Machine Medical Ethics


Book Description

The essays in this book, written by researchers from both humanities and science, describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility in medical contexts, and accurately modeling essential physician-machine-patient relationships. In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? This collection is the first book that addresses these 21st-century concerns.




Machine Ethics


Book Description

The new field of machine ethics is concerned with giving machines ethical principles, or a procedure for discovering a way to resolve the ethical dilemmas they might encounter, enabling them to function in an ethically responsible manner through their own ethical decision making. Developing ethics for machines, in contrast to developing ethics for human beings who use machines, is by its nature an interdisciplinary endeavor. The essays in this volume represent the first steps by philosophers and artificial intelligence researchers toward explaining why it is necessary to add an ethical dimension to machines that function autonomously, what is required in order to add this dimension, philosophical and practical challenges to the machine ethics project, various approaches that could be considered in attempting to add an ethical dimension to machines, work that has been done to date in implementing these approaches, and visions of the future of machine ethics research.




Moral Machines


Book Description

"Moral Machines is a fine introduction to the emerging field of robot ethics. There is much here that will interest ethicists, philosophers, cognitive scientists, and roboticists." ---Peter Danielson, Notre Dame Philosophical Reviews --




Oxford Handbook of Ethics of AI


Book Description

This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."




An Examination of Emerging Bioethical Issues in Biomedical Research


Book Description

On February 26, 2020, the Board on Health Sciences Policy of the National Academies of Sciences, Engineering, and Medicine hosted a 1-day public workshop in Washington, DC, to examine current and emerging bioethical issues that might arise in the context of biomedical research and to consider research topics in bioethics that could benefit from further attention. The scope of bioethical issues in research is broad, but this workshop focused on issues related to the development and use of digital technologies, artificial intelligence, and machine learning in research and clinical practice; issues emerging as nontraditional approaches to health research become more widespread; the role of bioethics in addressing racial and structural inequalities in health; and enhancing the capacity and diversity of the bioethics workforce. This publication summarizes the presentations and discussions from the workshop.




Machine Law, Ethics, and Morality in the Age of Artificial Intelligence


Book Description

Machines and computers are becoming increasingly sophisticated and self-sustaining. As we integrate such technologies into our daily lives, questions concerning moral integrity and best practices arise. A changing world requires renegotiating our current set of standards. Without best practices to guide interaction and use with these complex machines, interaction with them will turn disastrous. Machine Law, Ethics, and Morality in the Age of Artificial Intelligence is a collection of innovative research that presents holistic and transdisciplinary approaches to the field of machine ethics and morality and offers up-to-date and state-of-the-art perspectives on the advancement of definitions, terms, policies, philosophies, and relevant determinants related to human-machine ethics. The book encompasses theory and practice sections for each topical component of important areas of human-machine ethics both in existence today and prospective for the future. While highlighting a broad range of topics including facial recognition, health and medicine, and privacy and security, this book is ideally designed for ethicists, philosophers, scientists, lawyers, politicians, government lawmakers, researchers, academicians, and students. It is of special interest to decision- and policy-makers concerned with the identification and adoption of human-machine ethics initiatives, leading to needed policy adoption and reform for human-machine entities, their technologies, and their societal and legal obligations.




Good Ethics and Bad Choices


Book Description

An analysis of how findings in behavioral economics challenge fundamental assumptions of medical ethics, integrating the latest research in both fields. Bioethicists have long argued for rational persuasion to help patients with medical decisions. But the findings of behavioral economics—popularized in Thaler and Sunstein’s Nudge and other books—show that arguments depending on rational thinking are unlikely to be successful and even that the idea of purely rational persuasion may be a fiction. In Good Ethics and Bad Choices, Jennifer Blumenthal-Barby examines how behavioral economics challenges some of the most fundamental tenets of medical ethics. She not only integrates the latest research from both fields but also provides examples of how physicians apply concepts of behavioral economics in practice. Blumenthal-Barby analyzes ethical issues raised by “nudging” patient decision making and argues that the practice can improve patient decisions, prevent harm, and perhaps enhance autonomy. She then offers a more detailed ethical analysis of further questions that arise, including whether nudging amounts to manipulation, to what extent and at what point these techniques should be used, when and how their use would be wrong, and whether transparency about their use is required. She provides a snapshot of nudging “in the weeds,” reporting on practices she observed in clinical settings including psychiatry, pediatric critical care, and oncology. Warning that there is no “single, simple account of the ethics of nudging,” Blumenthal-Barby offers a qualified defense, arguing that a nudge can be justified in part by the extent to which it makes patients better off.




Artificial Intelligence in Healthcare


Book Description

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data




Machine Learning and AI for Healthcare


Book Description

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.




Ethics, Conflict and Medical Treatment for Children E-Book


Book Description

What should happen when doctors and parents disagree about what would be best for a child? When should courts become involved? Should life support be stopped against parents' wishes? The case of Charlie Gard, reached global attention in 2017. It led to widespread debate about the ethics of disagreements between doctors and parents, about the place of the law in such disputes, and about the variation in approach between different parts of the world. In this book, medical ethicists Dominic Wilkinson and Julian Savulescu critically examine the ethical questions at the heart of disputes about medical treatment for children. They use the Gard case as a springboard to a wider discussion about the rights of parents, the harms of treatment, and the vital issue of limited resources. They discuss other prominent UK and international cases of disagreement and conflict. From opposite sides of the debate Wilkinson and Savulescu provocatively outline the strongest arguments in favour of and against treatment. They analyse some of the distinctive and challenging features of treatment disputes in the 21st century and argue that disagreement about controversial ethical questions is both inevitable and desirable. They outline a series of lessons from the Gard case and propose a radical new 'dissensus' framework for future cases of disagreement. - This new book critically examines the core ethical questions at the heart of disputes about medical treatment for children. - The contents review prominent cases of disagreement from the UK and internationally and analyse some of the distinctive and challenging features around treatment disputes in the 21st century. - The book proposes a radical new framework for future cases of disagreement around the care of gravely ill people.