- New
-
Topics
- All Categories
- Metaphysics and Epistemology
- Value Theory
- Science, Logic, and Mathematics
- Science, Logic, and Mathematics
- Logic and Philosophy of Logic
- Philosophy of Biology
- Philosophy of Cognitive Science
- Philosophy of Computing and Information
- Philosophy of Mathematics
- Philosophy of Physical Science
- Philosophy of Social Science
- Philosophy of Probability
- General Philosophy of Science
- Philosophy of Science, Misc
- History of Western Philosophy
- Philosophical Traditions
- Philosophy, Misc
- Other Academic Areas
- Journals
- Submit material
- More
Philosophy of Artificial Intelligence
Edited by Eric Dietrich (State University of New York at Binghamton)
Assistant editor: Michelle Thomas (University of Western Ontario)
About this topic
| Summary |
The philosophy of artificial intelligence is a collection of issues primarily concerned with whether or not AI is possible -- with whether or not it is possible to build an intelligent thinking machine. Also of concern is whether humans and other animals are best thought of as machines (computational robots, say) themselves. The most important of the "whether-possible" problems lie at the intersection of theories of the semantic contents of thought and the nature of computation. A second suite of problems surrounds the nature of rationality. A third suite revolves around the seeming “transcendent” reasoning powers of the human mind. These problems derive from Kurt Gödel's famous Incompleteness Theorem. A fourth collection of problems concerns the architecture of an intelligent machine. Should a thinking computer use discrete or continuous modes of computing and representing, is having a body necessary, and is being conscious necessary. This takes us to the final set of questions. Can a computer be conscious? Can a computer have a moral sense? Would we have duties to thinking computers, to robots? For example, is it moral for humans to even attempt to build an intelligent machine? If we did build such a machine, would turning it off be the equivalent of murder? If we had a race of such machines, would it be immoral to force them to work for us? |
| Key works | Probably the most important attack on whether AI is possible is John Searle's famous Chinese Room Argument: Searle 1980. This attack focuses on the semantic aspects (mental semantics) of thoughts, thinking, and computing. For some replies to this argument, see the same 1980 journal issue as Searle's original paper. For the problem of the nature of rationality, see Pylyshyn 1987. An especially strong attack on AI from this angle is Jerry Fodor's work on the frame problem: Fodor 1987. On the frame problem in general, see McCarthy & Hayes 1969. For some replies to Fodor and advances on the frame problem, see Ford & Pylyshyn 1996. For the transcendent reasoning issue, a central and important paper is Hilary Putnam's Putnam 1960. This paper is arguably the source for the computational turn in 1960s-70s philosophy of mind. For architecture-of-mind issues, see, for starters: M. Spivey's The Contintuity of Mind, Oxford, which argues against the notion of discrete representations. See also, Gelder & Port 1995. For an argument for discrete representations, see, Dietrich & Markman 2003. For an argument that the mind's boundaries do not end at the body's boundaries, see, Clark & Chalmers 1998. For a statement of and argument for computationalism -- the thesis that the mind is a kind of computer -- see Shimon Edelman's excellent book Edelman 2008. See also Chapter 9 of Chalmers's book Chalmers 1996. |
| Introductions | Chinese Room Argument: Searle 1980. Frame problem: Fodor 1987, Computationalism and Godelian style refutation: Putnam 1960. Architecture: M. Spivey's The Contintuity of Mind, Oxford and Shimon Edelman's Edelman 2008. Ethical issues: Anderson & Anderson 2011 and Müller 2020. Conscious computers: Chalmers 2011. |
Show all references
Related
Subcategories
Artificial Minds (2,110 | 393)
The Turing Test (483)
The Chinese Room (272)
Machine Consciousness (371)
The Singularity* (112)
Mind Uploading* (50)
Artificial Minds, Misc (320)
Representation in Artificial Intelligence (846 | 185)
Areas of Artificial Intelligence (1,315 | 294)
Artificial Life* (258)
Computer Vision (10)
Cybernetics (206)
Dynamical Systems (226)
The Frame Problem (91)
Robotics (310)
Ethics of Artificial Intelligence (2,727 | 11)
Algorithmic Fairness (163)
Autonomous Vehicles (26)
Autonomous Weapons (44)
Machine Ethics (534)
Robot Ethics* (486)
Impact of Artificial Intelligence (1,058 | 115)
Autonomous Weapons* (44)
Autonomous Vehicles* (26)
Cyborgs (26)
Mind Uploading (50)
The Singularity (112)
Transhumanism (438)
Contents
15226 found
Order:
| 1 — 50 / 15226 |
Material to categorize
- If AI is our co-pilot, who is the captain?K. Woods - forthcoming - AI and Society:1-2.
- Ethics and administration of the ‘Res publica’: dynamics of democracy.Satinder P. Gill - forthcoming - AI and Society:1-3.
- Artificial Intelligence and the Phenomenology of Crisis.Jacob Martin Rump - manuscriptThis is the lightly revised text of my commentary/response to David Carr’s keynote address, “Phenomenology of Crisis,” at the 2024 meeting of the Husserl Circle.
- Tool-Augmented Human Creativity.Kjell Jørgen Hole - 2024 - Minds and Machines 34 (2):1-14.Creativity is the hallmark of human intelligence. Roli et al. (Frontiers in Ecology and Evolution 9:806283, 2022) state that algorithms cannot achieve human creativity. This paper analyzes cooperation between humans and intelligent algorithmic tools to compensate for algorithms’ limited creativity. The intelligent tools have functionality from the neocortex, the brain’s center for learning, reasoning, planning, and language. The analysis provides four key insights about human-tool cooperation to solve challenging problems. First, no neocortex-based tool without feelings can achieve human creativity. Second, (...)
- Black-Box Testing and Auditing of Bias in ADM Systems.Tobias D. Krafft, Marc P. Hauer & Katharina Zweig - 2024 - Minds and Machines 34 (2).For years, the number of opaque algorithmic decision-making systems (ADM systems) with a large impact on society has been increasing: e.g., systems that compute decisions about future recidivism of criminals, credit worthiness, or the many small decision computing systems within social networks that create rankings, provide recommendations, or filter content. Concerns that such a system makes biased decisions can be difficult to investigate: be it by people affected, NGOs, stakeholders, governmental testing and auditing authorities, or other external parties. Scientific testing (...)
- Perceived responsibility in AI-supported medicine.S. Krügel, J. Ammeling, M. Aubreville, A. Fritz, A. Kießig & Matthias Uhl - forthcoming - AI and Society:1-11.In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, although this is traditionally considered a category mistake in normative ethics. This tendency is stronger when (...)
- The New Mechanistic Approach and Cognitive Ontology—Or: What role do (neural) mechanisms play in cognitive ontology?Beate Krickel - forthcoming - Minds and Machines.Cognitive ontology has become a popular topic in philosophy, cognitive psychology, and cognitive neuroscience. At its center is the question of which cognitive capacities should be included in the ontology of cognitive psychology and cognitive neuroscience. One common strategy for answering this question is to look at brain structures and determine the cognitive capacities for which they are responsible. Some authors interpret this strategy as a search for neural mechanisms, as understood by the so-called new mechanistic approach. In this article, (...)Remove from this listExport citation
Bookmark - Julian Jaynes and the Next Metaphor of Mind: Rethinking Consciousness in the Age of Artificial Intelligence.George Saad - 2023 - Analecta Hermeneutica 15 (1):122-137.In _The Origin of Consciousness in the Breakdown of the Bicameral Mind_, Julian Jaynes presents a philosophy of mind with radical implications for contemporary discussions about artificial intelligence (AI). The ability of AI to replicate the cognitive functions of human consciousness has led to widespread speculation that AI is itself conscious (or will eventually become so). Against this functionalist theory of mind, Jaynes argues that consciousness only arises through the mythopoetic inspiration of metaphorical language. Consciousness develops and enacts new forms (...)
- Against AI Ableism: On "Optimal" Machines and "Disabled" Human Beings.George Saad - 2024 - Borderless Philosophy 7:171-190.My aim in this paper is to show how the functionalist standards assumed in the AI debate are, in fact, the assumptions of a capitalist, ableist society writ large. The already established argument against the proposed humanity of AI systems implies a wider critique of the entire ideology of functionalism under which the notion of intelligent machines has taken root.
- The Executioner Paradox: understanding self-referential dilemma in computational systems.Sachit Mahajan - forthcoming - AI and Society:1-8.As computational systems burgeon with advancing artificial intelligence (AI), the deterministic frameworks underlying them face novel challenges, especially when interfacing with self-modifying code. The Executioner Paradox, introduced herein, exemplifies such a challenge where a deterministic Executioner Machine (EM) grapples with self-aware and self-modifying code. This unveils a self-referential dilemma, highlighting a gap in current deterministic computational frameworks when faced with self-evolving code. In this article, the Executioner Paradox is proposed, highlighting the nuanced interactions between deterministic decision-making and self-aware code, and (...)
- Navigating technological shifts: worker perspectives on AI and emerging technologies impacting well-being.Tim Hinks - forthcoming - AI and Society:1-11.This paper asks whether workers’ experience of working with new technologies and workers’ perceived threats of new technologies are associated with expected well-being. Using survey data for 25 OECD countries we find that both experiences of new technologies and threats of new technologies are associated with more concern about expected well-being. Controlling for the negative experiences of COVID-19 on workers and their macroeconomic outlook both mitigate these findings, but workers with negative experiences of working alongside and with new technologies still (...)
- Personal AI, deception, and the problem of emotional bubbles.Philip Maxwell Thingbø Mlonyeni - forthcoming - AI and Society:1-12.Personal AI is a new type of AI companion, distinct from the prevailing forms of AI companionship. Instead of playing a narrow and well-defined social role, like friend, lover, caretaker, or colleague, with a set of pre-determined responses and behaviors, Personal AI is engineered to tailor itself to the user, including learning to mirror the user’s unique emotional language and attitudes. This paper identifies two issues with Personal AI. First, like other AI companions, it is deceptive about the presence of (...)
- Using artificial intelligence to enhance patient autonomy in healthcare decision-making.Jose Luis Guerrero Quiñones - forthcoming - AI and Society:1-10.The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative impact of (...)
- Artificial Intelligence and the future of work.John-Stewart Gordon & David J. Gunkel - forthcoming - AI and Society:1-7.In this paper, we delve into the significant impact of recent advancements in Artificial Intelligence (AI) on the future landscape of work. We discuss the looming possibility of mass unemployment triggered by AI and the societal repercussions of this transition. Despite the challenges this shift presents, we argue that it also unveils opportunities to mitigate social inequalities, combat global poverty, and empower individuals to follow their passions. Amidst this discussion, we also touch upon the existential question of the purpose of (...)
- How does artificial intelligence work in organisations? Algorithmic management, talent and dividuation processes.Joan Rovira Martorell, Francisco Tirado, José Luís Blasco & Ana Gálvez - forthcoming - AI and Society:1-11.This article analyses the forms of dividuation workers undergo when they are linked to technologies, such as algorithms or artificial intelligence. It examines functionalities and operations deployed by certain types of Talent Management software and apps—UKG, Tribepad, Afiniti, RetailNext and Textio. Specifically, it analyses how talented workers materialise in relation to the profiles and the statistical models generated by such artificial intelligence machines. It argues that these operate as a nooscope that allows the transindividual plane to be quantified through a (...)
- The extimate core of understanding: absolute metaphors, psychosis and large language models.Marc Heimann & Anne-Friederike Hübener - forthcoming - AI and Society:1-12.This paper delves into the striking parallels between the linguistic patterns of Large Language Models (LLMs) and the concepts of psychosis in Lacanian psychoanalysis. Lacanian theory, with its focus on the formal and logical underpinnings of psychosis, provides a compelling lens to juxtapose human cognition and AI mechanisms. LLMs, such as GPT-4, appear to replicate the intricate metaphorical and metonymical frameworks inherent in human language. Although grounded in mathematical logic and probabilistic analysis, the outputs of LLMs echo the nuanced linguistic (...)
- Why artificial intelligence needs sociology of knowledge: parts I and II.Harry Collins - forthcoming - AI and Society:1-15.Recent developments in artificial intelligence based on neural nets—deep learning and large language models which together I refer to as NEWAI—have resulted in startling improvements in language handling and the potential to keep up with changing human knowledge by learning from the internet. Nevertheless, examples such as ChatGPT, which is a ‘large language model’, have proved to have no moral compass: they answer queries with fabrications with the same fluency as they provide facts. I try to explain why this is, (...)
- The influential role of artificial intelligence (AI) adoption in digital value creation for small and medium enterprises (SMEs): does technological orientation mediate this relationship?Muhammad Farhan Jalil, Patrick Lynch, Dayang Affizzah Binti Awang Marikan & Abu Hassan Bin Md Isa - forthcoming - AI and Society.
- Reflective Artificial Intelligence.Peter R. Lewis & Ştefan Sarkadi - 2024 - Minds and Machines 34 (2):1-30.As artificial intelligence (AI) technology advances, we increasingly delegate mental tasks to machines. However, today’s AI systems usually do these tasks with an unusual imbalance of insight and understanding: new, deeper insights are present, yet many important qualities that a human mind would have previously brought to the activity are utterly absent. Therefore, it is crucial to ask which features of minds have we replicated, which are missing, and if that matters. One core feature that humans bring to tasks, when (...)
- Toward Sociotechnical AI: Mapping Vulnerabilities for Machine Learning in Context.Roel Dobbe & Anouk Wolters - 2024 - Minds and Machines 34 (2):1-51.This paper provides an empirical and conceptual account on seeing machine learning models as part of a sociotechnical system to identify relevant vulnerabilities emerging in the context of use. As ML is increasingly adopted in socially sensitive and safety-critical domains, many ML applications end up not delivering on their promises, and contributing to new forms of algorithmic harm. There is still a lack of empirical insights as well as conceptual tools and frameworks to properly understand and design for the impact (...)
- The age of the algorithmic society a Girardian analysis of mimesis, rivalry, and identity in the age of artificial intelligence.Lucas Freund - forthcoming - AI and Society:1-10.This paper explores the intersection of René Girard's mimetic theory and the algorithmic society, particularly in the context of the potential advent of Artificial General Intelligence (AGI). Girard's theory, which elucidates the dynamics of desire, rivalry, scapegoating, and the sacrificial crisis, provides a unique lens through which to examine the complexities of our relationship with AI and its role in the creation of the sacred. As individuals increasingly rely on AI recommendations, the distinction between personal choice and algorithmic manipulation becomes (...)
- The unseen dilemma of AI in mental healthcare.Akhil P. Joseph & Anithamol Babu - forthcoming - AI and Society:1-3.
- AI, automation and the lightening of work.David A. Spencer - forthcoming - AI and Society:1-11.Artificial intelligence (AI) technology poses possible threats to existing jobs. These threats extend not just to the number of jobs available but also to their quality. In the future, so some predict, workers could face fewer and potentially worse jobs, at least if society does not embrace reforms that manage the coming AI revolution. This paper uses the example of Daron Acemoglu and Simon Johnson’s recent book—_Power and Progress_ (2023)—to illustrate some of the dilemmas and options for managing the future (...)
- The case for a broader approach to AI assurance: addressing “hidden” harms in the development of artificial intelligence.Christopher Thomas, Huw Roberts, Jakob Mökander, Andreas Tsamados, Mariarosaria Taddeo & Luciano Floridi - forthcoming - AI and Society:1-16.Artificial intelligence (AI) assurance is an umbrella term describing many approaches—such as impact assessment, audit, and certification procedures—used to provide evidence that an AI system is legal, ethical, and technically robust. AI assurance approaches largely focus on two overlapping categories of harms: deployment harms that emerge at, or after, the point of use, and individual harms that directly impact a person as an individual. Current approaches generally overlook upstream collective and societal harms associated with the development of systems, such as (...)
- Health professions students’ perceptions of artificial intelligence and its integration to health professions education and healthcare: a thematic analysis.Ejercito Mangawa Balay-Odao, Dinara Omirzakova, Srinivasa Rao Bolla, Joseph U. Almazan & Jonas Preposi Cruz - forthcoming - AI and Society:1-11.Artificial intelligence (AI) is being tightly integrated into healthcare today. Even though AI is being utilized in healthcare, its application in clinical settings and health professions education is still controversial. The study described the perceptions of AI and its integration into health professions education and healthcare among health professions students. This descriptive phenomenological study analyzed the data from a purposive sample of 33 health professions students at a university in Kazakhstan using the thematic approach. Data collection was conducted from March (...)
- Artificial intelligence and human autonomy: the case of driving automation.Fabio Fossa - 2024 - AI and Society:1-12.The present paper aims at contributing to the ethical debate on the impacts of artificial intelligence (AI) systems on human autonomy. More specifically, it intends to offer a clearer understanding of the design challenges to the effort of aligning driving automation technologies to this ethical value. After introducing the discussion on the ambiguous impacts that AI systems exert on human autonomy, the analysis zooms in on how the problem has been discussed in the literature on connected and automated vehicles (CAVs). (...)
- Deconstructing public participation in the governance of facial recognition technologies in Canada.Maurice Jones & Fenwick McKelvey - forthcoming - AI and Society:1-14.On February 13, 2020, the Toronto Police Services (TPS) issued a statement admitting that its members had used Clearview AI’s controversial facial recognition technology (FRT). The controversy sparked widespread outcry by the media, civil society, and community groups, and put pressure on policy-makers to address FRTs. Public consultations presented a key tool to contain the scandal in Toronto and across Canada. Drawing on media reports, policy documents, and expert interviews, we investigate four consultations held by the Toronto Police Services Board (...)
- The Hierarchical Correspondence View of Levels: A Case Study in Cognitive Science.Luke Kersten - forthcoming - Minds and Machines.There is a general conception of levels in philosophy which says that the world is arrayed into a hierarchy of levels and that there are different modes of analysis that correspond to each level of this hierarchy, what can be labelled the ‘Hierarchical Correspondence View of Levels” (or HCL). The trouble is that despite its considerable lineage and general status in philosophy of science and metaphysics the HCL has largely escaped analysis in specific domains of inquiry. The goal of this (...)
- Ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations.Kristina Astromskė, Eimantas Peičius & Paulius Astromskis - 2021 - AI and Society 36 (2):509-520.This paper inquiries into the complex issue of informed consent applying artificial intelligence in medical diagnostic consultations. The aim is to expose the main ethical and legal concerns of the New Health phenomenon, powered by intelligent machines. To achieve this objective, the first part of the paper analyzes ethical aspects of the alleged right to explanation, privacy, and informed consent, applying artificial intelligence in medical diagnostic consultations. This analysis is followed by a legal analysis of the limits and requirements for (...)
- A proposal for the Dartmouth summer research project on artificial intelligence, august 31, 1955.M. John, L. M. Marvin, R. Nathaniel & E. S. Claude - 2006 - AI Magazine 27.
- Machine theology or artificial sainthood!Karamjit S. Gill - forthcoming - AI and Society:1-3.
- Towards Transnational Fairness in Machine Learning: A Case Study in Disaster Response Systems.Cem Kozcuer, Anne Mollen & Felix Bießmann - 2024 - Minds and Machines 34 (2):1-26.Research on fairness in machine learning (ML) has been largely focusing on individual and group fairness. With the adoption of ML-based technologies as assistive technology in complex societal transformations or crisis situations on a global scale these existing definitions fail to account for algorithmic fairness transnationally. We propose to complement existing perspectives on algorithmic fairness with a notion of transnational algorithmic fairness and take first steps towards an analytical framework. We exemplify the relevance of a transnational fairness assessment in a (...)
- Unite the study of AI in government: With a shared language and typology.Vincent J. Straub & Jonathan Bright - forthcoming - AI and Society:1-2.
- AI at work: understanding its uses and consequences on work activities and organization in radiology.Tamari Gamkrelidze, Moustafa Zouinar & Flore Barcellini - forthcoming - AI and Society:1-19.The progressive dissemination of artificial intelligence (AI) systems in work settings raises numerous questions and concerns regarding their consequences, whether positive or negative, on work activities and organizations. This paper presents an empirical study that was designed to identify and analyze these consequences in radiology. This study focuses on two AI systems: a voice recognition dictation system for radiological reports and a system for detecting fractures on X-rays images. Based on a qualitative analysis of field observations of work activities and (...)
- Embracing The New Natural: An Evolutionary Approach to Technological Singularity in the Age of A.I.J. Barratt - manuscriptThis paper explores the relationship between technological and human intelligence through ‘The New Natural’, a term which at once accepts the nature of technological intelligence as real instead of forever ‘artificial’. It supports an evolutionary, reciprocal relationship between humans and technology that culminates in technological singularity and rejects the primacy of human perception known to popular human access theories, before seriously considering the ‘decentered’ implications of posthuman access. In conversation with western-centric sci-fi film of the late twentieth century, then, this (...)
- A Review of Gulson, Sellar, and Webb’s Algorithms of Education.Daniel Shussett - 2023 - Social Epistmology Review and Reply Collective 12 (5):8-13.A review of Gulson, Sellar, and Webb’s "Algorithms of Education: How Datafication and Artificial Intelligence Shape Policy" (2022) published on the Social Epistemology Reply and Review Collective.
- AI Within Online Discussions: Rational, Civil, Privileged?Jonas Aaron Carstens & Dennis Friess - 2024 - Minds and Machines 34 (2):1-25.While early optimists have seen online discussions as potential spaces for deliberation, the reality of many online spaces is characterized by incivility and irrationality. Increasingly, AI tools are considered as a solution to foster deliberative discourse. Against the backdrop of previous research, we show that AI tools for online discussions heavily focus on the deliberative norms of rationality and civility. In the operationalization of those norms for AI tools, the complex deliberative dimensions are simplified, and the focus lies on the (...)
- The work of art in the age of generative AI: aura, liberation, and democratization.Sungjin Park - forthcoming - AI and Society:1-10.This paper investigates the transformative influence of generative AI on the arts, connecting it with Walter Benjamin's insights regarding the aura of art in the mechanical reproduction era. It scrutinizes how generative AI not only redefines art's traditional aura but also introduces a dynamic interplay between technological liberation and dependency. The analysis extends to the democratization of artistic expression and its broader societal impacts, highlighting a shift in art creation, perception, and interpretation in the digital age. This research encapsulates the (...)
- 2020 IEEE International Symposium on Circuits and Systems (ISCAS).Hao Zhan, Dan Wan & Zhiwei Huang (eds.) - 2020 - Seville, Spain: IEEE.Remove from this listExport citation Bookmark
- LINKs: The Art of Linking, an Annual Transdisciplinary Review, Special Edition 1, Unconventional Computing.Nancy Salay (ed.) - 2020Remove from this listExport citation Bookmark
- GPT-4-Trinis: assessing GPT-4’s communicative competence in the English-speaking majority world.Samantha Jackson, Barend Beekhuizen, Zhao Zhao & Rhonda McEwen - forthcoming - AI and Society:1-17.Biases and misunderstanding stemming from pre-training in Generative Pre-Trained Transformers are more likely for users of underrepresented English varieties, since the training dataset favors dominant Englishes (e.g., American English). We investigate (potential) bias in GPT-4 when it interacts with Trinidadian English Creole (TEC), a non-hegemonic English variety that partially overlaps with standardized English (SE) but still contains distinctive characteristics. (1) Comparable responses: we asked GPT-4 18 questions in TEC and SE and compared the content and detail of the responses. (2) (...)
- The case for global governance of AI: arguments, counter-arguments, and challenges ahead.Mark Coeckelbergh - forthcoming - AI and Society:1-4.It is increasingly recognized that as artificial intelligence becomes more powerful and pervasive in society and creates risks and ethical issues that cross borders, a global approach is needed for the governance of these risks. But why, exactly, do we need this and what does that mean? In this Open Forum paper, author argues for global governance of AI for moral reasons but also outlines the governance challenges that this project raises.
- Value preference profiles and ethical compliance quantification: a new approach for ethics by design in technology-assisted dementia care.Eike Buhr, Johannes Welsch & M. Salman Shaukat - forthcoming - AI and Society:1-17.Monitoring and assistive technologies (MATs) are being used more frequently in healthcare. A central ethical concern is the compatibility of these systems with the moral preferences of their users—an issue especially relevant to participatory approaches within the ethics-by-design debate. However, users’ incapacity to communicate preferences or to participate in design processes, e.g., due to dementia, presents a hurdle for participatory ethics-by-design approaches. In this paper, we explore the question of how the value preferences of users in the field of dementia (...)
- Balancing AI and academic integrity: what are the positions of academic publishers and universities?Bashar Haruna Gulumbe, Shuaibu Muhammad Audu & Abubakar Muhammad Hashim - forthcoming - AI and Society:1-10.This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...)
- An elemental ethics for artificial intelligence: water as resistance within AI’s value chain.Sebastián Lehuedé - forthcoming - AI and Society:1-14.Research and activism have increasingly denounced the problematic environmental record of the infrastructure and value chain underpinning artificial intelligence (AI). Water-intensive data centres, polluting mineral extraction and e-waste dumping are incontrovertibly part of AI’s footprint. In this article, I turn to areas affected by AI-fuelled environmental harm and identify an ethics of resistance emerging from local activists, which I term ‘elemental ethics’. Elemental ethics interrogates the AI value chain’s problematic relationship with the elements that make up the world, critiques the (...)
- Towards a Benchmark for Scientific Understanding in Humans and Machines.Kristian Gonzalez Barman, Sascha Caron, Tom Claassen & Henk De Regt - 2024 - Minds and Machines 34 (1):1-16.Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized (...)
- We are Building Gods: AI as the Anthropomorphised Authority of the Past.Carl Öhman - 2024 - Minds and Machines 34 (1):1-18.This article argues that large language models (LLMs) should be interpreted as a form of gods. In a theological sense, a god is an immortal being that exists beyond time and space. This is clearly nothing like LLMs. In an anthropological sense, however, a god is rather defined as the personified authority of a group through time—a conceptual tool that molds a collective of ancestors into a unified agent or voice. This is exactly what LLMs are. They are products of (...)
- The Man Behind the Curtain: Appropriating Fairness in AI.Marcin Korecki, Guillaume Köstner, Emanuele Martinelli & Cesare Carissimo - 2024 - Minds and Machines 34 (1):1-30.Our goal in this paper is to establish a set of criteria for understanding the meaning and sources of attributing (un)fairness to AI algorithms. To do so, we first establish that (un)fairness, like other normative notions, can be understood in a proper primary sense and in secondary senses derived by analogy. We argue that AI algorithms cannot be said to be (un)fair in the proper sense due to a set of criteria related to normativity and agency. However, we demonstrate how (...)
- Anthropomorphising Machines and Computerising Minds: The Crosswiring of Languages between Artificial Intelligence and Brain & Cognitive Sciences.Luciano Floridi & Anna C. Nobre - 2024 - Minds and Machines 34 (1):1-9.The article discusses the process of “conceptual borrowing”, according to which, when a new discipline emerges, it develops its technical vocabulary also by appropriating terms from other neighbouring disciplines. The phenomenon is likened to Carl Schmitt’s observation that modern political concepts have theological roots. The authors argue that, through extensive conceptual borrowing, AI has ended up describing computers anthropomorphically, as computational brains with psychological properties, while brain and cognitive sciences have ended up describing brains and minds computationally and informationally, as (...)
- Philosophical Lessons for Emotion Recognition Technology.Rosalie Waelen - 2024 - Minds and Machines 34 (1):1-13.Emotion recognition technology uses artificial intelligence to make inferences about a person’s emotions, on the basis of their facial expressions, body language, tone of voice, or other types of input. Underlying such technology are a variety of assumptions about the manifestation, nature, and value of emotions. To assure the quality and desirability of emotion recognition technology, it is important to critically assess the assumptions embedded in the technology. Within philosophy, there is a long tradition of epistemological, ontological, phenomenological, and ethical (...)
| 1 — 50 / 15226 |
PhilPapers logo by Andrea Andrews and Meghan Driscoll.
This site uses cookies and Google Analytics (see our terms & conditions for details regarding the privacy implications). Use of this site is subject to terms & conditions.
All rights reserved by The PhilPapers Foundation
Server: philpapers-web-5ff6c685cb-rv6xt uwo