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.
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  1. Machine learning and human learning: a socio-cultural and -material perspective on their relationship and the implications for researching working and learning.David Guile & Jelena Popov - forthcoming - AI and Society:1-14.
    The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new way to investigate the human + machine assistive assemblages emerging in professional work (e.g. medicine, architecture, design and engineering). Its starting point is Hutchins’s (1995a) concept of ‘distributed cognition’ and his argument that his concept of ‘cultural ecosystems’ constitutes a unit of analysis to investigate collective human + machine working and learning (Hutchins, Philos Psychol 27:39–49, 2013). It argues that: (...)
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  2. Bringing older people’s perspectives on consumer socially assistive robots into debates about the future of privacy protection and AI governance.Andrea Slane & Isabel Pedersen - forthcoming - AI and Society:1-20.
    A growing number of consumer technology companies are aiming to convince older people that humanoid robots make helpful tools to support aging-in-place. As hybrid devices, socially assistive robots (SARs) are situated between health monitoring tools, familiar digital assistants, security aids, and more advanced AI-powered devices. Consequently, they implicate older people’s privacy in complex ways. Such devices are marketed to perform functions common to smart speakers (e.g., Amazon Echo) and smart home platforms (e.g., Google Home), while other functions are more specific (...)
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  3. On prediction-modelers and decision-makers: why fairness requires more than a fair prediction model.Teresa Scantamburlo, Joachim Baumann & Christoph Heitz - forthcoming - AI and Society:1-17.
    An implicit ambiguity in the field of prediction-based decision-making concerns the relation between the concepts of prediction and decision. Much of the literature in the field tends to blur the boundaries between the two concepts and often simply refers to ‘fair prediction’. In this paper, we point out that a differentiation of these concepts is helpful when trying to implement algorithmic fairness. Even if fairness properties are related to the features of the used prediction model, what is more properly called (...)
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  4. Generative AI and human–robot interaction: implications and future agenda for business, society and ethics.Bojan Obrenovic, Xiao Gu, Guoyu Wang, Danijela Godinic & Ilimdorjon Jakhongirov - forthcoming - AI and Society:1-14.
    The revolution of artificial intelligence (AI), particularly generative AI, and its implications for human–robot interaction (HRI) opened up the debate on crucial regulatory, business, societal, and ethical considerations. This paper explores essential issues from the anthropomorphic perspective, examining the complex interplay between humans and AI models in societal and corporate contexts. We provided a comprehensive review of existing literature on HRI, with a special emphasis on the impact of generative models such as ChatGPT. The scientometric study posits that due to (...)
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  5. Trust, artificial intelligence and software practitioners: an interdisciplinary agenda.Sarah Pink, Emma Quilty, John Grundy & Rashina Hoda - forthcoming - AI and Society:1-14.
    Trust and trustworthiness are central concepts in contemporary discussions about the ethics of and qualities associated with artificial intelligence (AI) and the relationships between people, organisations and AI. In this article we develop an interdisciplinary approach, using socio-technical software engineering and design anthropological approaches, to investigate how trust and trustworthiness concepts are articulated and performed by AI software practitioners. We examine how trust and trustworthiness are defined in relation to AI across these disciplines, and investigate how AI, trust and trustworthiness (...)
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  6. Lessons from the California Gold Rush of 1849: prudence and care before advancing generative AI initiatives within your enterprise.Anthony Chambers & Nate Lewis - forthcoming - AI and Society:1-2.
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  7. Leveraging the potential of artificial intelligence (AI) in exploring the interplay among tax revenue, institutional quality, and economic growth in the G-7 countries.Charles Shaaba Saba & Nara Monkam - forthcoming - AI and Society:1-23.
    Due to G-7 countries' commitment to sustaining United Nations Sustainable Development Goal 8, which focuses on sustainable economic growth, there is a need to investigate the impact of tax revenue and institutional quality on economic growth, considering the role of artificial intelligence (AI) in the G-7 countries from 2012 to 2022. Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL) technique is used to analyze the data. The study's findings indicate a long-run equilibrium relationship among the variables under examination. The causality results can (...)
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  8. Five premises to understand human–computer interactions as AI is changing the world.Manh-Tung Ho & Quan-Hoang Vuong - forthcoming - AI and Society:1-2.
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  9. How far should we allow machines to further externalize human internal expression?Chenjun Wang & Naren Chitty - forthcoming - AI and Society:1-3.
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  10. Experiment on teaching visually impaired and blind children using a mobile electronic alphabetic braille trainer.Aliya Kintonova, Galimzhan Gabdreshov, Timur Yensebaev, Rizvangul Sadykova, Nurbek Yensebayev, Sultan Kulbasov & Daulet Magzymov - forthcoming - AI and Society:1-16.
    The article considers a pressing problem in the field of inclusive education: creating a comfortable learning environment for the effective education of children with special needs. In this article, a mobile electronic alphabet Braille simulator is an element of the learning environment for children with special needs. The article describes an experiment on teaching visually impaired and blind children using a mobile electronic Braille alphabet simulator. The mobile electronic Braille alphabet trainer, based on new advanced technology, was developed by Kazakh (...)
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  11. On the need to develop nuanced measures assessing attitudes towards AI and AI literacy in representative large-scale samples.Christian Montag, Preslav Nakov & Raian Ali - forthcoming - AI and Society:1-2.
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  12. The database construction of reality in the age of AI: the coming revolution in sociology?Mariusz Baranowski - forthcoming - AI and Society:1-3.
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  13. Artificial intelligence and identity: the rise of the statistical individual.Jens Christian Bjerring & Jacob Busch - forthcoming - AI and Society:1-13.
    Algorithms are used across a wide range of societal sectors such as banking, administration, and healthcare to make predictions that impact on our lives. While the predictions can be incredibly accurate about our present and future behavior, there is an important question about how these algorithms in fact represent human identity. In this paper, we explore this question and argue that machine learning algorithms represent human identity in terms of what we shall call the statistical individual. This statisticalized representation of (...)
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  14. Agent-Based Computational Economics: Overview and Brief History.Leigh Tesfatsion - 2023 - In Ragupathy Venkatachalam (ed.), Artificial Intelligence, Learning, and Computation in Economics and Finance. Cham: Springer. pp. 41-58.
    Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific modeling principles. (...)
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  15. Hybrid societies - Living with Social Robots.Bisconti Piercosma - 2024 - Routledge.
    This book explores how social robots and synthetic social agents will change our social systems and intersubjective relationships. It is obvious that technology influences societies. But how, and under what conditions do these changes occur? This book provides a theoretical foundation for the social implications of artificial intelligence (AI) and robotics. It starts from philosophy of technology, with a focus on social robotics, to systematically explore the concept of socio- technical change. It addresses two main questions: To what extent will (...)
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  16. Correction to: Emotional AI and the future of wellbeing in the post-pandemic workplace.Peter Mantello & Manh-Tung Ho - forthcoming - AI and Society:1-1.
  17. What to consider before incorporating generative AI into schools?Xiaofan Liu & Baichang Zhong - forthcoming - AI and Society:1-3.
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  18. The role of collective agreements in times of uncertain AI governance: lessons from the Hollywood scriptwriters’ agreement.Aida Ponce del Castillo - forthcoming - AI and Society:1-2.
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  19. Blind search and flexible product visions: the sociotechnical shaping of generative music engines.Oliver Bown - forthcoming - AI and Society:1-19.
    Amidst the surge in AI-oriented commercial ventures, music is a site of intensive efforts to innovate. A number of companies are seeking to apply AI to music production and consumption, and amongst them several are seeking to reinvent the music listening experience as adaptive, interactive, functional and infinitely generative. These are bold objectives, having no clear roadmap for what designs, technologies and use cases, if any, will be successful. Thus each company relies on speculative product visions. Through four case studies (...)
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  20. Poisoning an already poisoned well.Angela Misri - forthcoming - AI and Society:1-2.
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  21. Beyond Consciousness in Large Language Models: An Investigation into the Existence of a "Soul" in Self-Aware Artificial Intelligences.David Côrtes Cavalcante - 2024 - Https://Philpapers.Org/Rec/Crtbci. Translated by Côrtes Cavalcante David.
    Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a “soul”? This inquiry (...)
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  22. Cuteness in avatar design: a cross-cultural study on the influence of baby schema features and other visual characteristics.Shiri Lieber-Milo, Yair Amichai-Hamburger, Tomoko Yonezawa & Kazunori Sugiura - forthcoming - AI and Society:1-11.
    The concept of cuteness, which can evoke positive emotions in people, is an essential aspect to consider in artificial intelligence design. This study aimed to investigate whether the use of baby schema designed avatars in computer-mediated communication elicits higher positive attitudes than neutral avatars and whether the ethnicity of the cute avatars influences individuals' perceived level of cuteness. 485 participants from Israel and Japan viewed six avatar images, including three baby schema avatars of different visual characteristics and ethnicities (Caucasian, Asian, (...)
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  23. Authorship and ChatGPT: a Conservative View.René van Woudenberg, Chris Ranalli & Daniel Bracker - 2024 - Philosophy and Technology 37 (1):1-26.
    Is ChatGPT an author? Given its capacity to generate something that reads like human-written text in response to prompts, it might seem natural to ascribe authorship to ChatGPT. However, we argue that ChatGPT is not an author. ChatGPT fails to meet the criteria of authorship because it lacks the ability to perform illocutionary speech acts such as promising or asserting, lacks the fitting mental states like knowledge, belief, or intention, and cannot take responsibility for the texts it produces. Three perspectives (...)
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  24. Narrativity and responsible and transparent ai practices.Paul Hayes & Noel Fitzpatrick - forthcoming - AI and Society:1-21.
    This paper builds upon recent work in narrative theory and the philosophy of technology by examining the place of transparency and responsibility in discussions of AI, and what some of the implications of this might be for thinking ethically about AI and especially AI practices, that is, the structured social activities implicating and defining what AI is. In this paper, we aim to show how pursuing a narrative understanding of technology and AI can support knowledge of process and practice through (...)
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  25. Public perceptions of the use of artificial intelligence in Defence: a qualitative exploration.Lee Hadlington, Maria Karanika-Murray, Jane Slater, Jens Binder, Sarah Gardner & Sarah Knight - forthcoming - AI and Society:1-14.
    There are a wide variety of potential applications of artificial intelligence (AI) in Defence settings, ranging from the use of autonomous drones to logistical support. However, limited research exists exploring how the public view these, especially in view of the value of public attitudes for influencing policy-making. An accurate understanding of the public’s perceptions is essential for crafting informed policy, developing responsible governance, and building responsive assurance relating to the development and use of AI in military settings. This study is (...)
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  26. Surveying Judges about artificial intelligence: profession, judicial adjudication, and legal principles.Andreia Martinho - forthcoming - AI and Society:1-16.
    Artificial Intelligence (AI) is set to bring changes to legal systems. These technologies may have positive practical implications when it comes to access, efficiency, and accuracy in Justice. However, there are still many uncertainties and challenges associated with the implementation of AI in the legal space. In this research, we surveyed Judges on critical challenges related to the Judging Profession in the AI paradigm; Automated Adjudication; and Legal Principles. Our results suggest that (i) Judges are hesitant about changes in their (...)
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  27. Augmenting Morality through Ethics Education: the ACTWith model.Jeffrey White - forthcoming - AI and Society.
    Recently in this journal, Jessica Morley and colleagues (AI & SOC 2023 38:411–423) review AI ethics and education, suggesting that a cultural shift is necessary in order to prepare students for their responsibilities in developing technology infrastructure that should shape ways of life for many generations. Current AI ethics guidelines are abstract and difficult to implement as practical moral concerns proliferate. They call for improvements in ethics course design, focusing on real-world cases and perspective-taking tools to immerse students in challenging (...)
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  28. Nietzsche's Three Metamorphoses and Their Relevance to Artificial Intelligence Development.Beni Beeri Issembert - unknown
    This opinion paper delves into the philosophical underpinnings and implications of artificial intelligence (AI) development through the lens of Friedrich Nietzsche's "Three Metamorphoses," exploring the stages from the camel, through the lion, to the envisioned child phase within the AI context. Amidst growing concerns over AI's ethical ramifications, including job displacement, biased decision-making, and misuse potential, this analysis seeks to provide a comprehensive framework for understanding AI's evolution and its socio-technical effects on society. The discourse begins by contextualizing AI within (...)
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  29. What makes full artificial agents morally different.Erez Firt - forthcoming - AI and Society:1-10.
    In the research field of machine ethics, we commonly categorize artificial moral agents into four types, with the most advanced referred to as a full ethical agent, or sometimes a full-blown Artificial Moral Agent (AMA). This type has three main characteristics: autonomy, moral understanding and a certain level of consciousness, including intentional mental states, moral emotions such as compassion, the ability to praise and condemn, and a conscience. This paper aims to discuss various aspects of full-blown AMAs and presents the (...)
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  30. Negotiating the authenticity of AI: how the discourse on AI rejects human indeterminacy.Siri Beerends & Ciano Aydin - forthcoming - AI and Society:1-14.
    In this paper, we demonstrate how the language and reasonings that academics, developers, consumers, marketers, and journalists deploy to accept or reject AI as authentic intelligence has far-reaching bearing on how we understand our human intelligence and condition. The discourse on AI is part of what we call the “authenticity negotiation process” through which AI’s “intelligence” is given a particular meaning and value. This has implications for scientific theory, research directions, ethical guidelines, design principles, funding, media attention, and the way (...)
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  31. User-centered AI-based voice-assistants for safe mobility of older people in urban context.Bokolo Anthony Jnr - forthcoming - AI and Society:1-24.
    Voice-assistants are becoming increasingly popular and can be deployed to offers a low-cost tool that can support and potentially reduce falls, injuries, and accidents faced by older people within the age of 65 and older. But, irrespective of the mobility and walkability challenges faced by the aging population, studies that employed Artificial Intelligence (AI)-based voice-assistants to reduce risks faced by older people when they use public transportation and walk in built environment are scarce. This is because the development of AI-based (...)
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  32. Freedom, AI and God: why being dominated by a friendly super-AI might not be so bad.Morgan Luck - forthcoming - AI and Society:1-8.
    One response to the existential threat posed by a super-intelligent AI is to design it to be friendly to us. Some have argued that even if this were possible, the resulting AI would treat us as we do our pets. Sparrow (AI & Soc. https://doi.org/10.1007/s00146-023-01698-x, 2023) argues that this would be a bad outcome, for such an AI would dominate us—resulting in our freedom being diminished (Pettit in Just freedom: A moral compass for a complex world. WW Norton & Company, (...)
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  33. Challenges of responsible AI in practice: scoping review and recommended actions.Malak Sadek, Emma Kallina, Thomas Bohné, Céline Mougenot, Rafael A. Calvo & Stephen Cave - forthcoming - AI and Society:1-17.
    Responsible AI (RAI) guidelines aim to ensure that AI systems respect democratic values. While a step in the right direction, they currently fail to impact practice. Our work discusses reasons for this lack of impact and clusters them into five areas: (1) the abstract nature of RAI guidelines, (2) the problem of selecting and reconciling values, (3) the difficulty of operationalising RAI success metrics, (4) the fragmentation of the AI pipeline, and (5) the lack of internal advocacy and accountability. Afterwards, (...)
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  34. Ethical governance of artificial intelligence for defence: normative tradeoffs for principle to practice guidance.Alexander Blanchard, Christopher Thomas & Mariarosaria Taddeo - forthcoming - AI and Society:1-14.
    The rapid diffusion of artificial intelligence (AI) technologies in the defence domain raises challenges for the ethical governance of these systems. A recent shift from the what to the how of AI ethics sees a nascent body of literature published by defence organisations focussed on guidance to implement AI ethics principles. These efforts have neglected a crucial intermediate step between principles and guidance concerning the elicitation of ethical requirements for specifying the guidance. In this article, we outline the key normative (...)
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  35. What Do We Teach to Engineering Students: Embedded Ethics, Morality, and Politics.Avigail Ferdman & Emanuele Ratti - 2024 - Science and Engineering Ethics 30 (1):1-26.
    In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towards addressing ethics at the societal level. In this article, we propose a tripartite framework to overcome these (...)
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  36. Digital sovereignty, digital infrastructures, and quantum horizons.Geoff Gordon - 2024 - AI and Society 39 (1):125-137.
    This article holds that governmental investments in quantum technologies speak to the imaginable futures of digital sovereignty and digital infrastructures, two major areas of change driven by related technologies like AI and Big Data, among other things, in international law today. Under intense development today for future interpolation into digital systems that they may alter, quantum technologies occupy a sort of liminal position, rooted in existing assemblages of computational technologies while pointing to new horizons for them. The possibilities they raise (...)
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  37. Just accountability structures – a way to promote the safe use of automated decision-making in the public sector.Hanne Hirvonen - 2024 - AI and Society 39 (1):155-167.
    The growing use of automated decision-making (ADM) systems in the public sector and the need to control these has raised many legal questions in academic research and in policymaking. One of the timely means of legal control is accountability, which traditionally includes the ability to impose sanctions on the violator as one dimension. Even though many risks regarding the use of ADM have been noted and there is a common will to promote the safety of these systems, the relevance of (...)
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  38. Safety by simulation: theorizing the future of robot regulation.Mika Viljanen - 2024 - AI and Society 39 (1):139-154.
    Mobility robots may soon be among us, triggering a need for safety regulation. Robot safety regulation, however, remains underexplored, with only a few articles analyzing what regulatory approaches could be feasible. This article offers an account of the available regulatory strategies and attempts to theorize the effects of simulation-based safety regulation. The article first discusses the distinctive features of mobility robots as regulatory targets and argues that emergent behavior constitutes the key regulatory concern in designing robot safety regulation regimes. In (...)
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  39. Body stakes: an existential ethics of care in living with biometrics and AI.Amanda Lagerkvist, Matilda Tudor, Jacek Smolicki, Charles M. Ess, Jenny Eriksson Lundström & Maria Rogg - 2024 - AI and Society 39 (1):169-181.
    This article discusses the key existential stakes of implementing biometrics in human lifeworlds. In this pursuit, we offer a problematization and reinvention of central values often taken for granted within the “ethical turn” of AI development and discourse, such as autonomy, agency, privacy and integrity, as we revisit basic questions about what it means to be human and embodied. Within a framework of existential media studies, we introduce an existential ethics of care—through a conversation between existentialism, virtue ethics, a feminist (...)
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  40. “Please understand we cannot provide further information”: evaluating content and transparency of GDPR-mandated AI disclosures.Alexander J. Wulf & Ognyan Seizov - 2024 - AI and Society 39 (1):235-256.
    The General Data Protection Regulation (GDPR) of the EU confirms the protection of personal data as a fundamental human right and affords data subjects more control over the way their personal information is processed, shared, and analyzed. However, where data are processed by artificial intelligence (AI) algorithms, asserting control and providing adequate explanations is a challenge. Due to massive increases in computing power and big data processing, modern AI algorithms are too complex and opaque to be understood by most data (...)
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  41. Machine agency and representation.Beba Cibralic & James Mattingly - 2024 - AI and Society 39 (1):345-352.
    Theories of action tend to require agents to have mental representations. A common trope in discussions of artificial intelligence (AI) is that they do not, and so cannot be agents. Properly understood there may be something to the requirement, but the trope is badly misguided. Here we provide an account of representation for AI that is sufficient to underwrite attributions to these systems of ownership, action, and responsibility. Existing accounts of mental representation tend to be too demanding and unparsimonious. We (...)
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  42. Legal and ethical aspects of deploying artificial intelligence in climate-smart agriculture.Mahatab Uddin, Ataharul Chowdhury & Muhammad Ashad Kabir - 2024 - AI and Society 39 (1):221-234.
    This study aims to identify artificial intelligence (AI) technologies that are applied in climate-smart agricultural practices and address ethical concerns of deploying those technologies from legal perspectives. As climate-smart agricultural AI, the study considers those AI-based technologies that are used for precision agriculture, monitoring peat lands, deforestation tracking, and improved forest management. The study utilized a systematic literature review approach to identify and analyze AI technologies employed in climate-smart agriculture and associated ethical and legal concerns. The study findings indicate several (...)
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  43. Justificatory explanations in machine learning: for increased transparency through documenting how key concepts drive and underpin design and engineering decisions.David Casacuberta, Ariel Guersenzvaig & Cristian Moyano-Fernández - 2024 - AI and Society 39 (1):279-293.
    Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...)
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  44. What about investors? ESG analyses as tools for ethics-based AI auditing.Matti Minkkinen, Anniina Niukkanen & Matti Mäntymäki - 2024 - AI and Society 39 (1):329-343.
    Artificial intelligence (AI) governance and auditing promise to bridge the gap between AI ethics principles and the responsible use of AI systems, but they require assessment mechanisms and metrics. Effective AI governance is not only about legal compliance; organizations can strive to go beyond legal requirements by proactively considering the risks inherent in their AI systems. In the past decade, investors have become increasingly active in advancing corporate social responsibility and sustainability practices. Including nonfinancial information related to environmental, social, and (...)
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  45. Telepresence as a social-historical mode of being. ChatGPT and the ontological dimensions of digital representation.Alexandros Schismenos - 2024 - Lessico di Etica Pubblica (1-2/2023):37-52.
    Nel 1956, in piena guerra fredda, una conferenza di scienziati al Dartmouth College negli Stati Uniti annunciò il lancio di un audace progetto scientifico, l’Intelligenza Artificiale (I.A.). Dopo l’iniziale fallimento degli sforzi della “Hard AI” di produrre un’intelligenza simile a quella umana, alla fine del XX secolo è emerso il movimento della “Soft AI”. Invece di essere orientato a imitare il comportamento umano in relazione a compiti specifici, ha preferito cercare modi alternativi di eseguire i compiti basati sulle particolari funzioni (...)
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  46. Art histories from nowhere: on the coloniality of experiments in art and artificial intelligence.Mashinka Firunts Hakopian - 2024 - AI and Society 39 (1):29-41.
    This paper considers recent experiments in art and artificial intelligence that crystallize around training algorithms to generate artworks based on datasets derived from the Western art historical canon. Over the last decade, a shift towards the rejection of canonicity has begun to take shape in art historical discourse. At the same time, algorithmically enabled practices in the US and Europe have emerged that entrench the Western canon as a locus and guarantor of aesthetic value. Operating within the epistemic framework of (...)
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  47. Challenges in enabling user control over algorithm-based services.Pascal D. König - 2024 - AI and Society 39 (1):195-205.
    Algorithmic systems that provide services to people by supporting or replacing human decision-making promise greater convenience in various areas. The opacity of these applications, however, means that it is not clear how much they truly serve their users. A promising way to address the issue of possible undesired biases consists in giving users control by letting them configure a system and aligning its performance with users’ own preferences. However, as the present paper argues, this form of control over an algorithmic (...)
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  48. Sculpting the social algorithm for radical futurity.Anisa Matthews - 2024 - AI and Society 39 (1):75-86.
    Social media has revolutionized the way information is distributed throughout society, as folks continue to rely entirely on these apps for information on current events, health protocols, and socio-political discussions. However, these containers of knowledge do not appear in the same shape for every user; Algorithms, informed by capitalist agendas, determine what information sifts through its networks and to whom. Data scientists, researchers, and activists have dissected the hidden mechanics fueling these popular platforms, inciting critical conversations around the harmful biases (...)
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  49. On freedom and slavery when using a smart device.Anna Gorbacheva & Andrey Pestunov - 2024 - AI and Society 39 (1):397-398.
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  50. The Turing test is a joke.Attay Kremer - 2024 - AI and Society 39 (1):399-401.
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