Titlebook: Ethical Reasoning in Big Data; An Exploratory Analy Jeff Collmann,Sorin Adam Matei Book 2016 Springer International Publishing Switzerland

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Neurotechnological Convergence and “Big Data”: A Force-Multiplier Toward Advancing Neuroscience validity (b) adequate probabilistic inference, and (c) reliability. However big data employment in brain sciences also incurs a number of ethico-legal issues, and these are addressed, and approaches toward their resolution are discussed.

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Integrating Ethical Reasoning into Preparation for Participation to Work in/with Big Data Through th: (1) disciplines and fields are dynamic, and . stewardship; (2) the quality and integrity of disciplines must be actively preserved and conserved; and (3) there are particular habits of mind that characterize “those to whom we can entrust” the core features of a discipline or field. In order to for

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2509-9574 s, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in a978-3-319-80351-7978-3-319-28422-4Series ISSN 2509-9574 Series E-ISSN 2509-9582

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Book 2016ical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in a

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2509-9574 ing of big data.Discusses methods for individual and organizThis book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public’s trust in t

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https://doi.org/10.1007/978-3-642-94483-3and companies when they find deficiencies in personal data protection; being explicit about the insights they are gaining from their analysis and the benefits those insights yield; and pressing for legal regimes that minimize potential harms that could emerge from big data.