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The author investigates how to produce realistic and workable ethical codes or regulations in this rapidly developing field to address the immediate and realistic longer-term issues facing us. She spells out the key ethical debates concisely, exposing all sides of the arguments, and addresses how codes of ethics or other regulations might feasibly be developed, looking for pitfalls and opportunities, drawing on lessons learned in other fields, and explaining key points of professional ethics. The book provides a useful resource for those aiming to address the ethical challenges of AI research in meaningful and practical ways.
This book introduces readers to critical ethical concerns in the development and use of artificial intelligence. Offering clear and accessible information on central concepts and debates in AI ethics, it explores how related problems are now forcing us to address fundamental, age-old questions about human life, value, and meaning. In addition, the book shows how foundational and theoretical issues relate to concrete controversies, with an emphasis on understanding how ethical questions play out in practice. All topics are explored in depth, with clear explanations of relevant debates in ethics and philosophy, drawing on both historical and current sources. Questions in AI ethics are explored...
New developments in science and technology have resulted in shifting ethical challenges in many areas including in genomics research. This book enables those who are involved in genomics research, whether as researcher, participant or policy maker, to understand the ethical issues currently developing in this field and to participate actively in these important debates. A clear account is given of how science and technology are outstripping the capacity of previous ethical regulations to cope with current issues, together with practical illustrations of possible ways forward. Key ethical ideas are presented, drawing on the history of research regulation and on an account of the particular ch...
An argument that moral functioning is immeasurably complex, mediated by biology but not determined by it. Throughout history, humanity has been seen as being in need of improvement, most pressingly in need of moral improvement. Today, in what has been called the beginnings of “the golden age of neuroscience,” laboratory findings claim to offer insights into how the brain “does” morality, even suggesting that it is possible to make people more moral by manipulating their biology. Can “moral bioenhancement”—using technological or pharmaceutical means to boost the morally desirable and remove the morally problematic—bring about a morally improved humanity? In The Myth of the Mor...
This interdisciplinary and international handbook captures and shapes much needed reflection on normative frameworks for the production, application, and use of artificial intelligence in all spheres of individual, commercial, social, and public life.
Public health is a particular area of medical practice that raises a series of philosophical issues that require urgent discussion. The philosophy of public health includes metaphysical questions such as, what do we mean by 'public' in public health? How ought we to conceptualise the idea of 'populations'? Are they merely aggregations of individuals? It also includes epistemological questions such as, what methods are most appropriate for thinking about public health? How do empirical and normative issues relate to each other? Controversial ethical, political and social issues, including those relating to vaccinations, the threat of pandemics and possible restrictions to individual liberties, public health research, screening and obesity policy should also be considered. This volume includes a diverse set of papers exploring a number of the most important theoretical and practical issues that arise across the whole field of the philosophy of public health.
Contributions to this study are drawn both from health professionals engaged in genetic counselling and from observers and critics with backgrounds in law, philosophy, biology, and the social sciences. This diversity will enable health professonals to examine their activities with a fresh eye, and will help the observer-critic to understand the ethical problems that arise in genetic counselling practice, rather than in imaginary encounters. Most examinations of the ethical issues raised by genetics are concerned in a broad sense with the application of new technology to human reproduction. This volume focuses on genetic counselling and screening as such, providing valuable insights for the health professional, social scientist, philosopher, lawyer, and bioethicist.
Summary Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful e...
This book is a collection of papers presented and discussed at the 1992 Claremont Conference. Its contributing authors come from various disciplines that share a concern with models and criteria for inter-religious understanding, including religious studies, philosophy of religion, theology, comparative studies, and feminist philosophy.
This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.