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. Link Uncertainty, Implementation, and ML Opacity: A Reply to Tamir and Shech.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 341-345.
    This chapter responds to Michael Tamir and Elay Shech’s chapter “Understanding from Deep Learning Models in Context.”.
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  2. Artificial Intelligence Systems, Responsibility and Agential Self-Awareness.Lydia Farina - 2022 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2021. Berlin, Germany: pp. 15-25.
    This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing on a specific account (...)
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  3. Models, Algorithms, and the Subjects of Transparency.Hajo Greif - 2022 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2021. Berlin: Springer. pp. 27-37.
    Concerns over epistemic opacity abound in contemporary debates on Artificial Intelligence (AI). However, it is not always clear to what extent these concerns refer to the same set of problems. We can observe, first, that the terms 'transparency' and 'opacity' are used either in reference to the computational elements of an AI model or to the models to which they pertain. Second, opacity and transparency might either be understood to refer to the properties of AI systems or to the epistemic (...)
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  4. Autonomous Weapons Systems and the Necessity of Interpretation: What Heidegger Can Tell Us About Automated Warfare.Kieran M. Brayford - forthcoming - AI and Society:1-9.
    Despite resistance from various societal actors, the development and deployment of lethal autonomous weaponry to warzones is perhaps likely, considering the perceived operational and ethical advantage such weapons are purported to bring. In this paper, it is argued that the deployment of truly autonomous weaponry presents an ethical danger by calling into question the ability of such weapons to abide by the Laws of War. This is done by noting the resonances between battlefield target identification and the process of ontic-ontological (...)
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  5. Evidence-Based AI, Ethics and the Circular Economy of Knowledge.Caterina Berbenni-Rehm - forthcoming - AI and Society:1-7.
    Everything we do in life involves a connection with information, experience and know-how: together these represent the most valuable of intangible human assets encompassing our history, cultures and wisdom. However, the more easily new technologies gather information, the more we are confronted with our limited capacity to distinguish between what is essential, important or merely ‘nice-to-have’. This article presents the case study of a multilingual Knowledge Management System, the Business enabling e-Platform that gathers and protects tacit knowledge, as the key (...)
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  6. Coeckelbergh, Mark (2022). The Political Philosophy of AI, Polity Press, Cambridge, UK, ISBN-13: 978-1509548545.Joan Llorca Albareda - forthcoming - AI and Society:1-2.
  7. Human–Computer Interaction Tools with Gameful Design for Critical Thinking the Media Ecosystem: A Classification Framework.Elena Musi, Lorenzo Federico & Gianni Riotta - forthcoming - AI and Society:1-13.
    In response to the ever-increasing spread of online disinformation and misinformation, several human–computer interaction tools to enhance data literacy have been developed. Among them, many employ elements of gamification to increase user engagement and reach out to a broader audience. However, there are no systematic criteria to analyze their relevance and impact for building fake news resilience, partly due to the lack of a common understanding of data literacy. In this paper we put forward an operationalizable definition of data literacy (...)
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  8. Machine Learning: Can the Automatic Pilot Transcend the Toxic Fog?Karamjit S. Gill - forthcoming - AI and Society:1-4.
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  9. Gul A. Agha, Actors: A Model of Concurrent Computation in Distributed Systems[REVIEW]Varol Akman - 1990 - AI Magazine 11 (4):92-93.
    This is a review of Gul A. Agha’s Actors: A Model of Concurrent Computation in Distributed Systems (The MIT Press, Cambridge, MA, 1987), a part of the MIT Press Series in Artificial Intelligence, edited by Patrick Winston, Michael Brady, and Daniel Bobrow.
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  10. Representing Emotions in Terms of Object Directedness.Varol Akman & Hakime G. Unsal - 1994 - Department of Computer Engineering Technical Reports, Bilkent University.
    A logical formalization of emotions is considered to be tricky because they appear to have no strict types, reasons, and consequences. On the other hand, such a formalization is crucial for commonsense reasoning. Here, the so-called "object directedness" of emotions is studied by using Helen Nissenbaum's influential ideas.
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  11. From Pluralistic Normative Principles to Autonomous-Agent Rules.Beverley Townsend, Colin Paterson, T. T. Arvind, Gabriel Nemirovsky, Radu Calinescu, Ana Cavalcanti, Ibrahim Habli & Alan Thomas - 2022 - Minds and Machines 1:1-33.
    With recent advancements in systems engineering and artificial intelligence, autonomous agents are increasingly being called upon to execute tasks that have normative relevance. These are tasks that directly—and potentially adversely—affect human well-being and demand of the agent a degree of normative-sensitivity and -compliance. Such norms and normative principles are typically of a social, legal, ethical, empathetic, or cultural nature. Whereas norms of this type are often framed in the abstract, or as high-level principles, addressing normative concerns in concrete applications of (...)
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  12. Toward children-centric AI: a case for a growth model in children-AI interactions.Karolina La Fors - forthcoming - AI and Society:1-13.
    This article advocates for a hermeneutic model for children-AI interactions in which the desirable purpose of children’s interaction with artificial intelligence systems is children's growth. The article perceives AI systems with machine-learning components as having a recursive element when interacting with children. They can learn from an encounter with children and incorporate data from interaction, not only from prior programming. Given the purpose of growth and this recursive element of AI, the article argues for distinguishing the interpretation of bias within (...)
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  13. Meta’s Oversight Board: A Review and Critical Assessment.David Wong & Luciano Floridi - forthcoming - Minds and Machines:1-24.
    Since the announcement and establishment of the Oversight Board by the technology company Meta as an independent institution reviewing Facebook and Instagram’s content moderation decisions, the OB has been subjected to scholarly scrutiny ranging from praise to criticism. However, there is currently no overarching framework for understanding the OB’s various strengths and weaknesses. Consequently, this article analyses, organises, and supplements academic literature, news articles, and Meta and OB documents to understand the OB’s strengths and weaknesses and how it can be (...)
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  14. Tying the Knot with a Robot: Legal and Philosophical Foundations for Human–Artificial Intelligence Matrimony.Greg Yanke - 2021 - AI and Society 36 (2):417-427.
    Technological progress may eventually produce sophisticated robots with human-like traits that result in humans forming meaningful relationships with them. Such relationships would likely lead to a demand for human–artificial intelligence matrimony. U.S. Supreme Court decisions that expanded the definition of marriage to include interracial and same-sex couples, as well as those that have not extended marriage to polygamous relationships, provide guidance regarding the criteria that human–AI would have to meet to successfully assert a right to marry. Ultimately, robots will have (...)
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  15. What Drives Bio-Art in the Twenty-First Century? Sources of Innovations and Cultural Implications in Bio-Art/Biodesign and Biotechnology.Alexander N. Melkozernov & Vibeke Sorensen - 2021 - AI and Society 36 (4):1313-1321.
    Bio-art epitomizes a coalescence of art and sciences. It is an emerging contemporary artistic practice that uses a wide range of traditional artistic media interwoven with new artistic media that are biological in nature. This includes molecules, genes, cells, tissues, organs, living organisms, ecological niches, landscapes and ecosystems. In addition, bio-art expands into conceptual art using biological processes such as growth, cell division, photosynthesis and concepts of the origin of life and evolution, explaining them as new artistic media. In this (...)
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  16. Philosophy and Theory of Artificial Intelligence 2021.Vincent C. Müller (ed.) - 2022 - Berlin: Springer.
    This book gathers contributions from the fourth edition of the Conference on "Philosophy and Theory of Artificial Intelligence" (PT-AI), held on 27-28th of September 2021 at Chalmers University of Technology, in Gothenburg, Sweden. It covers topics at the interface between philosophy, cognitive science, ethics and computing. It discusses advanced theories fostering the understanding of human cognition, human autonomy, dignity and morality, and the development of corresponding artificial cognitive structures, analyzing important aspects of the relationship between humans and AI systems, including (...)
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  17. Exploring children’s exposure to voice assistants and their ontological conceptualizations of life and technology.Janik Festerling, Iram Siraj & Lars-Erik Malmberg - forthcoming - AI and Society:1-28.
    Digital Voice Assistants have become a ubiquitous technology in today’s home and childhood environments. Inspired by original study on how children’s ontological conceptualizations of life and technology were systematically associated with their real-world exposure to robotic entities, the current study explored this association for children in their middle childhood and with different levels of DVA-exposure. We analyzed correlational survey data from 143 parent–child dyads who were recruited on ‘Amazon Mechanical Turk’. Children’s ontological conceptualization patterns of life and technology were measured (...)
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  18. A machine learning approach to recognize bias and discrimination in job advertisements.Richard Frissen, Kolawole John Adebayo & Rohan Nanda - forthcoming - AI and Society:1-14.
    In recent years, the work of organizations in the area of digitization has intensified significantly. This trend is also evident in the field of recruitment where job application tracking systems have been developed to allow job advertisements to be published online. However, recent studies have shown that recruiting in most organizations is not inclusive, being subject to human biases and prejudices. Most discrimination activities appear early but subtly in the hiring process, for instance, exclusive phrasing in job advertisement discourages qualified (...)
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  19. AI ethics with Chinese characteristics? Concerns and preferred solutions in Chinese academia.Junhua Zhu - forthcoming - AI and Society:1-14.
    Since Chinese scholars are playing an increasingly important role in shaping the national landscape of discussion on AI ethics, understanding their ethical concerns and preferred solutions is essential for global cooperation on governance of AI. This article, therefore, provides the first elaborated analysis on the discourse on AI ethics in Chinese academia, via a systematic literature review. This article has three main objectives. to identify the most discussed ethical issues of AI in Chinese academia and those being left out ; (...)
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  20. Can we design artificial persons without being manipulative?Maciej Musiał - forthcoming - AI and Society:1-10.
    If we could build artificial persons with a moral status comparable to this of a typical human being, how should we design those APs in the right way? This question has been addressed mainly in terms of designing APs devoted to being servants and debated in reference to their autonomy and the harm they might experience. Recently, it has been argued that even if developing AP servants would neither deprive them of autonomy nor cause any net harm, then developing such (...)
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  21. Social robots as partners?Paul Healy - forthcoming - AI and Society:1-8.
    Although social robots are achieving increasing prominence as companions and carers, their status as partners in an interactive relationship with humans remains unclear. The present paper explores this issue, first, by considering why social robots cannot truly qualify as “Thous”, that is, as surrogate human partners, as they are often assumed to be, and then by briefly considering why it will not do to construe them as mere machines, slaves, or pets, as others have contended. Having concluded that none of (...)
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  22. Subnational AI policy: shaping AI in a multi-level governance system.Laura Liebig, Licinia Güttel, Anna Jobin & Christian Katzenbach - forthcoming - AI and Society:1-14.
    The promises and risks of Artificial Intelligence permeate current policy statements and have attracted much attention by AI governance research. However, most analyses focus exclusively on AI policy on the national and international level, overlooking existing federal governance structures. This is surprising because AI is connected to many policy areas, where the competences are already distributed between the national and subnational level, such as research or economic policy. Addressing this gap, this paper argues that more attention should be dedicated to (...)
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  23. Katherine Crawford: Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence.Aale Luusua - forthcoming - AI and Society:1-3.
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  24. Is LaMDA sentient?Max Griffiths - forthcoming - AI and Society:1-2.
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  25. Why we need to be weary of emotional AI.Mantello Peter & Manh-Tung Ho - forthcoming - AI and Society:1-3.
  26. The QWERTY keyboard from the perspective of the Collingridge dilemma: lessons for co-construction of human-technology.Mahdi Kafaee, Elahe Daviran & Mostafa Taqavi - forthcoming - AI and Society:1-13.
    According to the Collingridge dilemma, technology is easy to control when its consequences are not yet manifest; once they appear, the technology is difficult to control. This article examines the development of keyboard layout design from the perspective of the Collingridge dilemma. For this purpose, unlike related studies that focus on a limited period of time, the history of keyboard development is explored from the invention of the typewriter and the QWERTY to brain–computer interfaces. Today, there is no mechanical problem (...)
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  27. Victim-blaming AIs.Hazel T. Biana & Rosallia Domingo - forthcoming - AI and Society:1-2.
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  28. Artificial virtuous agents in a multi-agent tragedy of the commons.Jakob Stenseke - forthcoming - AI and Society:1-18.
    Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents, it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the details of a (...)
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  29. Social trust and public digitalization.Kees van Kersbergen & Gert Tinggaard Svendsen - forthcoming - AI and Society:1-12.
    Modern democratic states are increasingly adopting new information and communication technologies to enhance the efficiency and quality of public administration, public policy and services. However, there is substantial variation in the extent to which countries are successful in pursuing such public digitalization. This paper zooms in on the role of social trust as a possible account for the observed empirical pattern in the range and scope of public digitalization across countries. Our argument is that high social trust makes it easier (...)
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  30. Drivers behind the public perception of artificial intelligence: insights from major Australian cities.Tan Yigitcanlar, Kenan Degirmenci & Tommi Inkinen - forthcoming - AI and Society:1-21.
    Artificial intelligence is not only disrupting industries and businesses, particularly the ones have fallen behind the adoption, but also significantly impacting public life as well. This calls for government authorities pay attention to public opinions and sentiments towards AI. Nonetheless, there is limited knowledge on what the drivers behind the public perception of AI are. Bridging this gap is the rationale of this paper. As the methodological approach, the study conducts an online public perception survey with the residents of Sydney, (...)
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  31. AI ageism: a critical roadmap for studying age discrimination and exclusion in digitalized societies.Justyna Stypinska - forthcoming - AI and Society:1-13.
    In the last few years, we have witnessed a surge in scholarly interest and scientific evidence of how algorithms can produce discriminatory outcomes, especially with regard to gender and race. However, the analysis of fairness and bias in AI, important for the debate of AI for social good, has paid insufficient attention to the category of age and older people. Ageing populations have been largely neglected during the turn to digitality and AI. In this article, the concept of AI ageism (...)
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  32. To Envy an Algorithm.Alison Duncan Kerr - 2022 - In Sara Protasi (ed.), The Moral Psychology of Envy. pp. 199-216.
  33. Public procurement of artificial intelligence systems: new risks and future proofing.Merve Hickok - forthcoming - AI and Society:1-15.
    Public entities around the world are increasingly deploying artificial intelligence and algorithmic decision-making systems to provide public services or to use their enforcement powers. The rationale for the public sector to use these systems is similar to private sector: increase efficiency and speed of transactions and lower the costs. However, public entities are first and foremost established to meet the needs of the members of society and protect the safety, fundamental rights, and wellbeing of those they serve. Currently AI systems (...)
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  34. Smart cities: reviewing the debate about their ethical implications.Marta Ziosi, Benjamin Hewitt, Prathm Juneja, Mariarosaria Taddeo & Luciano Floridi - forthcoming - AI and Society:1-16.
    This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and sustainability, (...)
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  35. Urban AI: understanding the emerging role of artificial intelligence in smart cities.Aale Luusua, Johanna Ylipulli, Marcus Foth & Alessandro Aurigi - forthcoming - AI and Society:1-6.
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  36. The cyclical ethical effects of using artificial intelligence in education.Edward Dieterle, Chris Dede & Michael Walker - forthcoming - AI and Society:1-11.
    Our synthetic review of the relevant and related literatures on the ethics and effects of using AI in education reveals five qualitatively distinct and interrelated divides associated with access, representation, algorithms, interpretations, and citizenship. We open our analysis by probing the ethical effects of algorithms and how teams of humans can plan for and mitigate bias when using AI tools and techniques to model and inform instructional decisions and predict learning outcomes. We then analyze the upstream divides that feed into (...)
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  37. Bowling alone in the autonomous vehicle: the ethics of well-being in the driverless car.Avigail Ferdman - forthcoming - AI and Society:1-13.
    There is a growing body of scholarship on the ethics of autonomous vehicles. Yet the ethical discourse has mostly been focusing on the behavior of the vehicle in accident scenarios. This paper offers a different ethical prism: the implications of the autonomous vehicle for human well-being. As such, it contributes to the growing discourse on the wider societal and moral implications of the autonomous vehicle. The paper is premised on the neo-Aristotelian approach which holds that as human beings, our well-being (...)
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  38. The paradox of the artificial intelligence system development process: the use case of corporate wellness programs using smart wearables.Alessandra Angelucci, Ziyue Li, Niya Stoimenova & Stefano Canali - forthcoming - AI and Society:1-11.
    Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This means that (...)
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  39. Florian Butollo and Sabine Nuss (Eds.) Marx and the Robots: Networked Production, AI, and Human Labour, London, UK: Pluto Press, 2022, 324 pp., $26.95 (Paperback), $99.00. [REVIEW]Yanling Zhu - forthcoming - AI and Society:1-3.
  40. Rules for Privately Owned Robots in Public Spaces.Seng W. Loke - forthcoming - AI and Society:1-2.
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  41. Bas de Boer, How Scientific Instruments Speak. Postphenomenology and Technological Mediations in Neuroscientific Practice. Lexington Books: The Rowman & Littlefield Publishing Group, Inc., 2020. 211 Pages. ISBN 978-1-7936-2784-1 and 978-1-7936-2785-8. [REVIEW]Jan Kyrre Berg Olsen Friis - forthcoming - AI and Society:1-3.
  42. Review of R. C. Pradhan (RCP)’s Mind, Meaning and World: A Transcendental Perspective, Singapore: Springer Nature Singapore Pte Ltd., 2019. [REVIEW]Rajakishore Nath - forthcoming - AI and Society:1-4.
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  43. Editorial: On Modes of Participation.Ioannis Bardakos, Dalila Honorato, Claudia Jacques, Claudia Westermann & Primavera de Filippi - 2021 - Technoetic Arts 19 (3):221-225.
    In nature validation for physiological and emotional bonding becomes a mode for supporting social connectivity. Similarly, in the blockchain ecosystem, cryptographic validation becomes the substrate for all interactions. In the dialogue between human and artificial intelligence (AI) agents, between the real and the virtual, one can distinguish threads of physical or mental entanglements allowing different modes of participation. One could even suggest that in all types of realities there exist frameworks that are to some extent equivalent and act as validation (...)
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  44. Using Deceased People’s Personal Data.Hiroshi Nakagawa & Akiko Orita - forthcoming - AI and Society:1-19.
    It is important to manage individuals’ personal data after their death to maintain their dignity or follow their wishes as much as possible. From this perspective, this report describes the real-world commercialization of immortal digital personalities, which gives eternal life to the deceased in a digital form. We identify the problems with the commercialization of deceased users’ images and personal data, which becomes postmortem entertainment. Considering these problems, we seek out the ideal form of deceased users’ personal data for commercialization. (...)
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  45. Data Science and Molecular Biology: Prediction and Mechanistic Explanation.Ezequiel López-Rubio & Emanuele Ratti - 2021 - Synthese 198 (4):3131-3156.
    In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...)
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  46. Explainable Artificial Intelligence in Data Science: From Foundational Issues Towards Socio-Technical Considerations.Joaquín Borrego-Díaz & Juan Galán-Páez - 2022 - Minds and Machines 32 (3):485-531.
    A widespread need to explain the behavior and outcomes of AI-based systems has emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the relatively new research area of eXplainable AI. Nowadays, the importance of XAI lies in the fact that the increasing control transference to this kind of system for decision making -or, at least, its use for assisting executive stakeholders- already affects many sensitive realms. The decision-making power handover to opaque AI systems makes mandatory explaining those, primarily (...)
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  47. From representations in predictive processing to degrees of representational features.Danaja Rutar, Wanja Wiese & Johan Kwisthout - 2022 - Minds and Machines 32 (3):461-484.
    Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of (...)
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  48. Defining Explanation and Explanatory Depth in XAI.Stefan Buijsman - 2022 - Minds and Machines 32 (3):563-584.
    Explainable artificial intelligence aims to help people understand black box algorithms, particularly of their outputs. But what are these explanations and when is one explanation better than another? The manipulationist definition of explanation from the philosophy of science offers good answers to these questions, holding that an explanation consists of a generalization that shows what happens in counterfactual cases. Furthermore, when it comes to explanatory depth this account holds that a generalization that has more abstract variables, is broader in scope (...)
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  49. The End of Vagueness: Technological Epistemicism, Surveillance Capitalism, and Explainable Artificial Intelligence.Alison Duncan Kerr & Kevin Scharp - 2022 - Minds and Machines 32 (3):585-611.
    Artificial Intelligence pervades humanity in 2022, and it is notoriously difficult to understand how certain aspects of it work. There is a movement—Explainable Artificial Intelligence —to develop new methods for explaining the behaviours of AI systems. We aim to highlight one important philosophical significance of XAI—it has a role to play in the elimination of vagueness. To show this, consider that the use of AI in what has been labeled surveillance capitalism has resulted in humans quickly gaining the capability to (...)
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  50. From Algorithmic Governance to Govern Algorithm.Zichun Xu - forthcoming - AI and Society:1-10.
    Algorithm is the core category and basic methods of the digital age, and advanced technologies such as big data, artificial intelligence, and blockchain all need to rely on various algorithm designs or take the algorithm as the underlying principle. However, due to the characteristics of algorithm design, application, and technology itself, there are also hidden worries such as algorithm black-box, algorithm discrimination, and difficulty in accountability in the operation process to varying degrees. This paper summarizes these problems into three aspects: (...)
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