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  1. Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality.Bernd Stahl, Kevin Macnish, Tilimbe Jiya, Laurence Brooks, Josephina Antoniou & Mark Ryan - 2021 - Science and Engineering Ethics 27 (2):1-29.
    This study investigates the ethical use of Big Data and Artificial Intelligence technologies —using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues,, into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety of different social domains, fields, and (...)
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  • Four Responsibility Gaps with Artificial Intelligence: Why They Matter and How to Address Them.Filippo Santoni de Sio & Giulio Mecacci - forthcoming - Philosophy and Technology:1-28.
    The notion of “responsibility gap” with artificial intelligence was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected problems (...)
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  • The Right to Refuse Diagnostics and Treatment Planning by Artificial Intelligence.Thomas Ploug & Søren Holm - 2020 - Medicine, Health Care and Philosophy 23 (1):107-114.
    In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to the physician’s role in the patients’ formation of and acting on personal preferences and values, the bias and opacity problem of AI systems, and rational concerns about the future societal effects of introducing AI systems in the health care sector.
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  • Mobile Health Ethics and the Expanding Role of Autonomy.Bettina Schmietow & Georg Marckmann - 2019 - Medicine, Health Care and Philosophy 22 (4):623-630.
    Mhealth technology is mushrooming world-wide and, in a variety of forms, reaches increasing numbers of users in ever-widening contexts and virtually independent from standard medical evidence assessment. Yet, debate on the broader societal impact including in particular mapping and classification of ethical issues raised has been limited. This article, as part of an ongoing empirically informed ethical research project, provides an overview of ethical issues of mhealth applications with a specific focus on implications on autonomy as a key notion in (...)
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  • Problems with “Friendly AI”.Oliver Li - forthcoming - Ethics and Information Technology.
    On virtue ethical grounds, Barbro Fröding and Martin Peterson recently recommended that near-future AIs should be developed as ‘Friendly AI’. AI in social interaction with humans should be programmed such that they mimic aspects of human friendship. While it is a reasonable goal to implement AI systems interacting with humans as Friendly AI, I identify four issues that need to be addressed concerning Friendly AI with Fröding’s and Peterson’s understanding of Friendly AI as a starting point. In a first step, (...)
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  • Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing. [REVIEW]Peter Seele, Claus Dierksmeier, Reto Hofstetter & Mario D. Schultz - 2021 - Journal of Business Ethics 170 (4):697-719.
    Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative (...)
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  • Algorithmisches Entscheiden, Ambiguitätstoleranz und die Frage nach dem Sinn.Lisa Herzog - 2021 - Deutsche Zeitschrift für Philosophie 69 (2):197-213.
    In more and more contexts, human decision-making is replaced by algorithmic decision-making. While promising to deliver efficient and objective decisions, algorithmic decision systems have specific weaknesses, some of which are particularly dangerous if data are collected and processed by profit-oriented companies. In this paper, I focus on two problems that are at the root of the logic of algorithmic decision-making: tolerance for ambiguity, and instantiations of Campbell’s law, i. e. of indicators that are used for “social decision-making” being subject to (...)
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  • Model Talk: Calculative Cultures in Quantitative Finance.Kristian Bondo Hansen - 2021 - Science, Technology, and Human Values 46 (3):600-627.
    This paper explores how calculative cultures shape perceptions of models and practices of model use in the financial industry. A calculative culture comprises a specific set of practices and norms concerning data and model use in an organizational setting. Drawing on interviews with model users working in algorithmic securities trading, I argue that the introduction of complex machine-learning models changes the dynamics in calculative cultures, which leads to a displacement of human judgment in quantitative finance. In this paper, I distinguish (...)
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  • A New Argument for No-Fault Compensation in Health Care: The Introduction of Artificial Intelligence Systems.Søren Holm, Catherine Stanton & Benjamin Bartlett - forthcoming - Health Care Analysis:1-18.
    Artificial intelligence systems advising healthcare professionals will be widely introduced into healthcare settings within the next 5–10 years. This paper considers how this will sit with tort/negligence based legal approaches to compensation for medical error. It argues that the introduction of AI systems will provide an additional argument pointing towards no-fault compensation as the better legal solution to compensation for medical error in modern health care systems. The paper falls into four parts. The first part rehearses the main arguments for (...)
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  • Algorithmic Augmentation of Democracy: Considering Whether Technology Can Enhance the Concepts of Democracy and the Rule of Law Through Four Hypotheticals.Paul Burgess - forthcoming - AI and Society:1-16.
    The potential use, relevance, and application of AI and other technologies in the democratic process may be obvious to some. However, technological innovation and, even, its consideration may face an intuitive push-back in the form of algorithm aversion :114–126, 2015). In this paper, I confront this intuition and suggest that a more ‘extreme’ form of technological change in the democratic process does not necessarily result in a worse outcome in terms of the fundamental concepts of democracy and the Rule of (...)
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  • The Influence of Business Incentives and Attitudes on Ethics Discourse in the Information Technology Industry.Sanju Ahuja & Jyoti Kumar - forthcoming - Philosophy and Technology:1-26.
    As information technologies have become synonymous with progress in modern society, several ethical concerns have surfaced about their societal implications. In the past few decades, information technologies have had a value-laden impact on social evolution. However, there is limited agreement on the responsibility of businesses and innovators concerning the ethical aspects of information technologies. There is a need to understand the role of business incentives and attitudes in driving technological progress and to understand how they steer the ethics discourse on (...)
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  • Recognizing Argument Types and Adding Missing Reasons.Christoph Lumer - 2019 - In Bart J. Garssen, David Godden, Gordon Mitchell & Jean Wagemans (eds.), Proceedings of the Ninth Conference of the International Society for the Study of Argumentation (ISSA). [Amsterdam, July 3-6, 2018.]. Amsterdam (Netherlands): pp. 769-777.
    The article develops and justifies, on the basis of the epistemological argumentation theory, two central pieces of the theory of evaluative argumentation interpretation: 1. criteria for recognizing argument types and 2. rules for adding reasons to create ideal arguments. Ad 1: The criteria for identifying argument types are a selection of essential elements from the definitions of the respective argument types. Ad 2: After presenting the general principles for adding reasons (benevolence, authenticity, immanence, optimization), heuristics are proposed for finding missing (...)
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  • The Governance of Unmanned Aircraft Systems (UAS): Aviation Law, Human Rights, and the Free Movement of Data in the EU.Ugo Pagallo & Eleonora Bassi - 2020 - Minds and Machines 30 (3):439-455.
    The paper deals with the governance of Unmanned Aircraft Systems in European law. Three different kinds of balance have been struck between multiple regulatory systems, in accordance with the sector of the governance of UAS which is taken into account. The first model regards the field of civil aviation law and its European Union ’s regulation: the model looks like a traditional mix of top-down regulation and soft law. The second model concerns the EU general data protection law, the GDPR, (...)
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  • Listening to Distant Voices.Claudius Messner - 2020 - International Journal for the Semiotics of Law - Revue Internationale de Sémiotique Juridique 33 (4):1143-1173.
    The “digital revolution”, which the juridical observer is asked to tackle, as well as the consequences that legal experts have to deal with, is not an abstract phenomenon. Digitalisation is a consequence and the latest manifestation of the Western culture of the machine. This framework shapes the various concepts of language, political community, and justice, on which, in turn, the diverse current views of the interpreter depend. The twentieth century’s globalisation of legal civilisation has perfected the machinery of legal talk. (...)
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  • Towards Transparency by Design for Artificial Intelligence.Heike Felzmann, Eduard Fosch-Villaronga, Christoph Lutz & Aurelia Tamò-Larrieux - 2020 - Science and Engineering Ethics 26 (6):3333-3361.
    In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making environments. With the rise of artificial intelligence and the ability of AI systems to make automated and self-learned decisions, a call for transparency of how such systems reach decisions has echoed within academic and policy circles. The term transparency, however, relates to multiple concepts, fulfills many functions, and holds different (...)
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  • Against Interpretability: a Critical Examination of the Interpretability Problem in Machine Learning.Maya Krishnan - 2020 - Philosophy and Technology 33 (3):487-502.
    The usefulness of machine learning algorithms has led to their widespread adoption prior to the development of a conceptual framework for making sense of them. One common response to this situation is to say that machine learning suffers from a “black box problem.” That is, machine learning algorithms are “opaque” to human users, failing to be “interpretable” or “explicable” in terms that would render categorization procedures “understandable.” The purpose of this paper is to challenge the widespread agreement about the existence (...)
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  • From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles Into Practices.Jessica Morley, Luciano Floridi, Libby Kinsey & Anat Elhalal - 2020 - Science and Engineering Ethics 26 (4):2141-2168.
    The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...)
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  • Automatisierte Ungleichheit: Ethik der Künstlichen Intelligenz in der biopolitischen Wende des Digitalen Kapitalismus.Rainer Mühlhoff - 2020 - Deutsche Zeitschrift für Philosophie 68 (6):867-890.
    This paper sets out the notion of a current “biopolitical turn of digital capitalism” resulting from the increasing deployment of AI and data analytics technologies in the public sector. With applications of AI-based automated decisions currently shifting from the domain of business to customer relations to government to citizen relations, a new form of governance arises that operates through “algorithmic social selection”. Moreover, the paper describes how the ethics of AI is at an impasse concerning these larger societal and socioeconomic (...)
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  • Technology and Moral Vacuums in Just War Theorising.Elke Schwarz - 2018 - Journal of International Political Theory 14 (3):280-298.
    Our contemporary condition is deeply infused with scientific-technological rationales. These influence and shape our ethical reasoning on war, including the moral status of civilians and the moral choices available to us. In this article, I discuss how technology shapes and directs the moral choices available to us by setting parameters for moral deliberation. I argue that technology has moral significance for just war thinking, yet this is often overlooked in attempts to assess who is liable to harm in war and (...)
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  • Just Data? Solidarity and Justice in Data-Driven Medicine.Matthias Braun & Patrik Hummel - 2020 - Life Sciences, Society and Policy 16 (1):1-18.
    This paper argues that data-driven medicine gives rise to a particular normative challenge. Against the backdrop of a distinction between the good and the right, harnessing personal health data towards the development and refinement of data-driven medicine is to be welcomed from the perspective of the good. Enacting solidarity drives progress in research and clinical practice. At the same time, such acts of sharing could—especially considering current developments in big data and artificial intelligence—compromise the right by leading to injustices and (...)
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  • Examination and Diagnosis of Electronic Patient Records and Their Associated Ethics: A Scoping Literature Review.Tim Jacquemard, Colin P. Doherty & Mary B. Fitzsimons - 2020 - BMC Medical Ethics 21 (1):1-13.
    BackgroundElectronic patient record technology is a key enabler for improvements to healthcare service and management. To ensure these improvements and the means to achieve them are socially and ethically desirable, careful consideration of the ethical implications of EPRs is indicated. The purpose of this scoping review was to map the literature related to the ethics of EPR technology. The literature review was conducted to catalogue the prevalent ethical terms, to describe the associated ethical challenges and opportunities, and to identify the (...)
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  • The Needle and the Damage Done: Of Haystacks and Anxious Panopticons.Sarah Logan - 2017 - Big Data and Society 4 (2).
    How should we understand the surveillance state post Snowden? This paper is concerned with the relationship between increased surveillance capacity and state power. The paper begins by analysing two metaphors used in public post Snowden discourse to describe state surveillance practices: the haystack and the panopticon. It argues that these metaphors share a flawed common entailment regarding surveillance, knowledge and power which cannot accurately capture important aspects of state anxiety generated by mass surveillance in an age of big data. The (...)
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  • Algorithmic Affordances for Productive Resistance.Nancy Ettlinger - 2018 - Big Data and Society 5 (1).
    Although overarching if not foundational conceptualizations of digital governance in the field of critical data studies aptly account for and explain subjection, calculated resistance is left conceptually unattended despite case studies that document instances of resistance. I ask at the outset why conceptualizations of digital governance are so bleak, and I argue that all are underscored implicitly by a Deleuzian theory of desire that overlooks agency, defined here in Foucauldian terms. I subsequently conceptualize digital governance as encompassing subjection as well (...)
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  • Beyond Mystery: Putting Algorithmic Accountability in Context.Andrea Ballestero, Baki Cakici & Elizabeth Reddy - 2019 - Big Data and Society 6 (1).
    Critical algorithm scholarship has demonstrated the difficulties of attributing accountability for the actions and effects of algorithmic systems. In this commentary, we argue that we cannot stop at denouncing the lack of accountability for algorithms and their effects but must engage the broader systems and distributed agencies that algorithmic systems exist within; including standards, regulations, technologies, and social relations. To this end, we explore accountability in “the Generated Detective,” an algorithmically generated comic. Taking up the mantle of detectives ourselves, we (...)
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  • Transparency You Can Trust: Transparency Requirements for Artificial Intelligence Between Legal Norms and Contextual Concerns.Aurelia Tamò-Larrieux, Christoph Lutz, Eduard Fosch Villaronga & Heike Felzmann - 2019 - Big Data and Society 6 (1).
    Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We address the topic of transparency in artificial intelligence by integrating legal, social, and ethical aspects. We first investigate the ratio legis of the transparency requirement in the General Data Protection Regulation and its ethical underpinnings, showing its focus on the provision of information and explanation. We then discuss the pitfalls with respect (...)
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  • Manipulate to Empower: Hyper-Relevance and the Contradictions of Marketing in the Age of Surveillance Capitalism.Detlev Zwick & Aron Darmody - 2020 - Big Data and Society 7 (1).
    In this article, we explore how digital marketers think about marketing in the age of Big Data surveillance, automatic computational analyses, and algorithmic shaping of choice contexts. Our starting point is a contradiction at the heart of digital marketing namely that digital marketing brings about unprecedented levels of consumer empowerment and autonomy and total control over and manipulation of consumer decision-making. We argue that this contradiction of digital marketing is resolved via the notion of relevance, which represents what Fredric Jameson (...)
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  • Municipal Surveillance Regulation and Algorithmic Accountability.P. M. Krafft, Michael Katell & Meg Young - 2019 - Big Data and Society 6 (2).
    A wave of recent scholarship has warned about the potential for discriminatory harms of algorithmic systems, spurring an interest in algorithmic accountability and regulation. Meanwhile, parallel concerns about surveillance practices have already led to multiple successful regulatory efforts of surveillance technologies—many of which have algorithmic components. Here, we examine municipal surveillance regulation as offering lessons for algorithmic oversight. Taking the 2017 Seattle Surveillance Ordinance as our primary case study and surveying efforts across five other cities, we describe the features of (...)
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  • Occluded Algorithms.Adam Burke - 2019 - Big Data and Society 6 (2).
    Two definitions of algorithm, their uses, and their implied models of computing in society, are reviewed. The first, termed the structural programming definition, aligns more with usage in computer science, and as the name suggests, the intellectual project of structured programming. The second, termed the systemic definition, is more informal and emerges from ethnographic observations of discussions of software in both professional and everyday settings. Specific examples of locating algorithms within modern codebases are shared, as well as code directly impacting (...)
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  • Listening Without Ears: Artificial Intelligence in Audio Mastering.Thomas Birtchnell - 2018 - Big Data and Society 5 (2).
    Since the inception of recorded music there has been a need for standards and reliability across sound formats and listening environments. The role of the audio mastering engineer is prestigious and akin to a craft expert combining scientific knowledge, musical learning, manual precision and skill, and an awareness of cultural fashions and creative labour. With the advent of algorithms, big data and machine learning, loosely termed artificial intelligence in this creative sector, there is now the possibility of automating human audio (...)
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  • Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability.Mark Coeckelbergh - 2020 - Science and Engineering Ethics 26 (4):2051-2068.
    This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which draws (...)
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  • Robots in the Workplace: a Threat to—or Opportunity for—Meaningful Work?Jilles Smids, Sven Nyholm & Hannah Berkers - 2020 - Philosophy and Technology 33 (3):503-522.
    The concept of meaningful work has recently received increased attention in philosophy and other disciplines. However, the impact of the increasing robotization of the workplace on meaningful work has received very little attention so far. Doing work that is meaningful leads to higher job satisfaction and increased worker well-being, and some argue for a right to access to meaningful work. In this paper, we therefore address the impact of robotization on meaningful work. We do so by identifying five key aspects (...)
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  • Digital Hyperconnectivity and the Self.Rogers Brubaker - 2020 - Theory and Society 49 (5-6):771-801.
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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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  • The Epistemology of Non-distributive Profiles.Patrick Allo - 2020 - Philosophy and Technology 33 (3):379-409.
    The distinction between distributive and non-distributive profiles figures prominently in current evaluations of the ethical and epistemological risks that are associated with automated profiling practices. The diagnosis that non-distributive profiles may coincidentally situate an individual in the wrong category is often perceived as the central shortcoming of such profiles. According to this diagnosis, most risks can be retraced to the use of non-universal generalisations and various other statistical associations. This article develops a top-down analysis of non-distributive profiles in which this (...)
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  • Agency Laundering and Information Technologies.Alan Rubel, Clinton Castro & Adam Pham - 2019 - Ethical Theory and Moral Practice 22 (4):1017-1041.
    When agents insert technological systems into their decision-making processes, they can obscure moral responsibility for the results. This can give rise to a distinct moral wrong, which we call “agency laundering.” At root, agency laundering involves obfuscating one’s moral responsibility by enlisting a technology or process to take some action and letting it forestall others from demanding an account for bad outcomes that result. We argue that the concept of agency laundering helps in understanding important moral problems in a number (...)
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  • The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning (...)
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  • Artificial Intelligence and Patient-Centered Decision Making.Jens Christian Bjerring & Jacob Busch - forthcoming - Philosophy and Technology:1-23.
    Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: ​the details of their contents, calculations, (...)
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  • Understanding and Managing Responsible Innovation.Hans Bennink - 2020 - Philosophy of Management 19 (3):317-348.
    As a relational concept, responsible innovation can be made more tangible by asking innovation of what and responsibility of whom for what? Arranging the scattered field of responsible innovation comprehensively, starting from an anthropological point of view, into five fields of tension and five categories of spearheads, may be theoretically and practically helpful while offering suggestions for both research and management.
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  • Democratizing Algorithmic Fairness.Pak-Hang Wong - 2020 - Philosophy and Technology 33 (2):225-244.
    Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While researchers have (...)
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  • The Digital Phenotype: A Philosophical and Ethical Exploration.Michele Loi - 2019 - Philosophy and Technology 32 (1):155-171.
    The concept of the digital phenotype has been used to refer to digital data prognostic or diagnostic of disease conditions. Medical conditions may be inferred from the time pattern in an insomniac’s tweets, the Facebook posts of a depressed individual, or the web searches of a hypochondriac. This paper conceptualizes digital data as an extended phenotype of humans, that is as digital information produced by humans and affecting human behavior and culture. It argues that there are ethical obligations to persons (...)
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  • Artificial Intelligence and Medical Humanities.Kirsten Ostherr - forthcoming - Journal of Medical Humanities:1-22.
    The use of artificial intelligence in healthcare has led to debates about the role of human clinicians in the increasingly technological contexts of medicine. Some researchers have argued that AI will augment the capacities of physicians and increase their availability to provide empathy and other uniquely human forms of care to their patients. The human vulnerabilities experienced in the healthcare context raise the stakes of new technologies such as AI, and the human dimensions of AI in healthcare have particular significance (...)
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  • Enculturating Algorithms.Rafael Capurro - 2019 - NanoEthics 13 (2):131-137.
    The paper deals with the difference between who and what we are in order to take an ethical perspective on algorithms and their regulation. The present casting of ourselves as homo digitalis implies the possibility of projecting who we are as social beings sharing a world, into the digital medium, thereby engendering what can be called digital whoness, or a digital reification of ourselves. A main ethical challenge for the evolving digital age consists in unveiling this ethical difference, particularly when (...)
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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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  • 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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  • The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity.Ulrich Leicht-Deobald, Thorsten Busch, Christoph Schank, Antoinette Weibel, Simon Schafheitle, Isabelle Wildhaber & Gabriel Kasper - 2019 - Journal of Business Ethics 160 (2):377-392.
    Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it may shift the delicate balance between employees’ personal integrity and compliance more in the direction of compliance. We suggest that critical data literacy, ethical awareness, the use of participatory (...)
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  • On Social Machines for Algorithmic Regulation.Nello Cristianini & Teresa Scantamburlo - manuscript
    Autonomous mechanisms have been proposed to regulate certain aspects of society and are already being used to regulate business organisations. We take seriously recent proposals for algorithmic regulation of society, and we identify the existing technologies that can be used to implement them, most of them originally introduced in business contexts. We build on the notion of 'social machine' and we connect it to various ongoing trends and ideas, including crowdsourced task-work, social compiler, mechanism design, reputation management systems, and social (...)
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  • Toward an Ethics of AI Assistants: An Initial Framework.John Danaher - 2018 - Philosophy and Technology 31 (4):629-653.
    Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...)
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  • Ethics of the Health-Related Internet of Things: A Narrative Review.Brent Mittelstadt - 2017 - Ethics and Information Technology 19 (3):1-19.
    The internet of things is increasingly spreading into the domain of medical and social care. Internet-enabled devices for monitoring and managing the health and well-being of users outside of traditional medical institutions have rapidly become common tools to support healthcare. Health-related internet of things (H-IoT) technologies increasingly play a key role in health management, for purposes including disease prevention, real-time tele-monitoring of patient’s functions, testing of treatments, fitness and well-being monitoring, medication dispensation, and health research data collection. H-IoT promises many (...)
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  • Mental Time-Travel, Semantic Flexibility, and A.I. Ethics.Marcus Arvan - forthcoming - AI and Society:1-20.
    This article argues that existing approaches to programming ethical AI fail to resolve a serious moral-semantic trilemma, generating interpretations of ethical requirements that are either too semantically strict, too semantically flexible, or overly unpredictable. This paper then illustrates the trilemma utilizing a recently proposed ‘general ethical dilemma analyzer,’ _GenEth_. Finally, it uses empirical evidence to argue that human beings resolve the semantic trilemma using general cognitive and motivational processes involving ‘mental time-travel,’ whereby we simulate different possible pasts and futures. I (...)
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  • Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2019 - Philosophy and Technology 32 (4):661-683.
    We are sceptical of concerns over the opacity of algorithmic decision tools. While transparency and explainability are certainly important desiderata in algorithmic governance, we worry that automated decision-making is being held to an unrealistically high standard, possibly owing to an unrealistically high estimate of the degree of transparency attainable from human decision-makers. In this paper, we review evidence demonstrating that much human decision-making is fraught with transparency problems, show in what respects AI fares little worse or better and argue that (...)
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