evaluation of models' capabilities is rapidly emerging as a key subfield of modern ML, buoyed by regulatory attention and government grants. Despite this, the notion of an ML model possessing a capability has not been interrogated: what are we saying when we say that a model is able to do something? (...)
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  4. A Risk-Based Regulatory Approach to Autonomous Weapon Systems.Alexander Blanchard, Claudio Novelli, Luciano Floridi & Mariarosaria Taddeo - manuscript
    International regulation of autonomous weapon systems (AWS) is increasingly conceived as an exercise in risk management. This requires a shared approach for assessing the risks of AWS. This paper presents a structured approach to risk assessment and regulation for AWS, adapting a qualitative framework inspired by the Intergovernmental Panel on Climate Change (IPCC). It examines the interactions among key risk factors—determinants, drivers, and types—to evaluate the risk magnitude of AWS and establish risk tolerance thresholds through a risk matrix informed by (...)
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  5. Plurale Autorschaft von Mensch und Künstlicher Intelligenz?David Lauer - 2023 - Literatur in Wissenschaft Und Unterricht 2023 (2):245-266.
    This paper (in German) discusses the question of what is going on when large language models (LLMs) produce meaningful text in reaction to human prompts. Can LLMs be understood as authors or producers of speech acts? I argue that this question has to be answered in the negative, for two reasons. First, due to their lack of semantic understanding, LLMs do not understand what they are saying and hence literally do not know what they are (linguistically) doing. Since the agent’s (...)
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  6. Giới thiệu về năm tiền đề của tương tác giữa người và máy trong kỉ nguyên trí tuệ nhân tạo.Manh-Tung Ho & T. Hong-Kong Nguyen - manuscript
    Bài viết này giới thiệu năm yếu tố tiền đề đó với mục đích gia tăng nhận thức về quan hệ giữa người và máy trong bối cảnh công nghệ ngày càng thay đổi cuộc sống thường nhật. Năm tiền đề bao gồm: Tiền đề về cấu trúc xã hội, văn hóa, chính trị, và lịch sử; về tính tự chủ và sự tự do của con người; về nền tảng triết học và nhân văn của nhân loại; về hiện (...)
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  7. Machina sapiens.Nello Cristianini - 2024 - Bologna: Il Mulino -.
    Machina sapiens - l;algoritmo che ci ha rubato il segreto della conoscenza. -/- Le macchine possono pensare? Questa domanda inquietante, posta da Alan Turing nel 1950, ha forse trovato una risposta: oggi si può conversare con un computer senza poterlo distinguere da un essere umano. I nuovi agenti intelligenti come ChatGPT si sono rivelati capaci di svolgere compiti che vanno molto oltre le intenzioni iniziali dei loro creatori, e ancora non sappiamo perché: se sono stati addestrati per alcune abilità, altre (...)
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  8. Making sense of ‘genetic programs’: biomolecular Post–Newell production systems.Mihnea Capraru - 2024 - Biology and Philosophy 39 (2):1-12.
    The biomedical literature makes extensive use of the concept of a genetic program. So far, however, the nature of genetic programs has received no satisfactory elucidation from the standpoint of computer science. This unsettling omission has led to doubts about the very existence of genetic programs, on the grounds that gene regulatory networks lack a predetermined schedule of execution, which may seem to contradict the very idea of a program. I show, however, that we can make perfect sense of genetic (...)
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  9. Artificial Psychology.Jay Friedenberg - 2008 - Psychology Press.
    What does it mean to be human? Philosophers and theologians have been wrestling with this question for centuries. Recent advances in cognition, neuroscience, artificial intelligence and robotics have yielded insights that bring us even closer to an answer. There are now computer programs that can accurately recognize faces, engage in conversation, and even compose music. There are also robots that can walk up a flight of stairs, work cooperatively with each other and express emotion. If machines can do everything we (...)
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  10. Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs.Harvey Lederman & Kyle Mahowald - forthcoming - Transactions of the Association for Computational Linguistics.
    Are LLMs cultural technologies like photocopiers or printing presses, which transmit information but cannot create new content? A challenge for this idea, which we call bibliotechnism, is that LLMs generate novel text. We begin with a defense of bibliotechnism, showing how even novel text may inherit its meaning from original human-generated text. We then argue that bibliotechnism faces an independent challenge from examples in which LLMs generate novel reference, using new names to refer to new entities. Such examples could be (...)
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  11. Prosthetic Godhood and Lacan’s Alethosphere: The Psychoanalytic Significance of the Interplay of Randomness and Structure in Generative Art.Rayan Magon - 2023 - 26Th Generative Art Conference.
    Psychoanalysis, particularly as articulated by figures like Freud and Lacan, highlights the inherent division within the human subject—a schism between the conscious and unconscious mind. It could be said that this suggests that such an internal division becomes amplified in the context of generative art, where technology and algorithms are used to generate artistic expressions that are meant to emerge from the depths of the unconscious. Here, we encounter the tension between the conscious artist and the generative process itself, which (...)
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  12. Operationalising Representation in Natural Language Processing.Jacqueline Harding - forthcoming - British Journal for the Philosophy of Science.
    Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...)
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  13. 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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  14. Turning queries into questions: For a plurality of perspectives in the age of AI and other frameworks with limited (mind)sets.Claudia Westermann & Tanu Gupta - 2023 - Technoetic Arts 21 (1):3-13.
    The editorial introduces issue 21.1 of Technoetic Arts via a critical reflection on the artificial intelligence hype (AI hype) that emerged in 2022. Tracing the history of the critique of Large Language Models, the editorial underscores that there are substantial ethical challenges related to bias in the training data, copyright issues, as well as ecological challenges which the technology industry has consistently downplayed over the years. -/- The editorial highlights the distinction between the current AI technology’s reliance on extensive pre-existing (...)
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  15. Emerging plurality of life: Assessing the questions, challenges and opportunities.Jessica Abbott, Erik Persson & Olaf Witkowski - 2023 - Frontiers Human Dynamics 5:1153668.
    Research groups around the world are currently busy trying to invent new life in the laboratory, looking for extraterrestrial life, or making machines increasingly more life-like. In the case of astrobiology, any newly discovered life would likely be very old, but when discovered it would be new to us. In the case of synthetic organic life or life-like machines, humans will have invented life that did not exist before. Together, these endeavors amount to what we call the emerging plurality of (...)
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  16. Artificial Intelligence, Phenomenology, and the Molyneux Problem.Chris A. Kramer - 2023 - The Philosophy of Humor Yearbook 4 (1):225-226.
    This short article is a “conversation” in which an android, Mort, replies to Richard Marc Rubin’s android named Sol in “The Robot Sol Explains Laughter to His Android Brethren” (The Philosophy of Humor Yearbook, 2022). There Sol offers an explanation for how androids can laugh--largely a reaction to frustration and unmet expectations: “my account says that laughter is one of four ways of dealing with frustration, difficulties, and insults. It is a way of getting by. If you need to label (...)
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  17. Diffusing the Creator: Attributing Credit for Generative AI Outputs.Donal Khosrowi, Finola Finn & Elinor Clark - 2023 - Aies '23: Proceedings of the 2023 Aaai/Acm Conference on Ai, Ethics, and Society.
    The recent wave of generative AI (GAI) systems like Stable Diffusion that can produce images from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GAI? Existing views on creatorship are mixed: some insist that GAI systems are mere tools, and human prompters are creators proper; others are more open to acknowledging more significant roles for GAI, but most conceive (...)
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  18. The Great Philoosphical Objections to AI: The History and Legacy of the AI Wars.Eric Dietrich, Chris Fields, John P. Sullins, Van Heuveln Bram & Robin Zebrowski - 2021 - London: Bloomsbury Academic.
    This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets (...)
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  19. O "Frame Problem": a sensibilidade ao contexto como um desafio para teorias representacionais da mente.Carlos Barth - 2019 - Dissertation, Federal University of Minas Gerais
    Context sensitivity is one of the distinctive marks of human intelligence. Understanding the flexible way in which humans think and act in a potentially infinite number of circumstances, even though they’re only finite and limited beings, is a central challenge for the philosophy of mind and cognitive science, particularly in the case of those using representational theories. In this work, the frame problem, that is, the challenge of explaining how human cognition efficiently acknowledges what is relevant from what is not (...)
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  20. É Possível Evitar Vieses Algorítmicos?Carlos Barth - 2021 - Revista de Filosofia Moderna E Contemporânea 8 (3):39-68.
    Artificial intelligence (AI) techniques are used to model human activities and predict behavior. Such systems have shown race, gender and other kinds of bias, which are typically understood as technical problems. Here we try to show that: 1) to get rid of such biases, we need a system that can understand the structure of human activities and;2) to create such a system, we need to solve foundational problems of AI, such as the common-sense problem. Additionally, when informational platforms uses these (...)
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  21. Emerging Technologies & Higher Education.Jake Burley & Alec Stubbs - 2023 - Ieet White Papers.
    Extended Reality (XR) and Large Language Model (LLM) technologies have the potential to significantly influence higher education practices and pedagogy in the coming years. As these emerging technologies reshape the educational landscape, it is crucial for educators and higher education professionals to understand their implications and make informed policy decisions for both individual courses and universities as a whole. -/- This paper has two parts. In the first half, we give an overview of XR technologies and their potential future role (...)
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  22. The Role of A Priori Belief in the Design and Analysis of Fault-Tolerant Distributed Systems.Giorgio Cignarale, Ulrich Schmid, Tuomas Tahko & Roman Kuznets - 2023 - Minds and Machines 33 (2):293-319.
    The debate around the notions of a priori knowledge and a posteriori knowledge has proven crucial for the development of many fields in philosophy, such as metaphysics, epistemology, metametaphysics etc. We advocate that the recent debate on the two notions is also fruitful for man-made distributed computing systems and for the epistemic analysis thereof. Following a recently proposed modal and fallibilistic account of a priori knowledge, we elaborate the corresponding concept of a priori belief: We propose a rich taxonomy of (...)
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  23. Sono solo parole ChatGPT: anatomia e raccomandazioni per l’uso.Tommaso Caselli, Antonio Lieto, Malvina Nissim & Viviana Patti - 2023 - Sistemi Intelligenti 4:1-10.
  24. Thou Shalt Make a Human Mind in the Likeness of a Machine.Tomi Kokkonen, Ilmari Hirvonen & Matti Mäkikangas - 2022-10-17 - In Kevin S. Decker (ed.), Dune and Philosophy. Wiley. pp. 87–98.
    In God Emperor of Dune, Leto II explains to Moneo why people destroyed thinking machines in the Butlerian Jihad: "Humans had set those machines to usurp our sense of beauty, our necessary selfdom out of which we make living judgments." The Orange Catholic Bible (OCB), the key religious text in the Dune universe, forbids the creation of machines that imitate human thinking: "Thou shalt not make a machine in the likeness of a man's mind." The OCB focuses on human mental (...)
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  25. Waiting for a digital therapist: three challenges on the path to psychotherapy delivered by artificial intelligence.J. P. Grodniewicz & Mateusz Hohol - 2023 - Frontiers in Psychiatry 14 (1190084):1-12.
    Growing demand for broadly accessible mental health care, together with the rapid development of new technologies, trigger discussions about the feasibility of psychotherapeutic interventions based on interactions with Conversational Artificial Intelligence (CAI). Many authors argue that while currently available CAI can be a useful supplement for human-delivered psychotherapy, it is not yet capable of delivering fully fledged psychotherapy on its own. The goal of this paper is to investigate what are the most important obstacles on our way to developing CAI (...)
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  26. الفلسفة وتعويذة الجي بي تي.Salah Osman - manuscript
    لم نعد بحاجة إلى فانوس سحري نمسح عليه بأصابعنا لكي يخرج منه المارد القادر على خدمتنا وتلبية بعض أهم مطالبنا الحياتية، ولم نعد بحاجة إلى تعويذات نلج بها في عالم السحر والخيال؛ لقد خرج المارد بالفعل من قمقمه الحاسوبي؛ من جوف مختبرات البرمجة والذكاء الاصطناعي، بتعويذات (أكواد) رياضية رمزية سرعان ما تمكن من التهامها وهضمها، ليبيت قادرًا على إنتاج تعويذات أخرى مماثلة، وربما أفضل منها! خرج «المُحول التوليدي المدرب مُسبقًا»، المعروف اختصارًا باسم «جي بي تي»، ملوحًا بإمكانات بحثية وخدمية وإنتاجية (...)
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  27. العقل كبرمجيات حاسوبية.Salah Osman - manuscript
    تُخبرنا النظرية الحاسوبية للعقل (أو مذهب الحوسبة)، أن عقولنا تُشبه الحواسيب في عملها؛ أي أنها تتلقى مدخلات من العالم الخارجي، ثم تُنتج بالخوارزميات مخرجات في شكل حالات ذهنية أو أفعال. وبعبارة أخرى، تذهب النظرية إلى أن الدماغ لا يعدو أن يكون معالج معلومات؛ حيث يكون العقل بمثابة «برمجيات» (سوفت وير) تعمل على «جهاز» هو الدماغ (هارد وير). وما دام العقل مجرد برمجيات تخضع للحوسبة الفيزيائية بواسطة الأدمغة، أليس من الممكن إذن منطقيًا نقلها إلى أي حاسوب مثلما نقوم بنقل أية برمجيات (...)
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  28. More Human Than All Too Human: Challenges in Machine Ethics for Humanity Becoming a Spacefaring Civilization.Guy Pierre Du Plessis - 2023 - Qeios.
    It is indubitable that machines with artificial intelligence (AI) will be an essential component in humans’ quest to become a spacefaring civilization. Most would agree that long-distance space travel and the colonization of Mars will not be possible without adequately developed AI. Machines with AI have a normative function, but some argue that it can also be evaluated from the perspective of ethical norms. This essay is based on the assumption that machine ethics is an essential philosophical perspective in realizing (...)
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  29. Chatbots shouldn’t use emojis.Carissa Véliz - 2023 - Nature 615:375.
    Limits need to be set on AI’s ability to simulate human feelings. Ensuring that chatbots don’t use emotive language, including emojis, would be a good start. Emojis are particularly manipulative. Humans instinctively respond to shapes that look like faces — even cartoonish or schematic ones — and emojis can induce these reactions.
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  30. What does AI believe in?Evgeny Smirnov - manuscript
    I conducted an experiment by using four different artificial intelligence models developed by OpenAI to estimate the persuasiveness and rational justification of various philosophical stances. The AI models used were text-davinci-003, text-ada-001, text-curie-001, and text-babbage-001, which differed in complexity and the size of their training data sets. For the philosophical stances, the list of 30 questions created by Bourget & Chalmers (2014) was used. The results indicate that it seems that each model has its own plausible ‘cognitive’ style. The outcomes (...)
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  31. The Grossberg Code: Universal Neural Network Signatures of Perceptual Experience.Birgitta Dresp-Langley - 2023 - Information 14 (2):e82 1-17..
    Two universal functional principles of Grossberg’s Adaptive Resonance Theory [19] decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are re-visited (...)
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  32. Consciousness and Conscious Machines: What’s At Stake?Damien P. Williams - 2019 - Ceur Workshop Proceedings.
    This paper explores the moral, epistemological, and legal implications of multiple different definitions and formulations of human and nonhuman consciousness. Drawing upon research from race, gender, and disability studies, including the phenomenological basis for knowledge and claims to consciousness, I discuss the history of the struggles for personhood among different groups of humans, as well as nonhuman animals, and systems. In exploring the history of personhood struggles, we have a precedent for how engagements and recognition of conscious machines are likely (...)
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  33. AI Ethics in Higher Education: Insights from Africa and Beyond.Caitlin C. Corrigan, Simon Atuah Asakipaam, Jerry John Kponyo & Christoph Luetge (eds.) - 2023 - Springer Verlag.
    This open access book tackles the pressing problem of integrating concerns related to Artificial Intelligence (AI) ethics into higher education curriculums aimed at future AI developers in Africa and beyond. For doing so, it analyzes the present and future states of AI ethics education in local computer science and engineering programs. The authors share relevant best practices and use cases for teaching, develop answers to ongoing organizational challenges, and reflect on the practical implications of different theoretical approaches to AI ethics. (...)
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  34. The Shortcut - Why Intelligent Machines Do Not Think Like Us.Nello Cristianini - 2023 - Boca Raton, Florida: CRC Press.
    Book. From the Publisher. An influential scientist in the field of artificial intelligence (AI) explains its fundamental concepts and how it is changing culture and society. -/- A particular form of AI is now embedded in our tech, our infrastructure, and our lives. How did it get there? Where and why should we be concerned? And what should we do now? The Shortcut: Why Intelligent Machines Do Not Think Like Us provides an accessible yet probing exposure of AI in its (...)
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  35. Mapping the potential AI-driven virtual hyper-personalised ikigai universe.Soenke Ziesche & Roman Yampolskiy - manuscript
    Ikigai is a Japanese concept, which, in brief, refers to the “reason or purpose to live”. I-risks have been identified as a category of risks complementing x- risks, i.e., existential risks, and s-risks, i.e., suffering risks, which describes undesirable future scenarios in which humans are deprived of the pursuit of their individual ikigai. While some developments in AI increase i-risks, there are also AI-driven virtual opportunities, which reduce i-risks by increasing the space of potential ikigais, largely due to developments in (...)
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  36. How Is Perception Tractable?Tyler Brooke-Wilson - forthcoming - The Philosophical Review.
    Perception solves computationally demanding problems at lightning fast speed. It recovers sophisticated representations of the world from degraded inputs, often in a matter of milliseconds. Any theory of perception must be able to explain how this is possible; in other words, it must be able to explain perception's computational tractability. One of the few attempts to move toward such an explanation has been the information encapsulation hypothesis, which posits that perception can be fast because it keeps computational costs low by (...)
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  37. ¿What is Artificial Intelligence?Fabio Morandín-Ahuerma - 2022 - Int. J. Res. Publ. Rev 3 (12):1947-1951.
    La inteligencia artificial (IA) es la capacidad de una máquina o sistema informático para simular y realizar tareas que normalmente requerirían inteligencia humana, como el razonamiento lógico, el aprendizaje y la resolución de problemas. La inteligencia artificial se basa en el uso de algoritmos y tecnologías de aprendizaje automático para dar a las máquinas la capacidad de aplicar ciertas habilidades cognitivas y realizar tareas por sí mismas de manera autónoma o semiautónoma. La inteligencia artificial se distingue por su grado de (...)
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  38. How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  39. Techno-animism and the Pygmalion effect.Emanuele Arielli & Lev Manovich - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 3 of the ongoing publication "Artificial Aesthetics" Book information: Assume you're a designer, an architect, a photographer, a videographer, a curator, an art historian, a musician, a writer, an artist, or any other creative professional or student. Perhaps you're a digital content creator who works across multiple platforms. Alternatively, you could be an art historian, curator, or museum professional. -/- You may be wondering how AI will affect your professional area in general and your work and career. Our book (...)
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  40. 'AI for all' is a matter of social justice.Alessandra Buccella - 2022 - AI and Ethics 2:1-10.
    Artificial intelligence (AI) is a radically transformative technology (or system of technologies) that created new existential possibilities and new standards of well-being in human societies. In this article, I argue that to properly understand the increasingly important role AI plays in our society, we must consider its impacts on social justice. For this reason, I propose to conceptualize AI's transformative role and its socio-political implications through the lens of the theory of social justice known as the Capability Approach. According to (...)
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  41. Deepfakes, Intellectual Cynics, and the Cultivation of Digital Sensibility.Taylor Matthews - 2022 - Royal Institute of Philosophy Supplement 92:67-85.
    In recent years, a number of philosophers have turned their attention to developments in Artificial Intelligence, and in particular to deepfakes. A deepfake is a portmanteau of ‘deep learning' and ‘fake', and for the most part they are videos which depict people doing and saying things they never did. As a result, much of the emerging literature on deepfakes has turned on questions of trust, harms, and information-sharing. In this paper, I add to the emerging concerns around deepfakes by drawing (...)
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  42. 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, process, (...)
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  43. Integration in Educational Systems Extended with Artificial Intelligence – Based Technologies.Rossitza Kaltenborn - 2022 - Automatica and Informatics 1 (1):36-41.
    The main problems related to the integration of diverse functional elements of advanced intelligent learning systems are considered. It is shown that the integration of the elements in the learning process is a complex multilayered process due to the great variety and complexity of the ongoing basic processes – cognitive, pedagogical, technological, social and interpersonal. It is emphasized that the need for the integration process to be solved as a multifactor optimization data-driven problem and the use of modern techniques in (...)
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  44. Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - 2022 - Philosophy of Science 89 (5):1065-1074.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
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  45. Artificial Intelligence and Moral Theology: A Conversation.Brian Patrick Green, Matthew J. Gaudet, Levi Checketts, Brian Cutter, Noreen Herzfeld, Cory Andrew Labrecque, Anselm Ramelow, Paul Scherz, Marga Vega, Andrea Vicini & Jordan Joseph Wales - 2022 - Journal of Moral Theology 11 (Special Issue 1):13-40.
  46. The German Act on Autonomous Driving: Why Ethics Still Matters.Alexander Kriebitz, Raphael Max & Christoph Lütge - 2022 - Philosophy and Technology 35 (2):1-13.
    The German Act on Autonomous Driving constitutes the first national framework on level four autonomous vehicles and has received attention from policy makers, AI ethics scholars and legal experts in autonomous driving. Owing to Germany’s role as a global hub for car manufacturing, the following paper sheds light on the act’s position within the ethical discourse and how it reconfigures the balance between legislation and ethical frameworks. Specifically, in this paper, we highlight areas that need to be more worked out (...)
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  47. Philosophy of Artificial Intelligence.David Cycleback - 2019 - London (UK): Bookboon.
    This peer-reviewed book is a concise introduction to key philosophical questions in artificial intelligence that have long been debated by many of the great minds in computer science, cognitive science and philosophy, from Gottfried Leibniz to Alan Turing to Hubert Dreyfus. Topics include the limits of and problems in trying to create artificial general intelligence, if a computer can really think and have human-like sentience, how to identify intelligence in a computer, ethical and danger issues, and if human-like consciousness and (...)
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  48. The Mandatory Ontology of Robot Responsibility.Marc Champagne - 2021 - Cambridge Quarterly of Healthcare Ethics 30 (3):448–454.
    Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.
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  49. Artificial Intelligence, Mind and the Scholastics’ Notion of Intellectus.Justin Nnaemeka Onyeukaziri - manuscript
    For the philosopher, the most critical and fundamental question in the project of Artificial Intelligence is the question of intelligence or cognition in general. From the beginning of the research in “thinking Machining”, or Artificial Intelligence as it later became known, the key question is: What makes a thing intelligent or what constitutes intelligence? Since, intelligence, is a fundamental activity of the mind, the question, has been: Whether the mind is a computer or is the computer a mind? Many philosophers (...)
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  50. Climbing the Ladder: How Agents Reach Counterfactual Thinking.Caterina Moruzzi - 2022 - Proceedings of the 14th International Conference on Agents and Artificial Intelligence.
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