Results for 'Social Machine'

999 found
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  1. Applying mechanical philosophy to web science: The case of social machines.Paul R. Smart, Kieron O’Hara & Wendy Hall - 2021 - European Journal for Philosophy of Science 11 (3):1-29.
    Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines, there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the (...)
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  2. Can Machines Read Our Minds?Christopher Burr & Nello Cristianini - 2019 - Minds and Machines 29 (3):461-494.
    We explore the question of whether machines can infer information about our psychological traits or mental states by observing samples of our behaviour gathered from our online activities. Ongoing technical advances across a range of research communities indicate that machines are now able to access this information, but the extent to which this is possible and the consequent implications have not been well explored. We begin by highlighting the urgency of asking this question, and then explore its conceptual underpinnings, in (...)
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  3.  71
    The Social in the Platform Trap: Why a Microscopic System Focus Limits the Prospect of Social Machines.Markus Luczak-Roesch & Ramine Tinati - 2017 - Discover Society 40.
    “Filter bubble”, “echo chambers”, “information diet” – the metaphors to describe today’s information dynamics on social media platforms are fairly diverse. People use them to describe the impact of the viral spread of fake, biased or purposeless content online, as witnessed during the recent race for the US presidency or the latest outbreak of the Ebola virus (in the latter case a tasteless racist meme was drowning out any meaningful content). This unravels the potential envisioned to arise from emergent (...)
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  4. The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms.Michael Stuart - 2019 - In Mark Addis, Fernand Gobet & Peter Sozou (eds.), Scientific Discovery in the Social Sciences. Springer Verlag.
    When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar (...)
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  5.  37
    The Technologisation of the Social: A Political Anthropology of the Digital Machine.Paul O'Connor & Marius Ion Benta (eds.) - 2021 - London, UK: Routledge.
    In an era of digital revolution, artificial intelligence, big data and augmented reality, technology has shifted from being a tool of communication to a primary medium of experience and sociality. Some of the most basic human capacities are increasingly being outsourced to machines and we increasingly experience and interpret the world through digital interfaces, with machines becoming ever more ‘social’ beings. Social interaction and human perception are being reshaped in unprecedented ways. This book explores this technologisation of the (...)
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  6. The Social Turn of Artificial Intelligence.Nello Cristianini, Teresa Scantamburlo & James Ladyman - 2021 - AI and Society (online).
    Social machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behavior. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous (...) machines provide a new paradigm for the design of intelligent systems, marking a new phase in AI. After describing the characteristics of goal-driven social machines, we discuss the consequences of their adoption, for the practice of artificial intelligence as well as for its regulation. (shrink)
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  7.  67
    Ghosts and the Machine: Philosophy of Social Science in Contemporary Perspective.S. Turner & P. Roth - 2003 - In Stephen P. Turner & Paul Andrew Roth (eds.), The Blackwell Guide to the Philosophy of the Social Sciences. Blackwell. pp. 1--17.
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  8. Social Machinery and Intelligence.Nello Cristianini, James Ladyman & Teresa Scantamburlo - manuscript
    Social machines are systems formed by technical and human elements interacting in a structured manner. The use of digital platforms as mediators allows large numbers of human participants to join such mechanisms, creating systems where interconnected digital and human components operate as a single machine capable of highly sophisticated behaviour. Under certain conditions, such systems can be described as autonomous and goal-driven agents. Many examples of modern Artificial Intelligence (AI) can be regarded as instances of this class of (...)
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  9. Making Moral Machines: Why We Need Artificial Moral Agents.Paul Formosa & Malcolm Ryan - forthcoming - AI and Society.
    As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive (...)
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  10. Can Machines Be People? Reflections on the Turing Triage Test.Robert Sparrow - 2012 - In Patrick Lin, Keith Abney & George Bekey (eds.), Robot Ethics: The Ethical and Social Implications of Robotics. MIT Press. pp. 301-315.
    In, “The Turing Triage Test”, published in Ethics and Information Technology, I described a hypothetical scenario, modelled on the famous Turing Test for machine intelligence, which might serve as means of testing whether or not machines had achieved the moral standing of people. In this paper, I: (1) explain why the Turing Triage Test is of vital interest in the context of contemporary debates about the ethics of AI; (2) address some issues that complexify the application of this test; (...)
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  11.  48
    Machine.Thomas Patrick Pringle, Bernard Stiegler & Gertrud Koch - 2019 - Minnesota University Press and Meson Press.
    In today’s society of humans and machines, automation, animation, and ecosystems are terms of concern. Categories of life and technology have become mixed in governmental policies and drive economic exploitation and the pathologies of everyday life. This book both curiously and critically advances the term that underlies these new developments: machine.
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  12.  89
    Can Machines Think? The Controversy That Led to the Turing Test.Bernardo Gonçalves - forthcoming - AI and Society:1-11.
    Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did Turing (...)
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  13.  52
    Distributed Responsibility in Human–Machine Interactions.Anna Strasser - 2021 - AI and Ethics.
    Artificial agents have become increasingly prevalent in human social life. In light of the diversity of new human–machine interactions, we face renewed questions about the distribution of moral responsibility. Besides positions denying the mere possibility of attributing moral responsibility to artificial systems, recent approaches discuss the circumstances under which artificial agents may qualify as moral agents. This paper revisits the discussion of how responsibility might be distributed between artificial agents and human interaction partners (including producers of artificial agents) (...)
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  14. The Motivations and Risks of Machine Ethics.Stephen Cave, Rune Nyrup, Karina Vold & Adrian Weller - 2019 - Proceedings of the IEEE 107 (3):562-574.
    Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, (...)
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  15. Wired Bodies. New Perspectives on the Machine-Organism Analogy.Luca Tonetti & Cilia Nicole (eds.) - 2017 - Rome, Italy: CNR Edizioni.
    The machine-organism analogy has played a pivotal role in the history of Western philosophy and science. Notwithstanding its apparent simplicity, it hides complex epistemological issues about the status of both organism and machine and the nature of their interaction. What is the real object of this analogy: organisms as a whole, their parts or, rather, bodily functions? How can the machine serve as a model for interpreting biological phenomena, cognitive processes, or more broadly the social and (...)
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  16.  46
    Geoffrey C. Bunn, The Truth Machine: A Social History of the Lie Detector. Baltimore: Johns Hopkins University Press, 2012. Pp. Ix+246. ISBN 978-1-4214-0530-8. £18.00. [REVIEW]Sean F. Johnston - 2013 - British Journal for the History of Science 46 (3):540-541.
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  17.  87
    The Use and Misuse of Counterfactuals in Ethical Machine Learning.Atoosa Kasirzadeh & Andrew Smart - 2021 - In ACM Conference on Fairness, Accountability, and Transparency (FAccT 21).
    The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning (...)
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  18. Why Machines Will Never Rule the World: Artificial Intelligence Without Fear.Jobst Smith Landgrebe & Barry Smith - 2022 - Abingdon, England: Routledge.
    The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...)
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  19. In Defense of Happiness: A Response to the Experience Machine.Matthew Silverstein - 2000 - Social Theory and Practice 26 (2):279-300.
    Many philosophers believe that Robert Nozick's experience machine argument poses an insurmountable obstacle to hedonism as a theory of well-being. After an initial attempt to demonstrate that the persuasiveness of this argument rests on a key ambiguity, I argue that the intuitions to which the thought experiment appeals are not nearly as clear as many philosophers suppose they are. I believe that a careful consideration of the origin of those intuitions -- especially in light of the so-called "paradox of (...)
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  20. Conceptualizing Policy in Value Sensitive Design: A Machine Ethics Approach.Steven Umbrello - 2021 - In Steven John Thompson (ed.), Machine Law, Ethics, and Morality in the Age of Artificial Intelligence. Hershey, PA, USA: pp. 108-125.
    The value sensitive design (VSD) approach to designing transformative technologies for human values is taken as the object of study in this chapter. VSD has traditionally been conceptualized as another type of technology or instrumentally as a tool. The various parts of VSD’s principled approach would then aim to discern the various policy requirements that any given technological artifact under consideration would implicate. Yet, little to no consideration has been given to how laws, regulations, policies and social norms engage (...)
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  21. On Reason and Spectral Machines: Robert Brandom and Bounded Posthumanism.David Roden - 2017 - In Rosi Braidotti Rick Dolphijn (ed.), Philosophy After Nature. London - New York: Rowman & Littlefield International. pp. 99-119.
    I distinguish two theses regarding technological successors to current humans (posthumans): an anthropologically bounded posthumanism (ABP) and an anthropologically unbounded posthumanism (AUP). ABP proposes transcendental conditions on agency that can be held to constrain the scope for “weirdness” in the space of possible posthumans a priori. AUP, by contrast, leaves the nature of posthuman agency to be settled empirically (or technologically). Given AUP there are no “future proof” constraints on the strangeness of posthuman agents. -/- In Posthuman Life I defended (...)
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  22.  13
    An Unconventional Look at AI: Why Today’s Machine Learning Systems Are Not Intelligent.Nancy Salay - 2020 - In LINKs: The Art of Linking, an Annual Transdisciplinary Review, Special Edition 1, Unconventional Computing. pp. 62-67.
    Machine learning systems (MLS) that model low-level processes are the cornerstones of current AI systems. These ‘indirect’ learners are good at classifying kinds that are distinguished solely by their manifest physical properties. But the more a kind is a function of spatio-temporally extended properties — words, situation-types, social norms — the less likely an MLS will be able to track it. Systems that can interact with objects at the individual level, on the other hand, and that can sustain (...)
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  23. Our Intuitions About the Experience Machine.Richard Rowland - 2017 - Journal of Ethics and Social Philosophy 12 (1):110-117.
    This article responds to a recent empirical study by De Brigard and Weijers on intuitions about the experience machine and what it tells us about hedonism.
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  24. Three Concepts for Crossing the Nature-Artifice Divide: Technology, Milieu, and Machine.Marco Altamirano - 2014 - Foucault Studies 17:11-35.
    The distinction between nature and artifice has been definitive for Western conceptions of the role of humans within their natural environment. But the human must already be separated from nature in order to distinguish between nature and artifice. This separation, in turn, facilitates a classification of knowledge in general, typically cast in terms of a hierarchy of sciences that ascends from the natural sciences to the social (or human) sciences. However, this hierarchy considers nature as a substantial foundation upon (...)
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  25.  78
    From Eye to Machine: Shifting Authority in Color Measurement.Sean F. Johnston - 2002 - In B. Saunders & J. Van Brakel (eds.), Theories, Technologies, Instrumentalities of Color: Anthropological and Historiographic Perspectives. Lanham, MD 20706, USA: University Press of America. pp. 289-306.
    Given a subject so imbued with contention and conflicting theoretical stances, it is remarkable that automated instruments ever came to replace the human eye as sensitive arbiters of color specification. Yet, dramatic shifts in assumptions and practice did occur in the first half of the twentieth century. How and why was confidence transferred from careful observers to mechanized devices when the property being measured – color – had become so closely identified with human physiology and psychology? A fertile perspective on (...)
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  26. Social Media Studies.Vijaya Abhinandan - manuscript
    Social media sites offer a huge data about our everyday life, thoughts, feelings and reflecting what the users want and like. Since user behavior on OSNS is a mirror image of actions in the real world, scholars have to investigate the use SM to prediction, making forecasts about our daily life. This paper provide an overview of different commonly used social media and application of their data analysis.
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  27. Utopian Social Delusions in the 21st Century.Starks Michael - 2017 - Henderson,NV, USA: Michael Starks.
    This collection of articles was written over the last 10 years and edited them to bring them up to date (2017). All the articles are about human behavior (as are all articles by anyone about anything), and so about the limitations of having a recent monkey ancestry (8 million years or much less depending on viewpoint) and manifest words and deeds within the framework of our innate psychology as presented in the table of intentionality. As famous evolutionist Richard Leakey says, (...)
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  28. Bodily Intentionality and Social Affordances in Context.Erik Rietveld - 2012 - In Fabio Paglieri (ed.), Consciousness in Interaction. !e role of the natural and social context in shaping consciousness. John Benjamins.
    There are important structural similarities in the way that animals and humans engage in unreflective activities, including unreflective social interactions in the case of higher animals. Firstly, it is a form of unreflective embodied intelligence that is ‘motivated’ by the situation. Secondly, both humans and non-human animals are responsive to ‘affordances’ (Gibson 1979); to possibilities for action offered by an environment. Thirdly, both humans and animals are selectively responsive to one affordance rather than another. Social affordances are a (...)
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  29. Disoriented and Alone in the “Experience Machine” - On Netflix, Shared World Deceptions and the Consequences of Deepening Algorithmic Personalization.Maria Brincker - 2021 - SATS 22 (1):75-96.
    Most online platforms are becoming increasingly algorithmically personalized. The question is if these practices are simply satisfying users preferences or if something is lost in this process. This article focuses on how to reconcile the personalization with the importance of being able to share cultural objects - including fiction – with others. In analyzing two concrete personalization examples from the streaming giant Netflix, several tendencies are observed. One is to isolate users and sometimes entirely eliminate shared world aspects. Another tendency (...)
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  30.  45
    AI Powered Anti-Cyber Bullying System Using Machine Learning Algorithm of Multinomial Naïve Bayes and Optimized Linear Support Vector Machine.Tosin Ige & Sikiru Adewale - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 5.
    Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...)
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  31. Wittgenstein and the Problem of Machine Consciousness.J. C. Nyíri - 1989 - Grazer Philosophische Studien 33 (1):375-394.
    For any given society, its particular technology of communication has far-reaching consequences, not merely as regards social organization, but on the epistemic level as well. Plato's name-theory of meaning represents the transition from the age of primary orality to that of literacy; Wittgenstein's use-theory of meaning stands for the transition from the age of literacy to that of a second orality (audiovisual communication, electronic information processing). On the basis of a use-theory of meaning the problem of machine consciousness, (...)
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  32. Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains? Towards a Media Sociology of Machine Learning.Rainer Mühlhoff - 2019 - New Media and Society 1.
    Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and (...)
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  33. Lethal Autonomous Weapons: Designing War Machines with Values.Steven Umbrello - 2019 - Delphi: Interdisciplinary Review of Emerging Technologies 1 (2):30-34.
    Lethal Autonomous Weapons (LAWs) have becomes the subject of continuous debate both at national and international levels. Arguments have been proposed both for the development and use of LAWs as well as their prohibition from combat landscapes. Regardless, the development of LAWs continues in numerous nation-states. This paper builds upon previous philosophical arguments for the development and use of LAWs and proposes a design framework that can be used to ethically direct their development. The conclusion is that the philosophical arguments (...)
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  34.  33
    AI Powered Anti-Cyber Bullying System Using Machine Learning Algorithm of Multinomial Naïve Bayes and Optimized Linear Support Vector Machine.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 5.
    Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...)
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  35. A Definition, Benchmark and Database of AI for Social Good Initiatives.Josh Cowls, Andreas Tsmadaos, Mariarosaria Taddeo & Luciano Floridi - 2021 - Nature Machine Intelligence 3:111–⁠115.
    Initiatives relying on artificial intelligence (AI) to deliver socially beneficial outcomes—AI for social good (AI4SG)—are on the rise. However, existing attempts to understand and foster AI4SG initiatives have so far been limited by the lack of normative analyses and a shortage of empirical evidence. In this Perspective, we address these limitations by providing a definition of AI4SG and by advocating the use of the United Nations’ Sustainable Development Goals (SDGs) as a benchmark for tracing the scope and spread of (...)
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  36.  81
    Robots Working with Humans or Humans Working with Robots? Searching for Social Dimensions in New Human-Robot Interaction in Industry.António Moniz & Bettina-Johanna Krings - 2016 - Societies 2016 (23).
    The focus of the following article is on the use of new robotic systems in the manufacturing industry with respect to the social dimension. Since “intuitive” human–machine interaction (HMI) in robotic systems becomes a significant objective of technical progress, new models of work organization are needed. This hypothesis will be investigated through the following two aims: The first aim is to identify relevant research questions related to the potential use of robotic systems in different systems of work organization (...)
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  37. Mapping Value Sensitive Design Onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1 (3):283–296.
    Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, (...)
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  38. Robot Autonomy vs. Human Autonomy: Social Robots, Artificial Intelligence (AI), and the Nature of Autonomy.Paul Formosa - 2021 - Minds and Machines 31 (4):595-616.
    Social robots are robots that can interact socially with humans. As social robots and the artificial intelligence that powers them becomes more advanced, they will likely take on more social and work roles. This has many important ethical implications. In this paper, we focus on one of the most central of these, the impacts that social robots can have on human autonomy. We argue that, due to their physical presence and social capacities, there is a (...)
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  39. Lost in the Socially Extended Mind: Genuine Intersubjectivity and Disturbed Self-Other Demarcation in Schizophrenia.Tom Froese & Joel Krueger - 2020 - In Christian Tewes & Giovanni Stanghellini (eds.), Time and Body: Phenomenological and Psychopathological Approaches. Cambridge, UK: pp. 318-340.
    Much of the characteristic symptomatology of schizophrenia can be understood as resulting from a pervasive sense of disembodiment. The body is experienced as an external machine that needs to be controlled with explicit intentional commands, which in turn leads to severe difficulties in interacting with the world in a fluid and intuitive manner. In consequence, there is a characteristic dissociality: Others become problems to be solved by intellectual effort and no longer present opportunities for spontaneous interpersonal alignment. This dissociality (...)
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  40. The Metaphysics of the Time-Machine.Alexandros Schismenos - 2019 - SOCRATES 6 (3 & 4):37-53.
    The concept of time-travel is a modern idea which combines the imaginary signification of rational domination, the imaginary signification of technological omnipotence, the imaginary concept of eternity and the imaginary desire for immortality. It is a synthesis of central conceptual schemata of techno-science, such as the linearity and homogeneity of time, the radical separation of subjectivity from the world, the radical separation of the individual from his/her social-historical environment. The emergence of this idea, its spread during the 20th century (...)
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  41. Digital Subjectivation and Financial Markets: Criticizing Social Studies of Finance with Lazzarato.Tim Christiaens - 2016 - Big Data and Society 3 (2):1-15.
    The recently rising field of Critical Data Studies is still facing fundamental questions. Among these is the enigma of digital subjectivation. Who are the subjects of Big Data? A field where this question is particularly pressing is finance. Since the 1990s traders have been steadily integrated into computerized data assemblages, which calls for an ontology that eliminates the distinction between human sovereign subjects and non-human instrumental objects. The latter subjectivize traders in pre-conscious ways, because human consciousness runs too slow to (...)
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  42.  77
    Word vector embeddings hold social ontological relations capable of reflecting meaningful fairness assessments.Ahmed Izzidien - 2021 - AI and Society (March 2021):1-20.
    Programming artificial intelligence to make fairness assessments of texts through top-down rules, bottom-up training, or hybrid approaches, has presented the challenge of defining cross-cultural fairness. In this paper a simple method is presented which uses vectors to discover if a verb is unfair or fair. It uses already existing relational social ontologies inherent in Word Embeddings and thus requires no training. The plausibility of the approach rests on two premises. That individuals consider fair acts those that they would be (...)
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  43.  46
    Bereft of Reason: On the Decline of Social Thought and Prospects for its Renewal.Eugene Halton - 1995 - University of Chicago Press.
    In this radical critique of contemporary social theory, Eugene Halton argues that both modernism and postmodernism are damaged philosophies whose acceptance of the myths of the mind/body dichotomy make them incapable of solving our social dilemmas. Claiming that human beings should be understood as far more than simply a form of knowledge, social construction, or contingent difference, Halton argues that contemporary thought has lost touch with the spontaneous passions—or enchantment—of life. Exploring neglected works in twentieth century (...) thought and philosophy—particularly the writings of Lewis Mumford and Charles Peirce—as well as the work of contemporary writers such as Vaclav Havel, Maya Angelou, Milan Kundera, Doris Lessing, and Victor Turner, Halton argues that reason is dependent upon nonrational forces—including sentiment, instinct, conjecture, imagination, and experience. We must, he argues, frame our questions in a way which encompasses both enchantment and critical reason, and he offers an outline here for doing so. A passionate plea for a fundamental reexamination of the entrenched assumptions of the modern era, this book deals with issues of vital concern to modern societies and should be read by scholars across disciplines. Robert Bellah: "This is an original, incisive, and badly needed book. In prose as vigorous as his argument, Halton addresses issues urgent in many disciplines, as well as in our common culture." "Halton takes the 'ghost in the machine' as a dominant defining metaphor for modern thought and life, and criticizes it with gusto, wit, wide reading, and philosophical acumen."—Robert J. Mulvaney, _Review of Metaphysics_. (shrink)
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  44. Simulation as Formal and Generative Social Science: The Very Idea.Nuno David, Jaime Sichman & Helder Coelho - 2007 - In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science, and Us: Philosophy and Complexity. World Scientific. pp. 266--275.
    The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of (...)
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  45.  52
    Measuring Information Deprivation: A Democratic Proposal.Adrian K. Yee - forthcoming - Philosophy of Science.
    There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites' conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality and that doing so may improve the predictive and explanatory power (...)
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  46. Socio-Technical Computation.Markus Luczak-Roesch, Ramine Tinati, Kieron O'Hara & Nigel Shadbolt - 2015 - In Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing.
    Motivated by the significant amount of successful collaborative problem solving activity on the Web, we ask: Can the accumulated information propagation behavior on the Web be conceived as a giant machine, and reasoned about accordingly? In this paper we elaborate a thesis about the computational capability embodied in information sharing activities that happen on the Web, which we term socio-technical computation, reflecting not only explicitly conditional activities but also the organic potential residing in information on the Web.
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  47. Faszination Zeitreisen.Kay Herrmann - 2014 - Universitätsverlag Chemnitz.
    Time travel is one of mankind's most ancient dreams. It inspires our imagination and provides material for bizarre stories. H. G. Wells' novel, "The Time Machine" (1895), marks the beginning of a long history of science fiction literature devoted to the subject of time travel. -/- A work on the subject of time travel forces us to re-examine our concept of "time". The complexity and the contradictory nature this subject makes it difficult to be more precise about "time". On (...)
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  48. Algorithmic Fairness From a Non-Ideal Perspective.Sina Fazelpour & Zachary C. Lipton - 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society.
    Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and (...)
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  49. The Problem of Evil in Virtual Worlds.Brendan Shea - 2017 - In Mark Silcox (ed.), Experience Machines: The Philosophy of Virtual Worlds. Lanham, MD: Rowman & Littlefield. pp. 137-155.
    In its original form, Nozick’s experience machine serves as a potent counterexample to a simplistic form of hedonism. The pleasurable life offered by the experience machine, its seems safe to say, lacks the requisite depth that many of us find necessary to lead a genuinely worthwhile life. Among other things, the experience machine offers no opportunities to establish meaningful relationships, or to engage in long-term artistic, intellectual, or political projects that survive one’s death. This intuitive objection finds (...)
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  50. The Relations Between Pedagogical and Scientific Explanations of Algorithms: Case Studies From the French Administration.Maël Pégny - manuscript
    The opacity of some recent Machine Learning (ML) techniques have raised fundamental questions on their explainability, and created a whole domain dedicated to Explainable Artificial Intelligence (XAI). However, most of the literature has been dedicated to explainability as a scientific problem dealt with typical methods of computer science, from statistics to UX. In this paper, we focus on explainability as a pedagogical problem emerging from the interaction between lay users and complex technological systems. We defend an empirical methodology based (...)
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