Results for 'AI epistemology'

963 found
Order:
  1.  85
    A Philosophical Inquiry into AI-Inclusive Epistemology.Ammar Younas & Yi Zeng - unknown
    This paper introduces the concept of AI-inclusive epistemology, suggesting that artificial intelligence (AI) may develop its own epistemological perspectives, function as an epistemic agent, and assume the role of a quasi-member of society. We explore the unique capabilities of advanced AI systems and their potential to provide distinct insights within knowledge systems traditionally dominated by human cognition. Additionally, the paper proposes a framework for a sustainable symbiotic society where AI and human intelligences collaborate to enhance the breadth and depth (...)
    Download  
     
    Export citation  
     
    Bookmark  
  2. AI and the expert; a blueprint for the ethical use of opaque AI.Amber Ross - forthcoming - AI and Society:1-12.
    The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  3. Chatbot Epistemology.Susan Schneider - manuscript
    AI chatbots are disseminating more and more of the Internet’s search engine activity, transforming the face of education, serving as personalized AIs in intellectual and emotional relationships with humans, becoming “digital workers” that may outmode us at work, and more. Indeed, the larger category of generative AI may be one of the most transformative technologies of this decade, or even this century. Given this, it is imperative that we understand the epistemological challenges that arise with the everyday use of LLM (...)
    Download  
     
    Export citation  
     
    Bookmark  
  4. The AI-Stance: Crossing the Terra Incognita of Human-Machine Interactions?Anna Strasser & Michael Wilby - 2022 - In Raul Hakli, Pekka Mäkelä & Johanna Seibt (eds.), Social Robots in Social Institutions. Proceedings of Robophilosophy’22. IOS Press. pp. 286-295.
    Although even very advanced artificial systems do not meet the demanding conditions which are required for humans to be a proper participant in a social interaction, we argue that not all human-machine interactions (HMIs) can appropriately be reduced to mere tool-use. By criticizing the far too demanding conditions of standard construals of intentional agency we suggest a minimal approach that ascribes minimal agency to some artificial systems resulting in the proposal of taking minimal joint actions as a case of a (...)
    Download  
     
    Export citation  
     
    Bookmark  
  5. AI-Testimony, Conversational AIs and Our Anthropocentric Theory of Testimony.Ori Freiman - 2024 - Social Epistemology 38 (4):476-490.
    The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can (...)
    Download  
     
    Export citation  
     
    Bookmark  
  6. ChatGPT and the Technology-Education Tension: Applying Contextual Virtue Epistemology to a Cognitive Artifact.Guido Cassinadri - 2024 - Philosophy and Technology 37 (14):1-28.
    According to virtue epistemology, the main aim of education is the development of the cognitive character of students (Pritchard, 2014, 2016). Given the proliferation of technological tools such as ChatGPT and other LLMs for solving cognitive tasks, how should educational practices incorporate the use of such tools without undermining the cognitive character of students? Pritchard (2014, 2016) argues that it is possible to properly solve this ‘technology-education tension’ (TET) by combining the virtue epistemology framework with the theory of (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  7. Ameliorating Algorithmic Bias, or Why Explainable AI Needs Feminist Philosophy.Linus Ta-Lun Huang, Hsiang-Yun Chen, Ying-Tung Lin, Tsung-Ren Huang & Tzu-Wei Hung - 2022 - Feminist Philosophy Quarterly 8 (3).
    Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias can be handled (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  8. Combating Disinformation with AI: Epistemic and Ethical Challenges.Benjamin Lange & Ted Lechterman - 2021 - IEEE International Symposium on Ethics in Engineering, Science and Technology (ETHICS) 1:1-5.
    AI-supported methods for identifying and combating disinformation are progressing in their development and application. However, these methods face a litany of epistemic and ethical challenges. These include (1) robustly defining disinformation, (2) reliably classifying data according to this definition, and (3) navigating ethical risks in the deployment of countermeasures, which involve a mixture of harms and benefits. This paper seeks to expose and offer preliminary analysis of these challenges.
    Download  
     
    Export citation  
     
    Bookmark  
  9. Science Based on Artificial Intelligence Need not Pose a Social Epistemological Problem.Uwe Peters - 2024 - Social Epistemology Review and Reply Collective 13 (1).
    It has been argued that our currently most satisfactory social epistemology of science can’t account for science that is based on artificial intelligence (AI) because this social epistemology requires trust between scientists that can take full responsibility for the research tools they use, and scientists can’t take full responsibility for the AI tools they use since these systems are epistemically opaque. I think this argument overlooks that much AI-based science can be done without opaque models, and that agents (...)
    Download  
     
    Export citation  
     
    Bookmark  
  10. (1 other version)A united framework of five principles for AI in society.Luciano Floridi & Josh Cowls - 2019 - Harvard Data Science Review 1 (1).
    Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these (...)
    Download  
     
    Export citation  
     
    Bookmark   76 citations  
  11. Conformism, Ignorance & Injustice: AI as a Tool of Epistemic Oppression.Martin Miragoli - 2024 - Episteme: A Journal of Social Epistemology:1-19.
    From music recommendation to assessment of asylum applications, machine-learning algorithms play a fundamental role in our lives. Naturally, the rise of AI implementation strategies has brought to public attention the ethical risks involved. However, the dominant anti-discrimination discourse, too often preoccupied with identifying particular instances of harmful AIs, has yet to bring clearly into focus the more structural roots of AI-based injustice. This paper addresses the problem of AI-based injustice from a distinctively epistemic angle. More precisely, I argue that the (...)
    Download  
     
    Export citation  
     
    Bookmark  
  12. Big data and their epistemological challenge.Luciano Floridi - 2012 - Philosophy and Technology 25 (4):435-437.
    Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.
    Download  
     
    Export citation  
     
    Bookmark   36 citations  
  13. The trustworthiness of AI: Comments on Simion and Kelp’s account.Dong-Yong Choi - 2023 - Asian Journal of Philosophy 2 (1):1-9.
    Simion and Kelp explain the trustworthiness of an AI based on that AI’s disposition to meet its obligations. Roughly speaking, according to Simion and Kelp, an AI is trustworthy regarding its task if and only if that AI is obliged to complete the task and its disposition to complete the task is strong enough. Furthermore, an AI is obliged to complete a task in the case where the task is the AI’s etiological function or design function. This account has a (...)
    Download  
     
    Export citation  
     
    Bookmark  
  14.  84
    Summary by an AI of Jean-Louis Boucon's "Introduction to the Ontology of Knowledge" and "Time, Space, and World as Knowledge" 20240724.Jean-Louis Boucon - 2024 - Academia.Edu.
    This summary is not exactly the way I would have done it myself but I must admit that my writing is sometimes a challenge to read. So I asked an AI to do this summary expecting that it will give an easily understandable although not totally accurate view on Ontology of Knowledge and from this general understanding help the reader to read the original papers. Jean-Louis Boucon’s works, "Introduction to the Ontology of Knowledge" and "Time, Space, and World as Knowledge," (...)
    Download  
     
    Export citation  
     
    Bookmark  
  15. Is a subpersonal epistemology possible? Re-evaluating cognitive integration for extended cognition.Hadeel Naeem - 2021 - Dissertation, University of Edinburgh
    Virtue reliabilism provides an account of epistemic integration that explains how a reliable-belief forming process can become a knowledge-conducive ability of one’s cognitive character. The univocal view suggests that this epistemic integration can also explain how an external process can extend one’s cognition into the environment. Andy Clark finds a problem with the univocal view. He claims that cognitive extension is a wholly subpersonal affair, whereas the epistemic integration that virtue reliabilism puts forward requires personal-level agential involvement. To adjust the (...)
    Download  
     
    Export citation  
     
    Bookmark  
  16. Making Sense of the Conceptual Nonsense 'Trustworthy AI'.Ori Freiman - 2022 - AI and Ethics 4.
    Following the publication of numerous ethical principles and guidelines, the concept of 'Trustworthy AI' has become widely used. However, several AI ethicists argue against using this concept, often backing their arguments with decades of conceptual analyses made by scholars who studied the concept of trust. In this paper, I describe the historical-philosophical roots of their objection and the premise that trust entails a human quality that technologies lack. Then, I review existing criticisms about 'Trustworthy AI' and the consequence of ignoring (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  17. Epistemological Alchemy through the hermeneutics of Bits and Bytes.Shahnawaz Akhtar - manuscript
    This paper delves into the profound advancements of Large Language Models (LLMs), epitomized by GPT-3, in natural language processing and artificial intelligence. It explores the epistemological foundations of LLMs through the lenses of Aristotle and Kant, revealing apparent distinctions from human learning. Transitioning seamlessly, the paper then delves into the ethical landscape, extending beyond knowledge acquisition to scrutinize the implications of LLMs in decision-making and content creation. The ethical scrutiny, employing virtue ethics, deontological ethics, and teleological ethics, delves into LLMs' (...)
    Download  
     
    Export citation  
     
    Bookmark  
  18. 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 (...)
    Download  
     
    Export citation  
     
    Bookmark  
  19. Living with Uncertainty: Full Transparency of AI isn’t Needed for Epistemic Trust in AI-based Science.Uwe Peters - forthcoming - Social Epistemology Review and Reply Collective.
    Can AI developers be held epistemically responsible for the processing of their AI systems when these systems are epistemically opaque? And can explainable AI (XAI) provide public justificatory reasons for opaque AI systems’ outputs? Koskinen (2024) gives negative answers to both questions. Here, I respond to her and argue for affirmative answers. More generally, I suggest that when considering people’s uncertainty about the factors causally determining an opaque AI’s output, it might be worth keeping in mind that a degree of (...)
    Download  
     
    Export citation  
     
    Bookmark  
  20. Biases, Evidence and Inferences in the story of Ai.Efraim Wallach - manuscript
    This treatise covers the history, now more than 170 years long, of researches and debates concerning the biblical city of Ai. This archetypical chapter in the evolution of biblical archaeology and historiography was never presented in full. I use the historical data as a case study to explore a number of epistemological issues, such as the creation and revision of scientific knowledge, the formation and change of consensus, the Kuhnian model of paradigm shift, several models of discrimination between hypotheses about (...)
    Download  
     
    Export citation  
     
    Bookmark  
  21. Artificial Intelligence as Art – What the Philosophy of Art can offer the understanding of AI and Consciousness.Hutan Ashrafian - manuscript
    Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of epistemological objectivity where the domains (...)
    Download  
     
    Export citation  
     
    Bookmark  
  22. Menalar Skeptis Adopsi Artificial Intelegence (AI) di Indonesia: ‘Sebuah Tinjauan Filsafat Ilmu Komunikasi’.Felisianus Efrem Jelahut, Herman Yosep Utang, Yosep Emanuel Jelahut & Lasarus Jehamat - 2021 - Jurnal Filsafat Indonesia 4 (2):172-178.
    This research was conducted on the basis of research references from Microsoft Indonesia regarding the adoption of artificial intelligence in Indonesia which obtained research results that there were 14% of employees and leaders of technology-based companies in Indonesia who were still skeptical of the adoption of artificial intelligence. This study aims to provide a theoretical overview from the point of view of the philosophy of communication science in responding to considerations about the good and bad 'doubt' or skepticism of 14% (...)
    Download  
     
    Export citation  
     
    Bookmark  
  23. Seeing by Models: Vision as Adaptative Epistemology.Ignazio Licata - 2012 - In G. MInati (ed.), Methods, Models, Simulations and Approaches Towards a General Theory of Change. World Scientific.
    In this paper we suggest a clarification in relation to the notions of computational and intrinsic emergence, by showing how the latter is deeply connected to the new Logical Openness Theory, an original extension of Gödel theorems to the model theory. The epistemological scenario we are going to make use of is that of the theory of vision, a particularly instructive one. In order to reach our goal we introduce a dynamic theory of relationship between the observer and the observed (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  24. Embodied intelligence: epistemological remarks on an emerging paradigm in the artificial intelligence debate.Nicola Di Stefano & Giampaolo Ghilardi - 2013 - Epistemologia 36 (1):100-111.
    In this paper we want to analyze some philosophical and epistemological connections between a new kind of technology recently developed within robotics, and the previous mechanical approach. A new paradigm about machine-design in robotics, currently defined as ‘Embodied Intelligence’, has recently been developed. Here we consider the debate on the relationship between the hand and the intellect, from the perspective of the history of philosophy, aiming at providing a more suitable understanding of this paradigm. The new bottom-up approach to design (...)
    Download  
     
    Export citation  
     
    Bookmark  
  25. Qurio: QBit Learning, Quantum Pedagogy, and Agentive AI Tutors.Shanna Dobson & Julian Scaff - manuscript
    We propose Qurio, which is our new model of pedagogy incorporating the principles of quantum mechanics with a curiosity AI called Curio AI equipped with a meta-curiosity algorithm. Curio has a curiosity profile that is in a quantum superposition of every possible curiosity type. We describe the ethos and tenets of Qurio, which we claim can create an environment supporting neuroplasticity that cultivates curiosity powered by tools that exhibit their own curiosity. We give examples of how to incorporate non-locality, complementarity, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  26. From human to artificial cognition and back: New perspectives on cognitively inspired AI systems.Antonio Lieto & Daniele Radicioni - 2016 - Cognitive Systems Research 39 (c):1-3.
    We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  27. La riscoperta dell'umiltà come virtù relazionale: la risposta della tradizione ai problemi contemporanei.Michel Croce - 2014 - In Simona Langella & Maria Silvia Vaccarezza (eds.), Emozioni e virtù. Percorsi e prospettive di un tema classico. Orthotes. pp. 159-170.
    Questo contributo riguarda il tema specifico dell’umiltà come virtù etica e nasce all’interno di uno studio più ampio sulla relazione tra umiltà in campo morale e umiltà intellettuale, tema ricorrente tra i sostenitori della Virtue Epistemology. L’intento di questo saggio è quello di approfondire il recente dibattito circa la natura dell’umiltà come virtù e la sua definizione e il mio obiettivo è quello di mostrare come la tradizione aristotelico-tomista, generalmente sottovalutata da chi si occupa di umiltà nella filosofia analitica (...)
    Download  
     
    Export citation  
     
    Bookmark  
  28. Imagine This: Opaque DLMs are Reliable in the Context of Justification.Logan Carter - manuscript
    Artificial intelligence (AI) and machine learning (ML) models have undoubtedly become useful tools in science. In general, scientists and ML developers are optimistic – perhaps rightfully so – about the potential that these models have in facilitating scientific progress. The philosophy of AI literature carries a different mood. The attention of philosophers remains on potential epistemological issues that stem from the so-called “black box” features of ML models. For instance, Eamon Duede (2023) argues that opacity in deep learning models (DLMs) (...)
    Download  
     
    Export citation  
     
    Bookmark  
  29. Deepfakes, Fake Barns, and Knowledge from Videos.Taylor Matthews - 2023 - Synthese 201 (2):1-18.
    Recent develops in AI technology have led to increasingly sophisticated forms of video manipulation. One such form has been the advent of deepfakes. Deepfakes are AI-generated videos that typically depict people doing and saying things they never did. In this paper, I demonstrate that there is a close structural relationship between deepfakes and more traditional fake barn cases in epistemology. Specifically, I argue that deepfakes generate an analogous degree of epistemic risk to that which is found in traditional cases. (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  30. 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 AI (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  31. From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap.Tianqi Kou - manuscript
    Two goals - improving replicability and accountability of Machine Learning research respectively, have accrued much attention from the AI ethics and the Machine Learning community. Despite sharing the measures of improving transparency, the two goals are discussed in different registers - replicability registers with scientific reasoning whereas accountability registers with ethical reasoning. Given the existing challenge of the Responsibility Gap - holding Machine Learning scientists accountable for Machine Learning harms due to them being far from sites of application, this paper (...)
    Download  
     
    Export citation  
     
    Bookmark  
  32. Saint Thomas d'Aquin contre les robots. Pistes pour une approche philosophique de l'Intelligence Artificielle.Matthieu Raffray - 2019 - Angelicum 4 (96):553-572.
    In light of the pervasive developments of new technologies, such as NBIC (Nanotechnology, biotechnology, information technology, and cognitive science), it is imperative to produce a coherent and deep reflexion on the human nature, on human intelligence and on the limit of both of them, in order to successfully respond to some technical argumentations that strive to depict humanity as a purely mechanical system. For this purpose, it is interesting to refer to the epistemology and metaphysics of Thomas Aquinas as (...)
    Download  
     
    Export citation  
     
    Bookmark  
  33. Understanding Biology in the Age of Artificial Intelligence.Adham El Shazly, Elsa Lawerence, Srijit Seal, Chaitanya Joshi, Matthew Greening, Pietro Lio, Shantung Singh, Andreas Bender & Pietro Sormanni - manuscript
    Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet it (...)
    Download  
     
    Export citation  
     
    Bookmark  
  34. The Explanatory Role of Machine Learning in Molecular Biology.Fridolin Gross - forthcoming - Erkenntnis:1-21.
    The philosophical debate around the impact of machine learning in science is often framed in terms of a choice between AI and classical methods as mutually exclusive alternatives involving difficult epistemological trade-offs. A common worry regarding machine learning methods specifically is that they lead to opaque models that make predictions but do not lead to explanation or understanding. Focusing on the field of molecular biology, I argue that in practice machine learning is often used with explanatory aims. More specifically, I (...)
    Download  
     
    Export citation  
     
    Bookmark  
  35. When the (Bayesian) ideal is not ideal.Danilo Fraga Dantas - 2023 - Logos and Episteme 15 (3):271-298.
    Bayesian epistemologists support the norms of probabilism and conditionalization using Dutch book and accuracy arguments. These arguments assume that rationality requires agents to maximize practical or epistemic value in every doxastic state, which is evaluated from a subjective point of view (e.g., the agent’s expectancy of value). The accuracy arguments also presuppose that agents are opinionated. The goal of this paper is to discuss the assumptions of these arguments, including the measure of epistemic value. I have designed AI agents based (...)
    Download  
     
    Export citation  
     
    Bookmark  
  36. Hijacking Epistemic Agency - How Emerging Technologies Threaten our Wellbeing as Knowers.John Dorsch - 2022 - Proceedings of the 2022 Aaai/Acm Conference on Ai, Ethics, and Society 1.
    The aim of this project to expose the reasons behind the pandemic of misinformation (henceforth, PofM) by examining the enabling conditions of epistemic agency and the emerging technologies that threaten it. I plan to research the emotional origin of epistemic agency, i.e. on the origin of our capacity to acquire justification for belief, as well as on the significance this emotional origin has for our lives as epistemic agents in our so-called Misinformation Age. This project has three objectives. First, I (...)
    Download  
     
    Export citation  
     
    Bookmark  
  37. Ex Machina: Testing Machines for Consciousness and Socio-Relational Machine Ethics.Harrison S. Jackson - 2022 - Journal of Science Fiction and Philosophy 5.
    Ex Machina is a 2014 science-fiction film written and directed by Alex Garland, centered around the creation of a human-like artificial intelligence (AI) named Ava. The plot focuses on testing Ava for consciousness by offering a unique reinterpretation of the Turing Test. The film offers an excellent thought experiment demonstrating the consequences of various approaches to a potentially conscious AI. In this paper, I will argue that intelligence testing has significant epistemological shortcomings that necessitate an ethical approach not reliant on (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  38.  29
    Introduction: Algorithmic Thought.M. Beatrice Fazi - 2021 - Theory, Culture and Society 38 (7-8):5-11.
    This introduction to a special section on algorithmic thought provides a framework through which the articles in that collection can be contextualised and their individual contributions highlighted. Over the past decade, there has been a growing interest in artificial intelligence (AI). This special section reflects on this AI boom and its implications for studying what thinking is. Focusing on the algorithmic character of computing machines and the thinking that these machines might express, each of the special section’s essays considers different (...)
    Download  
     
    Export citation  
     
    Bookmark  
  39. La fisica unifenomenica cartesiana e il punto debole dell'IA forte.Rocco Vittorio Macrì - 2001 - Episteme 4.
    “If you find it strange that, in setting out these elements, I do not use those qualities called heat, cold, moistness, and dryness, as do the philosophers, I shall say to you that these qualities appear to me to be themselves in need of explanation. Indeed, unless I am mistaken, not only these four qualities, but also all the others (indeed all the forms of inanimate bodies) can be explained without the need of supposing for that purpose any other thing (...)
    Download  
     
    Export citation  
     
    Bookmark  
  40. The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised (...)
    Download  
     
    Export citation  
     
    Bookmark   16 citations  
  41. Informational richness and its impact on algorithmic fairness.Marcello Di Bello & Ruobin Gong - forthcoming - Philosophical Studies:1-29.
    The literature on algorithmic fairness has examined exogenous sources of biases such as shortcomings in the data and structural injustices in society. It has also examined internal sources of bias as evidenced by a number of impossibility theorems showing that no algorithm can concurrently satisfy multiple criteria of fairness. This paper contributes to the literature stemming from the impossibility theorems by examining how informational richness affects the accuracy and fairness of predictive algorithms. With the aid of a computer simulation, we (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  42. Action and Agency in Artificial Intelligence: A Philosophical Critique.Justin Nnaemeka Onyeukaziri - 2023 - Philosophia: International Journal of Philosophy (Philippine e-journal) 24 (1):73-90.
    The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language and science of artificial (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  43.  39
    Thomas Kelly, "Bias: A Philosophical Study". [REVIEW]Jyoti Kishore - 2024 - Philosophy in Review 44 (3):19-21.
    Thomas Kelly's book 'Bias: A philosophical study', is a philosophical exploration of the phenomena of bias and our practice of attributing it. He delves into the multifaceted nature of bias and offers a norm theoretic account for conceptualizing the phenomenon as typically involving "systematic departures from the norms". As a topic of inquiry, bias has attracted comparatively less attention in philosophy than in other disciplines like psychology and statistics. Hence, this book is an interesting and relevant read. Scholars working in (...)
    Download  
     
    Export citation  
     
    Bookmark  
  44. Interdisciplinary Confusion and Resolution in the Context of Moral Machines.Jakob Stenseke - 2022 - Science and Engineering Ethics 28 (3):1-17.
    Recent advancements in artificial intelligence have fueled widespread academic discourse on the ethics of AI within and across a diverse set of disciplines. One notable subfield of AI ethics is machine ethics, which seeks to implement ethical considerations into AI systems. However, since different research efforts within machine ethics have discipline-specific concepts, practices, and goals, the resulting body of work is pestered with conflict and confusion as opposed to fruitful synergies. The aim of this paper is to explore ways to (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  45. 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 potentially shed (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  46. Philosophy of Artificial Intelligence: A Course Outline.William J. Rapaport - 1986 - Teaching Philosophy 9 (2):103-120.
    In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the Philosophy Department’s (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  47. The Discovery of the Artificial: Behavior, Mind and Machines Before and Beyond Cybernetics.Roberto Cordeschi - 2002 - Kluwer Academic Publishers.
    Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building of (...)
    Download  
     
    Export citation  
     
    Bookmark   25 citations  
  48. Ranking Theory and Conditional Reasoning.Niels Skovgaard-Olsen - 2016 - Cognitive Science 40 (4):848-880.
    Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and (...)
    Download  
     
    Export citation  
     
    Bookmark   16 citations  
  49. Artificial Intelligence and the Notions of the “Natural” and the “Artificial.”.Justin Nnaemeka Onyeukaziri - 2022 - Journal of Data Analysis 17 (No. 4):101-116.
    This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind in general. This paper, intends to (...)
    Download  
     
    Export citation  
     
    Bookmark  
  50.  79
    A feeling for the algorithm: Diversity, expertise and artificial intelligence.Catherine Stinson & Sofie Vlaad - 2024 - Big Data and Society 11 (1).
    Diversity is often announced as a solution to ethical problems in artificial intelligence (AI), but what exactly is meant by diversity and how it can solve those problems is seldom spelled out. This lack of clarity is one hurdle to motivating diversity in AI. Another hurdle is that while the most common perceptions about what diversity is are too weak to do the work set out for them, stronger notions of diversity are often defended on normative grounds that fail to (...)
    Download  
     
    Export citation  
     
    Bookmark  
1 — 50 / 963