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  1. What is Public Health?Jonathan Anomaly - 2021 - Public Choice 188.
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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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  • How to design AI for social good: seven essential factors.Luciano Floridi, Josh Cowls, Thomas C. King & Mariarosaria Taddeo - 2020 - Science and Engineering Ethics 26 (3):1771–1796.
    The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that are (...)
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  • Mapping Value Sensitive Design onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1 (3):283–296.
    Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML (...)
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  • AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations.Luciano Floridi, Josh Cowls, Monica Beltrametti, Raja Chatila, Patrice Chazerand, Virginia Dignum, Christoph Luetge, Robert Madelin, Ugo Pagallo, Francesca Rossi, Burkhard Schafer, Peggy Valcke & Effy Vayena - 2018 - Minds and Machines 28 (4):689-707.
    This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other (...)
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  • An Analysis of the Interaction Between Intelligent Software Agents and Human Users.Christopher Burr, Nello Cristianini & James Ladyman - 2018 - Minds and Machines 28 (4):735-774.
    Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...)
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  • Exacerbating Inequalities? Health Policy and the Behavioural Sciences.Kathryn MacKay & Muireann Quigley - 2018 - Health Care Analysis 26 (4):380-397.
    There have been calls for some time for a new approach to public health in the United Kingdom and beyond. This is consequent on the recognition and acceptance that health problems often have a complex and multi-faceted aetiology. At the same time, policies which utilise insights from research in behavioural economics and psychology have gained prominence on the political agenda. The relationship between the social determinants of health and behavioural science in health policy has not hitherto been explored. Given the (...)
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  • A Value-Sensitive Design Approach to Intelligent Agents.Steven Umbrello & Angelo Frank De Bellis - 2018 - In Yampolskiy Roman (ed.), Artificial Intelligence Safety and Security. CRC Press. pp. 395-410.
    This chapter proposed a novel design methodology called Value-Sensitive Design and its potential application to the field of artificial intelligence research and design. It discusses the imperatives in adopting a design philosophy that embeds values into the design of artificial agents at the early stages of AI development. Because of the high risk stakes in the unmitigated design of artificial agents, this chapter proposes that even though VSD may turn out to be a less-than-optimal design methodology, it currently provides a (...)
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  • Service robots, care ethics, and design.A. van Wynsberghe - 2016 - Ethics and Information Technology 18 (4):311-321.
    It should not be a surprise in the near future to encounter either a personal or a professional service robot in our homes and/or our work places: according to the International Federation for Robots, there will be approx 35 million service robots at work by 2018. Given that individuals will interact and even cooperate with these service robots, their design and development demand ethical attention. With this in mind I suggest the use of an approach for incorporating ethics into the (...)
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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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  • (2 other versions)Meaningful Human Control over Smart Home Systems: A Value Sensitive Design Approach.Steven Umbrello - 2020 - Humana.Mente Journal of Philosophical Studies 13 (37):40-65.
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control over (...)
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  • Against the Public Goods Conception of Public Health.Justin Bernstein & Pierce Randall - 2020 - Public Health Ethics 13 (3):225-233.
    Public health ethicists face two difficult questions. First, what makes something a matter of public health? While protecting citizens from outbreaks of communicable diseases is clearly a matter of public health, is the same true of policies that aim to reduce obesity, gun violence or political corruption? Second, what should the scope of the government’s authority be in promoting public health? May government enact public health policies some citizens reasonably object to or policies that are paternalistic? Recently, some theorists have (...)
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  • Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus Explainability.Alex John London - 2019 - Hastings Center Report 49 (1):15-21.
    Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or (...)
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  • Demandingness and Public Health Ethics.Julian Savulescu & Alberto Giubilini - 2019 - Moral Philosophy and Politics 6 (1):65-87.
    Public health policies often require individuals to make personal sacrifices for the sake of protecting other individuals or the community at large. Such requirements can be more or less demanding for individuals. This paper examines the implications of demandingness for public health ethics and policy. It focuses on three possible public health policies that pose requirements that are differently demanding: vaccination policies, policy to contain antimicrobial resistance, and quarantine and isolation policies. Assuming the validity of the ‘demandingness objection’ in ethics, (...)
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  • From hostile worlds to multiple spheres: towards a normative pragmatics of justice for the Googlization of health.Tamar Sharon - 2021 - Medicine, Health Care and Philosophy 24 (3):315-327.
    The datafication and digitalization of health and medicine has engendered a proliferation of new collaborations between public health institutions and data corporations like Google, Apple, Microsoft and Amazon. Critical perspectives on these new partnerships tend to frame them as an instance of market transgressions by tech giants into the sphere of health and medicine, in line with a “hostile worlds” doctrine that upholds that the borders between market and non-market spheres should be carefully policed. This article seeks to outline the (...)
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  • From Libertarian Paternalism to Nudging—and Beyond.Adrien Barton & Till Grüne-Yanoff - 2015 - Review of Philosophy and Psychology 6 (3):341-359.
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  • The Institutional Consequences of Nudging – Nudges, Politics, and the Law.Robert Lepenies & Magdalena Małecka - 2015 - Review of Philosophy and Psychology 6 (3):427-437.
    In this article we argue that a widespread adoption of nudging can alter legal and political institutions. Debates on nudges thus far have largely revolved around a set of philosophical theories that we call individualistic approaches. Our analysis concerns the ways in which adherents of nudging make use of the newest findings in the behavioral sciences for the purposes of policy-making. We emphasize the fact that most nudges proposed so far are not a part of the legal system and are (...)
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  • Doctors, Patients, and Nudging in the Clinical Context—Four Views on Nudging and Informed Consent.Thomas Ploug & Søren Holm - 2015 - American Journal of Bioethics 15 (10):28-38.
    In an analysis of recent work on nudging we distinguish three positions on the relationship between nudging founded in libertarian paternalism and the protection of personal autonomy through informed consent. We argue that all three positions fail to provide adequate protection of personal autonomy in the clinical context. Acknowledging that nudging may be beneficial, we suggest a fourth position according to which nudging and informed consent are valuable in different domains of interaction.
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  • (2 other versions)Meaningful Human Control Over Smart Home Systems: A Value Sensitive Design Approach.Steven Umbrello - 2020 - Humana.Mente Journal of Philosophical Studies 13 (37):40-65.
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control over (...)
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  • A paradigm shift for robot ethics: from HRI to human–robot–system interaction.Aimee van Wynsberghe & Shuhong Li - 2019 - Medicolegal and Bioethics:11-21.
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  • In Defense of Nudge–Autonomy Compatibility.J. S. Blumenthal-Barby & Aanand D. Naik - 2015 - American Journal of Bioethics 15 (10):45-47.
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  • Nudging, informed consent and bullshit.William Simkulet - 2018 - Journal of Medical Ethics 44 (8):536-542.
    Some philosophers have argued that during the process of obtaining informed consent, physicians should try to nudge their patients towards consenting to the option the physician believes best, where a nudge is any influence that is expected to predictably alter a person’s behaviour without restricting her options. Some proponents of nudging even argue that it is a necessary and unavoidable part of securing informed consent. Here I argue that nudging is incompatible with obtaining informed consent. I assume informed consent requires (...)
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  • Behavioral economics as neoliberalism: Producing and governing homo economicus.John McMahon - 2015 - Contemporary Political Theory 14 (2):137-158.
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  • Twenty years of value sensitive design: a review of methodological practices in VSD projects. [REVIEW]Till Winkler & Sarah Spiekermann - 2018 - Ethics and Information Technology 23 (1):17-21.
    This article reviews the academic literature that emerged under value sensitive design. It investigates those VSD projects that employed the tripartite methodology, examining the use of VSD methodological elements, and illustrating common practices and identifying shortcomings. The article provides advice for VSD researchers on how to complete and enhance their methodological approach as the research community moves forward.
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