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Big Data, Health Law, and Bioethics
When data from all aspects of our lives can be relevant to our health - from our habits at the grocery store and our Google searches to our FitBit data and our medical records - can we really differentiate between big data and health big data? Will health big data be used for good, such as to improve drug safety, or ill, as in insurance discrimination? Will it disrupt health care (and the health care system) as we know it? Will it be possible to protect our health privacy? What barriers will there be to collecting and utilizing health big data? What role should law play, and what ethical concerns may arise? This timely, groundbreaking volume explores these questions and more from a variety of perspectives, examining how law promotes or discourages the use of big data in the health care sphere, and also what we can learn from other sectors.
Reprogen-Ethics and the Future of Gender
'Reprogen-Ethics and the Future of Gender' brings together three tightly related topics, which have so far been dealt separately in bioethics: assisted reproduction, enhancing and gender. Part one in this book targets present policies and legislature of assisted reproduction. Part two focuses on current views of the ethics of PGD and enhancing. Part three tackles the future of gender. Part four deals with artificial wombs and ectogenesis. The aim of this book is to provide a joint perspective in order to get the big picture. Contributors include Matti Häyry, Tuija Takala, Søren Holm, David Heyd, Daniel Callahan, Harriet Bradley, Ekaterina Balabanova and others. Some chapters in this book will significantly contribute to the current discussion of the topics at stake; other chapters will start a discussion on issues that have not yet been discussed. 'Reprogen-Ethics and the Future of Gender' will certainly appeal to readers who are interested in any of the intersecting topics of assisted reproduction, genetic enhancing and gender; bioethicists, sociologists, genetic counsellors, gynaecologists, legislators, and students of the relevant disciplines.
The Ethical Governance of Artificial Intelligence and Machine Learning in Healthcare
This book explores the ethical governance of Artificial Intelligence (AI) & Machine Learning (ML) in healthcare. AI/ML usage in healthcare as well as our daily lives is not new. However, the direct, and oftentimes long-term effects of current technologies, in addition to the onset of future innovations, have caused much debate about the safety of AI/ML. On the one hand, AI/ML has the potential to provide effective and efficient care to patients, and this sways the argument in favor of continuing to use AI/ML; but on the other hand, the dangers (including unforeseen future consequences of the further development of the technology) leads to vehement disagreement with further AI/ML usage. Due to its potential for beneficial outcomes, the book opts to push for ethical AI/ML to be developed and examines various areas in healthcare, such as big data analytics and clinical decision-making, to uncover and discuss the importance of developing ethical governance for AI/ML in this setting.
Ethics and governance of artificial intelligence for health
This WHO Guidance document discusses ethical and governance issues as they arise in the use of artificial intelligence (AI) for health. It contains a set of principles, recommendations, and checklists for selected end-users. The target audience is Ministries of Health, AI developers, health care workers, and industry.
Reproductive Donation
Reproductive donation is the most contentious area of assisted reproduction. Even within Europe there are wide variations in what is permitted in each country. This multidisciplinary book takes a fresh look at the practices of egg, sperm and embryo donation and surrogacy, bringing together ethical analysis and empirical research. New evidence is offered on aspects of assisted reproduction and the families these create, including non-traditional types. One of the key issues addressed is should children be told of their donor origin? If they do learn the identity of their donor, what kinds of relationships may be forged between families, the donor and other donor sibling families? Should donation involve a gift relationship? Is intra-familial donation too close for comfort? How should we understand the growing trend for 'reproductive tourism'? This lively and informed discussion offers new insights into reproductive donation and the resulting donor families.
Genomics and the Reimagining of Personalized Medicine
Drawing on insights from work in medical history and sociology, this book analyzes changing meanings of personalized medicine over time, from the rise of biomedicine in the twentieth century, to the emergence of pharmacogenomics and personal genomics in the 1990s and 2000s. In the past when doctors championed personalization they did so to emphasize that patients had unique biographies and social experiences in the name of caring for their patients as individuals. However, since the middle of the twentieth century, geneticists have successfully promoted the belief that genes are implicated in why some people develop diseases and why some have adverse reactions to drugs when others do not. In...
Ethics and governance of artificial intelligence for health: large multi-modal models. WHO guidance
Artificial Intelligence (AI) refers to the capability of algorithms integrated into systems and tools to learn from data so that they can perform automated tasks without explicit programming of every step by a human. Generative AI is a category of AI techniques in which algorithms are trained on data sets that can be used to generate new content, such as text, images or video. This guidance addresses one type of generative AI, large multi-modal models (LMMs), which can accept one or more type of data input and generate diverse outputs that are not limited to the type of data fed into the algorithm. It has been predicted that LMMs will have wide use and application in health care, scientific research, public health and drug development. LMMs are also known as “general-purpose foundation models”, although it is not yet proven whether LMMs can accomplish a wide range of tasks and purposes.
The Ethics of Biomedical Big Data
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.
Oxford Handbook of Digital Ethics
"The Oxford Handbook of Digital Ethics is a lively and authoritative guide to ethical issues related to digital technologies, with a special emphasis on AI. Philosophers with a wide range of expertise cover thirty-seven topics: from the right to have access to internet, to trolling and online shaming, speech on social media, fake news, sex robots and dating online, persuasive technology, value alignment, algorithmic bias, predictive policing, price discrimination online, medical AI, privacy and surveillance, automating democracy, the future of work, and AI and existential risk, among others. Each chapter gives a rigorous map of the ethical terrain, engaging critically with the most notable work in the area, and pointing directions for future research"--
Digitalization and the Welfare State
This volume explores how digitalization--in different forms--affects the welfare state. Digitalization is likely to have a lasting impact on work, welfare, and the distribution of income. It will radically transform not only social risks in health, education and the labour market, but also the means by which these risks are addressed. The volume studies how digitalization affects policies as well as the underlying power relationship between actors, i.e. the politics of the welfare state. The volume brings together internationally renowned welfare-state scholars to identify - the socio-economic challenges that result from rapid technological change; - the ensuing political conflicts and strug...
