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  1. Ethical Issues in Consent for the Reuse of Data in Health Data Platforms.Alex McKeown, Miranda Mourby, Paul Harrison, Sophie Walker, Mark Sheehan & Ilina Singh - 2021 - Science and Engineering Ethics 27 (1):1-21.
    Data platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate model for facilitating (...)
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  • Recommender systems and their ethical challenges.Silvia Milano, Mariarosaria Taddeo & Luciano Floridi - 2020 - AI and Society (4):957-967.
    This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.
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  • Surveillance, security, and AI as technological acceptance.Yong Jin Park & S. Mo Jones-Jang - 2023 - AI and Society 38 (6):2667-2678.
    Public consumption of artificial intelligence (AI) technologies has been rarely investigated from the perspective of data surveillance and security. We show that the technology acceptance model, when properly modified with security and surveillance fears about AI, builds an insight on how individuals begin to use, accept, or evaluate AI and its automated decisions. We conducted two studies, and found positive roles of perceived ease of use (PEOU) and perceived usefulness (PU). AI security concern, however, negatively affected PEOU and PU, resulting (...)
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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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  • Scraping the Web for Public Health Gains: Ethical Considerations from a ‘Big Data’ Research Project on HIV and Incarceration.Stuart Rennie, Mara Buchbinder, Eric Juengst, Lauren Brinkley-Rubinstein, Colleen Blue & David L. Rosen - 2020 - Public Health Ethics 13 (1):111-121.
    Web scraping involves using computer programs for automated extraction and organization of data from the Web for the purpose of further data analysis and use. It is frequently used by commercial companies, but also has become a valuable tool in epidemiological research and public health planning. In this paper, we explore ethical issues in a project that “scrapes” public websites of U.S. county jails as part of an effort to develop a comprehensive database to enhance HIV surveillance and improve continuity (...)
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