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  1. Evaluating the prospects for university-based ethical governance in artificial intelligence and data-driven innovation.Christine Hine - 2021 - Research Ethics 17 (4):464-479.
    There has been considerable debate around the ethical issues raised by data-driven technologies such as artificial intelligence. Ethical principles for the field have focused on the need to ensure...
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  • Unprepared humanities: A pedagogy (forced) online.Houman Harouni - 2021 - Journal of Philosophy of Education 55 (4-5):633-648.
    Journal of Philosophy of Education, EarlyView.
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  • Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective.Erik Hermann - 2022 - Journal of Business Ethics 179 (1):43-61.
    Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To (...)
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  • Varieties of artifacts: Embodied, perceptual, cognitive, and affective.Richard Heersmink - 2021 - Topics in Cognitive Science (4):1-24.
    The primary goal of this essay is to provide a comprehensive overview and analysis of the various relations between material artifacts and the embodied mind. A secondary goal of this essay is to identify some of the trends in the design and use of artifacts. First, based on their functional properties, I identify four categories of artifacts co-opted by the embodied mind, namely (1) embodied artifacts, (2) perceptual artifacts, (3) cognitive artifacts, and (4) affective artifacts. These categories can overlap 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 - 2021 - Philosophy and Technology 34 (4):1057-1084.
    The notion of “responsibility gap” with artificial intelligence (AI) 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 (...)
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  • The Ethical Gravity Thesis: Marrian Levels and the Persistence of Bias in Automated Decision-making Systems.Atoosa Kasirzadeh & Colin Klein - 2021 - Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES '21).
    Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not ameliorate more (...)
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  • Near-term ethical challenges of digital twins.Brent Mittelstadt - 2021 - Journal of Medical Ethics 47 (6):405-406.
    In ‘Represent me: please! Towards an ethics of digital twins in medicine’,1 Braun analyses the potential for simulations of human organs and bodies, or ‘digital twins,’ to faithfully a person. Drawing from several French philosophers, he introduces ‘first conditions for digital twins to take on an ethically justifiable form of representation’.1 The analysis predominantly focuses on challenges that arise in terms of representation, embodiment, control by the patients after which the twin is modelled. Many challenges are posited on the existence (...)
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  • Problems with “Friendly AI”.Oliver Li - 2021 - Ethics and Information Technology 23 (3):543-550.
    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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  • 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: (1) (in)tolerance for ambiguity, and (2) instantiations of Campbell’s law, i. e. of indicators that are used for “social decision-making” being (...)
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  • Political machines: a framework for studying politics in social machines.Orestis Papakyriakopoulos - 2022 - AI and Society 37 (1):113-130.
    In the age of ubiquitous computing and artificially intelligent applications, social machines serves as a powerful framework for understanding and interpreting interactions in socio-algorithmic ecosystems. Although researchers have largely used it to analyze the interactions of individuals and algorithms, limited attempts have been made to investigate the politics in social machines. In this study, I claim that social machines are per se political machines, and introduce a five-point framework for classifying influence processes in socio-algorithmic ecosystems. By drawing from scholars from (...)
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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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  • Discrimination in the age of artificial intelligence.Bert Heinrichs - 2022 - AI and Society 37 (1):143-154.
    In this paper, I examine whether the use of artificial intelligence (AI) and automated decision-making (ADM) aggravates issues of discrimination as has been argued by several authors. For this purpose, I first take up the lively philosophical debate on discrimination and present my own definition of the concept. Equipped with this account, I subsequently review some of the recent literature on the use AI/ADM and discrimination. I explain how my account of discrimination helps to understand that the general claim in (...)
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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 - 2021 - Health Care Analysis 29 (3):171-188.
    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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  • Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI.Juan Manuel Durán & Karin Rolanda Jongsma - 2021 - Journal of Medical Ethics 47 (5):medethics - 2020-106820.
    The use of black box algorithms in medicine has raised scholarly concerns due to their opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and responsibility, patient autonomy and compromised trust transpire with black box algorithms. These worries connect epistemic concerns with normative issues. In this paper, we outline that black box algorithms are less problematic for epistemic reasons than many scholars seem to believe. By outlining that more transparency in algorithms is not always necessary, and by explaining that (...)
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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 - 2022 - AI and Society 37 (1):97-112.
    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 (Dietvorst et al. J Exp Psychol 144(1):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 (...)
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  • 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 (AI) technologies (BD + AI)—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, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety (...)
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  • The Influence of Business Incentives and Attitudes on Ethics Discourse in the Information Technology Industry.Sanju Ahuja & Jyoti Kumar - 2021 - Philosophy and Technology 34 (4):941-966.
    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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  • Care ethics and the responsible management of power and privacy in digitally enhanced disaster response.Paul Hayes & Damian Jackson - 2020 - Journal of Information, Communication and Ethics in Society 18 (1):157-174.
    PurposeThis paper aims to argue that traditional ethical theories used in disaster response may be inadequate and particularly strained by the emergence of new technologies and social media, particularly with regard to privacy. The paper suggests incorporation of care ethics into the disaster ethics nexus to better include the perspectives of disaster affected communities.Design/methodology/approachThis paper presents a theoretical examination of privacy and care ethics in the context of social media/digitally enhanced disaster response.FindingsThe paper proposes an ethics of care can fruitfully (...)
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  • The ethics of algorithms: key problems and solutions.Andreas Tsamados, Nikita Aggarwal, Josh Cowls, Jessica Morley, Huw Roberts, Mariarosaria Taddeo & Luciano Floridi - 2021 - AI and Society.
    Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...)
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  • What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research.Markus Langer, Daniel Oster, Timo Speith, Lena Kästner, Kevin Baum, Holger Hermanns, Eva Schmidt & Andreas Sesing - 2021 - Artificial Intelligence 296 (C):103473.
    Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, and demands regarding artificial systems (we call these “stakeholders' desiderata”) in a variety of contexts. However, the literature on XAI is vast, spreads out across multiple largely disconnected disciplines, and it often remains unclear how explainability approaches are supposed to achieve the goal of satisfying stakeholders' desiderata. This paper discusses the main classes of stakeholders calling for explainability (...)
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  • Making the black box society transparent.Daniel Innerarity - forthcoming - AI and Society:1-7.
    The growing presence of smart devices in our lives turns all of society into something largely unknown to us. The strategy of demanding transparency stems from the desire to reduce the ignorance to which this automated society seems to condemn us. An evaluation of this strategy first requires that we distinguish the different types of non-transparency. Once we reveal the limits of the transparency needed to confront these devices, the article examines the alternative strategy of explainable artificial intelligence and concludes (...)
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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 (B2C) relations to government to citizen (G2C) 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 (...)
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  • The algorithm audit: Scoring the algorithms that score us.Jovana Davidovic, Shea Brown & Ali Hasan - 2021 - Big Data and Society 8 (1).
    In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not (...)
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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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  • 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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  • 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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  • 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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  • Perceptual bias and technical metapictures: critical machine vision as a humanities challenge.Fabian Offert & Peter Bell - forthcoming - AI and Society.
    In many critical investigations of machine vision, the focus lies almost exclusively on dataset bias and on fixing datasets by introducing more and more diverse sets of images. We propose that machine vision systems are inherently biased not only because they rely on biased datasets but also because theirperceptual topology, their specific way of representing the visual world, gives rise to a new class of bias that we callperceptual bias. Concretely, we define perceptual topology as the set of those inductive (...)
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  • Getting into the engine room: a blueprint to investigate the shadowy steps of AI ethics.Johan Rochel & Florian Evéquoz - 2021 - AI and Society 36 (2):609-622.
    Enacting an AI system typically requires three iterative phases where AI engineers are in command: selection and preparation of the data, selection and configuration of algorithmic tools, and fine-tuning of the different parameters on the basis of intermediate results. Our main hypothesis is that these phases involve practices with ethical questions. This paper maps these ethical questions and proposes a way to address them in light of a neo-republican understanding of freedom, defined as absence of domination. We thereby identify different (...)
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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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  • Ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations.Kristina Astromskė, Eimantas Peičius & Paulius Astromskis - 2021 - AI and Society 36 (2):509-520.
    This paper inquiries into the complex issue of informed consent applying artificial intelligence in medical diagnostic consultations. The aim is to expose the main ethical and legal concerns of the New Health phenomenon, powered by intelligent machines. To achieve this objective, the first part of the paper analyzes ethical aspects of the alleged right to explanation, privacy, and informed consent, applying artificial intelligence in medical diagnostic consultations. This analysis is followed by a legal analysis of the limits and requirements for (...)
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  • Digital hyperconnectivity and the self.Rogers Brubaker - 2020 - Theory and Society 49 (5-6):771-801.
    Digital hyperconnectivity is a defining fact of our time. In addition to recasting social interaction, culture, economics, and politics, it has profoundly transformed the self. It has created new ways of being and constructing a self, but also new ways of being constructed as a self from the outside, new ways of being configured, represented, and governed as a self by sociotechnical systems. Rather than analyze theories of the self, I focus on practices of the self, using this expression in (...)
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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 (EPR) 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 (...)
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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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  • Artificial Intelligence and Medical Humanities.Kirsten Ostherr - 2020 - Journal of Medical Humanities 43 (2):211-232.
    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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  • A taxonomy of human–machine collaboration: capturing automation and technical autonomy.Monika Simmler & Ruth Frischknecht - 2021 - AI and Society 36 (1):239-250.
    Due to the ongoing advancements in technology, socio-technical collaboration has become increasingly prevalent. This poses challenges in terms of governance and accountability, as well as issues in various other fields. Therefore, it is crucial to familiarize decision-makers and researchers with the core of human–machine collaboration. This study introduces a taxonomy that enables identification of the very nature of human–machine interaction. A literature review has revealed that automation and technical autonomy are main parameters for describing and understanding such interaction. Both aspects (...)
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  • Can Finance Be a Virtuous Practice? A MacIntyrean Account.Marta Rocchi, Ignacio Ferrero & Ron Beadle - 2021 - Business Ethics Quarterly 31 (1):75-105.
    ABSTRACTFinance may suffer from institutional deformations that subordinate its distinctive goods to the pursuit of external goods, but this should encourage attempts to reform the institutionalization of finance rather than to reject its potential for virtuous business activity. This article argues that finance should be regarded as a domain-relative practice. Alongside management, its moral status thereby varies with the purposes it serves. Hence, when practitioners working in finance facilitate projects that create common goods, it allows them to develop virtues. This (...)
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  • The explanation game: a formal framework for interpretable machine learning.David S. Watson & Luciano Floridi - 2020 - Synthese 198 (10):1–⁠32.
    We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...)
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  • Automated Influence and the Challenge of Cognitive Security.Sarah Rajtmajer & Daniel Susser - forthcoming - HoTSoS: ACM Symposium on Hot Topics in the Science of Security.
    Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of “cognitive security,” we argue, offers a promising approach.
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  • Algorithms and values in justice and security.Paul Hayes, Ibo van de Poel & Marc Steen - 2020 - AI and Society 35 (3):533-555.
    This article presents a conceptual investigation into the value impacts and relations of algorithms in the domain of justice and security. As a conceptual investigation, it represents one step in a value sensitive design based methodology. Here, we explicate and analyse the expression of values of accuracy, privacy, fairness and equality, property and ownership, and accountability and transparency in this context. We find that values are sensitive to disvalue if algorithms are designed, implemented or deployed inappropriately or without sufficient consideration (...)
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  • Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
    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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  • 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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  • Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2018 - 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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  • Ethical concerns with the use of intelligent assistive technology: findings from a qualitative study with professional stakeholders.Tenzin Wangmo, Mirjam Lipps, Reto W. Kressig & Marcello Ienca - 2019 - BMC Medical Ethics 20 (1):1-11.
    Background Advances in artificial intelligence, robotics and wearable computing are creating novel technological opportunities for mitigating the global burden of population ageing and improving the quality of care for older adults with dementia and/or age-related disability. Intelligent assistive technology is the umbrella term defining this ever-evolving spectrum of intelligent applications for the older and disabled population. However, the implementation of IATs has been observed to be sub-optimal due to a number of barriers in the translation of novel applications from the (...)
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