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  1. Beauty Filters in Self-Perception: The Distorted Mirror Gazing Hypothesis.Gloria Andrada - 2025 - Topoi:1-12.
    Beauty filters are automated photo editing tools that use artificial intelligence and computer vision to detect facial features and modify them, allegedly improving a face’s physical appearance and attractiveness. Widespread use of these filters has raised concern due to their potentially damaging psychological effects. In this paper, I offer an account that examines the effect that interacting with such filters has on self-perception. I argue that when looking at digitally-beautified versions of themselves, individuals are looking at AI-curated distorted mirrors. This (...)
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  2. Neurocomunicación en la educación: un estudio teórico con la perspectiva de la nueva experiencia en inteligencia artificial.Almudena Barrientos-Báez, David Caldevilla-Domínguez & Pedro García-Guirao - 2024 - In María Navarro-Granados, Noelia Pelícano Piris, Jesús Palenzuela-Bautista & Amelia Rosa Granda-Piñán (eds.), Investigación en escenarios formativos y conocimiento abierto en acción. Madrid: Dykinson. pp. 65-76.
    En las últimas décadas, la neurocomunicación ha emergido como un campo interdisciplinario que explora cómo los procesos neurológicos influyen en la manera en que las personas se comunican y aprenden. En el ámbito educativo, esta disciplina abre nuevas posibilidades para comprender cómo los estudiantes procesan la información y responden a los estímulos cognitivos y emocionales. Con la creciente influencia de la IA, se han desarrollado herramientas que permiten aplicar principios de neurocomunicación en contextos pedagógicos. Este artículo de revisión se centra (...)
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  3. Investigación en escenarios formativos y conocimiento abierto en acción.María Navarro-Granados, Noelia Pelícano Piris, Jesús Palenzuela-Bautista & Amelia Rosa Granda-Piñán (eds.) - 2024 - Madrid: Dykinson.
    El libro “Investigación en escenarios formativos y conocimiento abierto en acción” explora, a través de diez capítulos, una amplia gama de temas relevantes en el ámbito de la investigación educativa y la innovación docente, integrando teoría y práctica en diversos contextos educativos. Desde el análisis de herramientas psicométricas hasta el impacto de las tecnologías emergentes, esta obra adopta un enfoque multidisciplinario orientado a mejorar la calidad de la educación. En el Capítulo 1, se examinan las propiedades psicométricas del cuestionario LIDPED, (...)
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  4. Confronting the Limits of Optical Interpretation: Some Philosophical Considerations of Microscopic Details.Daniel Liu - 2024 - In Elizabeth Brogden & Christiane Frey (eds.), Milieus of minutiae: contextualizing the small in literature, philosophy, and science. Charlottesville: University of Virginia Press. pp. 122-148.
  5. Réinventer l’intégrité académique à l’ère de l’intelligence artificielle.Michelle Bergadaà & Paulo Peixoto (eds.) - forthcoming - Caen (France): EMS Management et Sociétés.
    Nous vivons aujourd'hui une période de transformations technologiques d'une ampleur sans précédent, où l'IA s'impose comme un phénomène qui redessine en profondeur les structures de notre société. Le monde académique, socle premier de la production et de la diffusion du savoir, est particulièrement touché par cette révolution. En produisant des contenus de manière autonome, en introduisant de nouvelles dynamiques qui reconfigurent les pratiques académiques, l'IA met à l'épreuve les valeurs sur lesquelles repose la légitimité scientifique. En dix chapitres issus de (...)
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  6. Récit, littérature et pratique littéraire : Délices du métier d'éditeur et les vertiges de l'IA.Ignace Haaz - forthcoming - In Michelle Bergadaà & Paulo Peixoto (eds.), Réinventer l’intégrité académique à l’ère de l’intelligence artificielle. Caen (France): EMS Management et Sociétés.
    Dans son chapitre, Ignace Haaz analyse la pratique littéraire depuis son poste d’observation d’éditeur. Traditionnellement, la publication scientifique est le fruit d’un processus rigoureux de recherche, de vérification et de validation par les pairs. Cependant, avec la capacité de l’IA à générer de manière autonome des textes cohérents et détaillés, il devient plus difficile de distinguer les travaux véritablement innovants de ceux qui ne sont que des répliques ou des compilations automatisées de travaux existants. Comment garantir que l’utilisation de l’IA (...)
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  7. A philosophical inquiry on the effect of reasoning in A.I models for bias and fairness.Aadit Kapoor - manuscript
    Advances in Artificial Intelligence (AI) have driven the evolution of reasoning in modern AI models, particularly with the development of Large Language Models (LLMs) and their "Think and Answer" paradigm. This paper explores the influence of human reinforcement on AI reasoning and its potential to enhance decision-making through dynamic human interaction. It analyzes the roots of bias and fairness in AI, arguing that these issues often stem from human data and reflect inherent human biases. The paper is structured as follows: (...)
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  8. A Capability Approach to AI Ethics.Emanuele Ratti & Mark Graves - 2025 - American Philosophical Quarterly 62 (1):1-16.
    We propose a conceptualization and implementation of AI ethics via the capability approach. We aim to show that conceptualizing AI ethics through the capability approach has two main advantages for AI ethics as a discipline. First, it helps clarify the ethical dimension of AI tools. Second, it provides guidance to implementing ethical considerations within the design of AI tools. We illustrate these advantages in the context of AI tools in medicine, by showing how ethics-based auditing of AI tools in medicine (...)
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  9. Do It Yourself Content and the Wisdom of the Crowds.Dallas Amico-Korby, Maralee Harrell & David Danks - 2025 - Erkenntnis:1-29.
    Many social media platforms enable (nearly) anyone to post (nearly) anything. One clear downside of this permissiveness is that many people appear bad at determining who to trust online. Hacks, quacks, climate change deniers, vaccine skeptics, and election deniers have all gained massive followings in these free markets of ideas, and many of their followers seem to genuinely trust them. At the same time, there are many cases in which people seem to reliably determine who to trust online. Consider, for (...)
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  10. Review of Nick Bostrom's Deep Utopia. [REVIEW]Matthew Hammerton - 2024 - Notre Dame Philosophical Reviews 202411.
    Nick Bostrom is perhaps best known for his 2014 book Superintelligence, which explores the existential threat posed to humans by superintelligent AI. In his new book, Deep Utopia, he shifts gears to explore the existentialist threat that superintelligent AI poses. Suppose that humans successfully navigate the technological, moral, and political challenges that come with advanced AI. The result of such success, according to Bostrom, would be a kind of deep utopia. We would not only live in a post-work, and post-scarcity (...)
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  11. Proletarianization of the Mind:A Media Theory of Artificial Intelligence after Simondon and Stiegler.Anaïs Nony - 2024 - Tropos. Rivista di Ermeneutica e Critica Filosofica 16 (1):116-136.
    This article draws on Bernard Stiegler and Gilbert Simondon’s work to further interrogate the psychic, social, and political problems raised by the development of Artificial Intelligence. Stiegler’s political philosophy of time-consciousness reveals three concomitants urgencies: human memory is conditioned by industrial supplements that are increasingly disruptive, capitalism has produced an entropic condition where life on earth is threaten by toxic systems, the deployment of technologies of spirits has striped individuals of their psychic and collective individuation. I read media theory along (...)
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  12. LLMs and practical knowledge: What is intelligence?Barry Smith - 2024 - In Kristof Nyiri (ed.), Electrifying the Future, 11th Budapest Visual Learning Conference. Budapest: Hungarian Academy of Science. pp. 19-26.
    Elon Musk famously predicted that an artificial intelligence superior to the smartest individual human would arrive by the year 2025. In response, Gary Marcus offered Musk a $1 million bet to the effect that he would be proved wrong. In specifying the conditions of this bet (which Musk did not take) Marcus lists the following ‘tasks that ordinary people can perform’ which, he claimed, AI will not be able to perform by the end of 2025. • Reliably drive a car (...)
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  13. As máquinas podem cuidar?E. M. Carvalho - 2024 - O Que Nos Faz Pensar 31 (53):6-24.
    Applications and devices of artificial intelligence are increasingly common in the healthcare field. Robots fulfilling some caregiving functions are not a distant future. In this scenario, we must ask ourselves if it is possible for machines to care to the extent of completely replacing human care and if such replacement, if possible, is desirable. In this paper, I argue that caregiving requires know-how permeated by affectivity that is far from being achieved by currently available machines. I also maintain that the (...)
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  14. The value of testimonial-based beliefs in the face of AI-generated quasi-testimony.Felipe Alejandro Álvarez Osorio & Ruth Marcela Espinosa Sarmiento - 2024 - Aufklärung 11 (Especial):25-38.
    The value of testimony as a source of knowledge has been a subject of epistemological debates. The "trust theory of testimony" suggests that human testimony is based on an affective relationship supported by social norms. However, the advent of generative artificial intelligence challenges our understanding of genuine testimony. The concept of "quasi-testimony" seeks to characterize utterances produced by non-human entities that mimic testimony but lack certain fundamental attributes. This article analyzes these issues in depth, exploring philosophical perspectives on testimony and (...)
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  15. The case for human–AI interaction as system 0 thinking.Marianna Bergamaschi Ganapini - 2024 - Nature Human Behaviour 8.
    The rapid integration of these artificial intelligence (AI) tools into our daily lives is reshaping how we think and make decisions. We propose that data-driven AI systems, by transcending individual artefacts and interfacing with a dynamic, multiartefact ecosystem, constitute a distinct psychological system. We call this ‘system 0’, and position it alongside Kahneman’s system 1 (fast, intuitive thinking) and system 2 (slow, analytical thinking).System 0 represents the outsourcing of certain cognitive tasks to AI, which can process vast amounts of data (...)
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  16. Emotional Cues and Misplaced Trust in Artificial Agents.Joseph Masotti - forthcoming - In Henry Shevlin (ed.), AI in Society: Relationships (Oxford Intersections). Oxford University Press.
    This paper argues that the emotional cues exhibited by AI systems designed for social interaction may lead human users to hold misplaced trust in such AI systems, and this poses a substantial problem for human-AI relationships. It begins by discussing the communicative role of certain emotions relevant to perceived trustworthiness. Since displaying such emotions is a reliable indicator of trustworthiness in humans, we use such emotions to assess agents’ trustworthiness according to certain generalizations of folk psychology. Our tendency to engage (...)
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  17. 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 disclose (...)
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  18. Trust in AI: Progress, Challenges, and Future Directions.Saleh Afroogh, Ali Akbari, Emmie Malone, Mohammadali Kargar & Hananeh Alambeigi - forthcoming - Nature Humanities and Social Sciences Communications.
    The increasing use of artificial intelligence (AI) systems in our daily life through various applications, services, and products explains the significance of trust/distrust in AI from a user perspective. AI-driven systems have significantly diffused into various fields of our lives, serving as beneficial tools used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust/distrust in AI plays the role of a regulator and could significantly (...)
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  19. Will AI and Humanity Go to War?Simon Goldstein - manuscript
    This paper offers the first careful analysis of the possibility that AI and humanity will go to war. The paper focuses on the case of artificial general intelligence, AI with broadly human capabilities. The paper uses a bargaining model of war to apply standard causes of war to the special case of AI/human conflict. The paper argues that information failures and commitment problems are especially likely in AI/human conflict. Information failures would be driven by the difficulty of measuring AI capabilities, (...)
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  20. From Past to Present: A study of AI-driven gamification in heritage education.Sepehr Vaez Afshar, Sarvin Eshaghi, Mahyar Hadighi & Guzden Varinlioglu - 2024 - 42Nd Conference on Education and Research in Computer Aided Architectural Design in Europe: Data-Driven Intelligence 2:249-258.
    The use of Artificial Intelligence (AI) in educational gamification marks a significant advancement, transforming traditional learning methods by offering interactive, adaptive, and personalized content. This approach makes historical content more relatable and promotes active learning and exploration. This research presents an innovative approach to heritage education, combining AI and gamification, explicitly targeting the Silk Roads. It represents a significant progression in a series of research, transitioning from basic 2D textual interactions to a 3D environment using photogrammetry, combining historical authenticity and (...)
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  21. Interpretable and accurate prediction models for metagenomics data.Edi Prifti, Antoine Danchin, Jean-Daniel Zucker & Eugeni Belda - 2020 - Gigascience 9 (3):giaa010.
    Background: Microbiome biomarker discovery for patient diagnosis, prognosis, and risk evaluation is attracting broad interest. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as black boxes and seldom generalize well. Their interpretation is challenging for physicians and biologists, which makes them difficult to trust and use routinely in the physician-patient decision-making process. Novel methods that provide interpretability and biological insight (...)
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  22. A Brief Note on Japan’s AI Race, the Copyright Dilemma, and Generative AI Impact on Authorship.Montserrat Crespin Perales - 2024 - Interface - Journal of European Languages and Literatures 24:3-22.
    Abstract This article delves into the intricate interplay between copyright laws, Artificial Intelligence (AI) technologies, and the evolving role of authors in the contemporary digital landscape, especially after the irruption of Generative AI systems, as ChatGPT. The paper scrutinizes Japan’s approach to copyright in the realm of AI training, highlighting the delicate balance between safeguarding creators’ rights and fostering competitiveness in the global market. By examining the concept of “the death of the Author” as elucidated by Roland Barthes, the study (...)
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  23. Patenting Bias: Algorithmic Race and Ethnicity Classifications, Proprietary Rights, and Public Data.Tiffany Nichols - 2022 - MIT Case Studies Series in Social and Ethical Responsibilities of Computing 2022 (Summer).
    By focusing on patents for recent algorithms that incorporate publicly available data to yield automated racial and ethnic classification schemes, I provide a glimpse into how engineers and programmers understand and define racial and ethnic categories. Patents provide insights into how engineers and programmers encode assumptions about identity and behavior, due to disclosure provisions required by US patent law; similar requirements are present in patent laws throughout the world. Such disclosures provide insights that are otherwise unavailable for most proprietary assets. (...)
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  24. Beyond the AI Divide: Towards an Inclusive Future Free from AI Caste Systems and AI Dalits.Yu Chen - manuscript
    In the rapidly evolving landscape of artificial intelligence (AI), disparities in access and benefits are becoming increasingly apparent, leading to the emergence of an AI divide. This divide not only amplifies existing socio-economic inequalities but also fosters the creation of AI caste systems, where marginalized groups—referred to as AI Dalits—are systematically excluded from AI advancements. This article explores the definitions and contributing factors of the AI divide and delves into the concept of AI caste systems, illustrating how they perpetuate inequality. (...)
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  25. A phenomenology and epistemology of large language models: transparency, trust, and trustworthiness.Richard Heersmink, Barend de Rooij, María Jimena Clavel Vázquez & Matteo Colombo - 2024 - Ethics and Information Technology 26 (3):1-15.
    This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. (...)
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  26. An Outlook for AI Innovation in Multimodal Communication Research.Alexander Henlein, Reetu Bhattacharjee & Jens Lemanski - 2024 - In Duffy Vincent G. (ed.), Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (HCII 2024). pp. 182–234.
    In the rapidly evolving landscape of multimodal communication research, this paper explores the transformative role of machine learning (ML), particularly using multimodal large language models, in tracking, augmenting, annotating, and analyzing multimodal data. Building upon the foundations laid in our previous work, we explore the capabilities that have emerged over the past years. The integration of ML allows researchers to gain richer insights from multimodal data, enabling a deeper understanding of human (and non-human) communication across modalities. In particular, augmentation methods (...)
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  27. Self-Absorption in the Digital Era: A Review of "Self-Improvement Technologies of the Soul in the Age of Artificial Intelligence" by Mark Coeckelbergh. [REVIEW]James J. Hughes - 2024 - Journal of Ethics and Emerging Technologies 33 (1).
    Mark Coeckelbergh is a Belgian philosopher who specializes in the philosophy of technology. His work primarily explores the intersection of technology and society, specifically the philosophical implications of emerging technologies such as AI and robotics. He has written on whether machines can be moral agents and how ethical frameworks should be applied to autonomous machines. He has a broad philosophical perspective drawing on classical sources, Eastern philosophy, Marxism, Foucault, phenomenology, and the postmodernists. In this short text, he brings his remarkable (...)
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  28. 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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  29. 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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  30. Artificial Intelligence for the Internal Democracy of Political Parties.Claudio Novelli, Giuliano Formisano, Prathm Juneja, Sandri Giulia & Luciano Floridi - 2024 - Minds and Machines 34 (36):1-26.
    The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can (...)
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  31. 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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  32. A narrative review of the active ingredients in psychotherapy delivered by conversational agents.Arthur Herbener, Michal Klincewicz & Malene Flensborg Damholdt A. Show More - 2024 - Computers in Human Behavior Reports 14.
    The present narrative review seeks to unravel where we are now, and where we need to go to delineate the active ingredients in psychotherapy delivered by conversational agents (e.g., chatbots). While psychotherapy delivered by conversational agents has shown promising effectiveness for depression, anxiety, and psychological distress across several randomized controlled trials, little emphasis has been placed on the therapeutic processes in these interventions. The theoretical framework of this narrative review is grounded in prominent perspectives on the active ingredients in psychotherapy. (...)
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  33. 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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  34. Cultural Bias in Explainable AI Research.Uwe Peters & Mary Carman - forthcoming - Journal of Artificial Intelligence Research.
    For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations and that (...)
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  35. 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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  36. Adopting trust as an ex post approach to privacy.Haleh Asgarinia - 2024 - AI and Ethics 3 (4).
    This research explores how a person with whom information has been shared and, importantly, an artificial intelligence (AI) system used to deduce information from the shared data contribute to making the disclosure context private. The study posits that private contexts are constituted by the interactions of individuals in the social context of intersubjectivity based on trust. Hence, to make the context private, the person who is the trustee (i.e., with whom information has been shared) must fulfil trust norms. According to (...)
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  37. The Best View Money Can Buy.Phillip B. Levin - 2024 - B&N Press. Amazon..
    A collection of philosophical fiction stories about the future, humanity, science, technology, artificial intelligence, and religion.
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  38. 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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  39. Escape climate apathy by harnessing the power of generative AI.Quan-Hoang Vuong & Manh-Tung Ho - 2024 - AI and Society 39 (6):1-2.
    “Throw away anything that sounds too complicated. Only keep what is simple to grasp...If the information appears fuzzy and causes the brain to implode after two sentences, toss it away and stop listening. Doing so will make the news as orderly and simple to understand as the truth.” - In “GHG emissions,” The Kingfisher Story Collection, (Vuong 2022a).
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  40. Beat the Simulation and Seize Control of Your Life.Julian Friedland & Kristian Myrseth - 2023 - Psychology Today 12 (26).
    The simulation hypothesis can reinforce a cynical dismissal of human potential. This attitude can allow online platform designers to rationalize employing manipulative neuromarketing techniques to control user decisions. We point to cognitive boosting techniques at both user and designer levels to build critical reflection and mindfulness.
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  41. Algorithmic Transparency and Manipulation.Michael Klenk - 2023 - Philosophy and Technology 36 (4):1-20.
    A series of recent papers raises worries about the manipulative potential of algorithmic transparency (to wit, making visible the factors that influence an algorithm’s output). But while the concern is apt and relevant, it is based on a fraught understanding of manipulation. Therefore, this paper draws attention to the ‘indifference view’ of manipulation, which explains better than the ‘vulnerability view’ why algorithmic transparency has manipulative potential. The paper also raises pertinent research questions for future studies of manipulation in the context (...)
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  42. The Challenges of Artificial Judicial Decision-Making for Liberal Democracy.Christoph Winter - 2022 - In P. Bystranowski, Bartosz Janik & M. Prochnicki (eds.), Judicial Decision-Making: Integrating Empirical and Theoretical Perspectives. Springer Nature. pp. 179-204.
    The application of artificial intelligence (AI) to judicial decision-making has already begun in many jurisdictions around the world. While AI seems to promise greater fairness, access to justice, and legal certainty, issues of discrimination and transparency have emerged and put liberal democratic principles under pressure, most notably in the context of bail decisions. Despite this, there has been no systematic analysis of the risks to liberal democratic values from implementing AI into judicial decision-making. This article sets out to fill this (...)
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  43. 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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  44. Ethics of Artificial Intelligence.Stefan Buijsman, Michael Klenk & Jeroen van den Hoven - forthcoming - In Nathalie Smuha (ed.), Cambridge Handbook on the Law, Ethics and Policy of AI. Cambridge University Press.
    Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the context (...)
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  45. ChatGPT’s Responses to Dilemmas in Medical Ethics: The Devil is in the Details.Lukas J. Meier - 2023 - American Journal of Bioethics 23 (10):63-65.
    In their Target Article, Rahimzadeh et al. (2023) discuss the virtues and vices of employing ChatGPT in ethics education for healthcare professionals. To this end, they confront the chatbot with a moral dilemma and analyse its response. In interpreting the case, ChatGPT relies on Beauchamp and Childress’ four prima-facie principles: beneficence, non-maleficence, respect for patient autonomy, and justice. While the chatbot’s output appears admirable at first sight, it is worth taking a closer look: ChatGPT not only misses the point when (...)
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  46. Operationalising Representation in Natural Language Processing.Jacqueline Harding - 2023 - 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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  47. The Curious Case of Uncurious Creation.Lindsay Brainard - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    This paper seeks to answer the question: Can contemporary forms of artificial intelligence be creative? To answer this question, I consider three conditions that are commonly taken to be necessary for creativity. These are novelty, value, and agency. I argue that while contemporary AI models may have a claim to novelty and value, they cannot satisfy the kind of agency condition required for creativity. From this discussion, a new condition for creativity emerges. Creativity requires curiosity, a motivation to pursue epistemic (...)
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  48. 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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  49. The Great Philosophical 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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  50. Quantum Intrinsic Curiosity Algorithms.Shanna Dobson & Julian Scaff - manuscript
    We propose a quantum curiosity algorithm as a means to implement quantum thinking into AI, and we illustrate 5 new quantum curiosity types. We then introduce 6 new hybrid quantum curiosity types combining animal and plant curiosity elements with biomimicry beyond human sensing. We then introduce 4 specialized quantum curiosity types, which incorporate quantum thinking into coding frameworks to radically transform problem-solving and discovery in science, medicine, and systems analysis. We conclude with a forecasting of the future of quantum thinking (...)
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