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  1. (1 other version)The epistemological foundations of data science: a critical analysis.Jules Desai, David Watson, Vincent Wang, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry (...)
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  • Information and design: book symposium on Luciano Floridi’s The Logic of Information.Tim Gorichanaz, Jonathan Furner, Lai Ma, David Bawden, Liz Robinson, Dominic Dixon, Ken Herold, Sille Obelitz Søe, Betsy Van der Veer Martens & Luciano Floridi - 2020 - Journal of Documentation 76 (2).
    The purpose of this paper is to review and discuss Luciano Floridi’s 2019 book The Logic of Information: A Theory of Philosophy as Conceptual Design, the latest instalment in his philosophy of information (PI) tetralogy, particularly with respect to its implications for library and information studies (LIS) .
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  • (1 other version)Trusting artificial intelligence in cybersecurity is a double-edged sword.Mariarosaria Taddeo, Tom McCutcheon & Luciano Floridi - 2019 - Philosophy and Technology 32 (1):1-15.
    Applications of artificial intelligence (AI) for cybersecurity tasks are attracting greater attention from the private and the public sectors. Estimates indicate that the market for AI in cybersecurity will grow from US$1 billion in 2016 to a US$34.8 billion net worth by 2025. The latest national cybersecurity and defence strategies of several governments explicitly mention AI capabilities. At the same time, initiatives to define new standards and certification procedures to elicit users’ trust in AI are emerging on a global scale. (...)
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  • Big Data, new epistemologies and paradigm shifts.Rob Kitchin - 2014 - Big Data and Society 1 (1).
    This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, (...)
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  • Information and design: book symposium on Luciano Floridi’s The Logic of Information.D. Bawden, T. Gorichanaz, J. Furner, L. Robinson, M. Ma, K. Herold, B. Van der Veer Martens, L. Floridi & D. Dixon - manuscript
    Purpose – To review and discuss Luciano Floridi’s 2019 book The Logic of Information: A Theory of Philosophy as Conceptual Design, the latest instalment in his philosophy of information (PI) tetralogy, particularly with respect to its implications for library and information studies (LIS). Design/methodology/approach – Nine scholars with research interests in philosophy and LIS read and responded to the book, raising critical and heuristic questions in the spirit of scholarly dialogue. Floridi responded to these questions. Findings – Floridi’s PI, including (...)
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  • Contemporary Philosophy and Social Science: An Interdisciplinary Dialogue.Michiru Nagatsu & Attilia Ruzzene (eds.) - 2019 - London: Bloomsbury Academic.
    How should we theorize about the social world? How can we integrate theories, models and approaches from seemingly incompatible disciplines? Does theory affect social reality? This state-of-the-art collection addresses contemporary methodological questions and interdisciplinary developments in the philosophy of social science. Facilitating a mutually enriching dialogue, chapters by leading social scientists are followed by critical evaluations from philosophers of social science. This exchange showcases recent major theoretical and methodological breakthroughs and challenges in the social sciences, as well as fruitful ways (...)
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  • Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
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  • Making Data Valuable: Political, Economic, and Conceptual Bases of Big Data.Anna Lauren Hoffmann - 2018 - Philosophy and Technology 31 (2):209-212.
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  • Simplified models: a different perspective on models as mediators.C. D. McCoy & Michela Massimi - 2018 - European Journal for Philosophy of Science 8 (1):99-123.
    We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...)
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  • The ethics of algorithms: mapping the debate.Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter & Luciano Floridi - 2016 - Big Data and Society 3 (2):2053951716679679.
    In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...)
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  • Big Data, epistemology and causality: Knowledge in and knowledge out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...)
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  • The Causal Nature of Modeling with Big Data.Wolfgang Pietsch - 2016 - Philosophy and Technology 29 (2):137-171.
    I argue for the causal character of modeling in data-intensive science, contrary to widespread claims that big data is only concerned with the search for correlations. After discussing the concept of data-intensive science and introducing two examples as illustration, several algorithms are examined. It is shown how they are able to identify causal relevance on the basis of eliminative induction and a related difference-making account of causation. I then situate data-intensive modeling within a broader framework of an epistemology of scientific (...)
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  • Ethical Issues in Consent for the Reuse of Data in Health Data Platforms.Alex McKeown, Miranda Mourby, Paul Harrison, Sophie Walker, Mark Sheehan & Ilina Singh - 2021 - Science and Engineering Ethics 27 (1):1-21.
    Data platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate model for facilitating (...)
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  • The Deluge of Spurious Correlations in Big Data.Cristian S. Calude & Giuseppe Longo - 2016 - Foundations of Science 22 (3):595-612.
    Very large databases are a major opportunity for science and data analytics is a remarkable new field of investigation in computer science. The effectiveness of these tools is used to support a “philosophy” against the scientific method as developed throughout history. According to this view, computer-discovered correlations should replace understanding and guide prediction and action. Consequently, there will be no need to give scientific meaning to phenomena, by proposing, say, causal relations, since regularities in very large databases are enough: “with (...)
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  • The ethics of big data: current and foreseeable issues in biomedical contexts.Brent Daniel Mittelstadt & Luciano Floridi - 2016 - Science and Engineering Ethics 22 (2):303–341.
    The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...)
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  • Can we trust Big Data? Applying philosophy of science to software.John Symons & Ramón Alvarado - 2016 - Big Data and Society 3 (2).
    We address some of the epistemological challenges highlighted by the Critical Data Studies literature by reference to some of the key debates in the philosophy of science concerning computational modeling and simulation. We provide a brief overview of these debates focusing particularly on what Paul Humphreys calls epistemic opacity. We argue that debates in Critical Data Studies and philosophy of science have neglected the problem of error management and error detection. This is an especially important feature of the epistemology of (...)
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  • The rise of machine learning in the academic social sciences.Charles Rahal, Mark Verhagen & David Kirk - forthcoming - AI and Society.
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  • Algo-Rhythms and the Beat of the Legal Drum.Ugo Pagallo - 2018 - Philosophy and Technology 31 (4):507-524.
    The paper focuses on concerns and legal challenges brought on by the use of algorithms. A particular class of algorithms that augment or replace analysis and decision-making by humans, i.e. data analytics and machine learning, is under scrutiny. Taking into account Balkin’s work on “the laws of an algorithmic society”, attention is drawn to obligations of transparency, matters of due process, and accountability. This US-centric analysis on drawbacks and loopholes of current legal systems is complemented with the analysis of norms (...)
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  • A moral analysis of intelligent decision-support systems in diagnostics through the lens of Luciano Floridi’s information ethics.Dmytro Mykhailov - 2021 - Human Affairs 31 (2):149-164.
    Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine (...)
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  • The Ethics of Biomedical ‘Big Data’ Analytics.Brent Mittelstadt - 2019 - Philosophy and Technology 32 (1):17-21.
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  • From Individual to Group Privacy in Big Data Analytics.Brent Mittelstadt - 2017 - Philosophy and Technology 30 (4):475-494.
    Mature information societies are characterised by mass production of data that provide insight into human behaviour. Analytics has arisen as a practice to make sense of the data trails generated through interactions with networked devices, platforms and organisations. Persistent knowledge describing the behaviours and characteristics of people can be constructed over time, linking individuals into groups or classes of interest to the platform. Analytics allows for a new type of algorithmically assembled group to be formed that does not necessarily align (...)
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  • Big Data for Biomedical Research and Personalised Medicine: an Epistemological and Ethical Cross-Analysis.Thierry Magnin & Mathieu Guillermin - 2017 - Human and Social Studies. Research and Practice 6 (3):13-36.
    Big data techniques, data-driven science and their technological applications raise many serious ethical questions, notably about privacy protection. In this paper, we highlight an entanglement between epistemology and ethics of big data. Discussing the mobilisation of big data in the fields of biomedical research and health care, we show how an overestimation of big data epistemic power – of their objectivity or rationality understood through the lens of neutrality – can become ethically threatening. Highlighting the irreducible non-neutrality at play in (...)
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  • Varieties of Data-Centric Science: Regional Climate Modeling and Model Organism Research.Elisabeth Lloyd, Greg Lusk, Stuart Gluck & Seth McGinnis - 2022 - Philosophy of Science 89 (4):802-823.
    Modern science’s ability to produce, store, and analyze big datasets is changing the way that scientific research is practiced. Philosophers have only begun to comprehend the changed nature of scientific reasoning in this age of “big data.” We analyze data-focused practices in biology and climate modeling, identifying distinct species of data-centric science: phenomena-laden in biology and phenomena-agnostic in climate modeling, each better suited for its own domain of application, though each entail trade-offs. We argue that data-centric practices in science are (...)
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  • Dissecting the Algorithmic Leviathan: On the Socio-Political Anatomy of Algorithmic Governance.Pascal D. König - 2020 - Philosophy and Technology 33 (3):467-485.
    A growing literature is taking an institutionalist and governance perspective on how algorithms shape society based on unprecedented capacities for managing social complexity. Algorithmic governance altogether emerges as a novel and distinctive kind of societal steering. It appears to transcend established categories and modes of governance—and thus seems to call for new ways of thinking about how social relations can be regulated and ordered. However, as this paper argues, despite its novel way of realizing outcomes of collective steering and coordination, (...)
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  • Thinking about the idea of consent in data science genomics: How ‘informed’ is it?Jennifer Greenwood & Andrew Crowden - 2021 - Nursing Philosophy 22 (3):e12347.
    In this paper we argue that ‘informed’ consent in Big Data genomic biobanking is frequently less than optimally informative. This is due to the particular features of genomic biobanking research which render it ethically problematic. We discuss these features together with details of consent models aimed to address them. Using insights from consent theory, we provide a detailed analysis of the essential components of informed consent which includes recommendations to improve consent performance. In addition, and using insights from philosophy of (...)
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  • Big Data Analytics, Infectious Diseases and Associated Ethical Impacts.Chiara Garattini, Jade Raffle, Dewi N. Aisyah, Felicity Sartain & Zisis Kozlakidis - 2019 - Philosophy and Technology 32 (1):69-85.
    The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are (...)
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  • (1 other version)What the near future of artificial intelligence could be.Luciano Floridi - 2019 - Philosophy and Technology 32 (1):1-15.
    In this article, I shall argue that AI’s likely developments and possible challenges are best understood if we interpret AI not as a marriage between some biological-like intelligence and engineered artefacts, but as a divorce between agency and intelligence, that is, the ability to solve problems successfully and the necessity of being intelligent in doing so. I shall then look at five developments: (1) the growing shift from logic to statistics, (2) the progressive adaptation of the environment to AI rather (...)
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  • Information quality.Luciano Floridi - 2013 - Philosophy and Technology 26 (1):1-6.
    Information, and information and communication technologies (ICTs) are critical for most developed post-industrial societies. It follows, therefore, that the better the quality of the information exchanged, the more likely such societies and their members may prosper. But what is information quality (IQ) exactly? This paper discusses current definitions, problems and approaches to IQ and the question of how we should, and could, evaluate IQ in the future.
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  • AI, big data, and the future of consent.Adam J. Andreotta, Nin Kirkham & Marco Rizzi - 2022 - AI and Society 37 (4):1715-1728.
    In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that can impede (...)
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  • At close quarters: Combatting Facebook design, features and temporalities in social research.Stevie Docherty & Justine Gangneux - 2018 - Big Data and Society 5 (2).
    As researchers we often find ourselves grappling with social media platforms and data ‘at close quarters’. Although social media platforms were created for purposes other than academic research – which are apparent in their architecture and temporalities – they offer opportunities for researchers to repurpose them for the collection, generation and analysis of rich datasets. At the same time, this repurposing raises an evolving range of practical and methodological challenges at the small and large scale. We draw on our experiences (...)
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  • Raw data or hypersymbols? Meaning-making with digital data, between discursive processes and machinic procedures.Lucile Crémier, Maude Bonenfant & Laura Iseut Lafrance St-Martin - 2019 - Semiotica 2019 (230):189-212.
    The large-scale and intensive collection and analysis of digital data (commonly called “Big Data”) has become a common, popular, and consensual research method for the social sciences, as the automation of data collection, mathematization of analysis, and digital objectification reinforce both its efficiency and truth-value. This article opens with a critical review of the literature on data collection and analysis, and summarizes current ethical discussions focusing on these technologies. A semiotic model of data production and circulation is then introduced to (...)
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  • (1 other version)Los desafíos éticos en la era del conocimiento científico-técnico según la óptica de Paul Ricoeur.Beatriz Contreras Tasso - 2014 - Veritas: Revista de Filosofía y Teología 30:09-27.
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  • Managing Algorithmic Accountability: Balancing Reputational Concerns, Engagement Strategies, and the Potential of Rational Discourse.Alexander Buhmann, Johannes Paßmann & Christian Fieseler - 2020 - Journal of Business Ethics 163 (2):265-280.
    While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...)
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  • Mapping the public debate on ethical concerns: algorithms in mainstream media.Balbir S. Barn - 2019 - Journal of Information, Communication and Ethics in Society 18 (1):124-139.
    Purpose Algorithms are in the mainstream media news on an almost daily basis. Their context is invariably artificial intelligence and machine learning decision-making. In media articles, algorithms are described as powerful, autonomous actors that have a capability of producing actions that have consequences. Despite a tendency for deification, the prevailing critique of algorithms focuses on ethical concerns raised by decisions resulting from algorithmic processing. However, the purpose of this paper is to propose that the ethical concerns discussed are limited in (...)
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  • Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study.Abdallah Al-Ani, Abdallah Rayyan, Ahmad Maswadeh, Hala Sultan, Ahmad Alhammouri, Hadeel Asfour, Tariq Alrawajih, Sarah Al Sharie, Fahed Al Karmi, Ahmad Azzam, Asem Mansour & Maysa Al-Hussaini - 2024 - BMC Medical Ethics 25 (1):1-14.
    Aims To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners. Methods We implemented a literature-validated questionnaire to examine the knowledge, attitudes, and practices of the target population during the period between April and August 2023. Themes of ethical debate included privacy breaches, consent, ownership, augmented biases, epistemology, and accountability. Participants’ responses were showcased using descriptive statistics and compared between groups using t-test or ANOVA. (...)
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  • (1 other version)Floridi/Flusser: - Parallel Lives in Hyper/Posthistory.Vasileios Galanos - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 229-244.
    Vilém Flusser, philosopher of communication, and Luciano Floridi, philosopher of information have been engaged with common subjects, extracting surprisingly similar conclusions in distant ages, affecting distant audiences. Curiously, despite the common characteristics, their works have almost never been used together. This paper presents Flusser’s concepts of functionaries, informational environment, information recycle, and posthistory as mellontological hypotheses verified in Floridi’s recently proposed realistic neologisms of inforgs, infosphere, e-nvironmentalism, and hyperhistory. Following Plutarch’s literature model of “parallel lives,” the description of an earlier (...)
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