Ethics and governance of artificial intelligence for health


Book Description

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.




Ethics and governance of artificial intelligence for health: large multi-modal models. WHO guidance


Book Description

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 Ethical Governance of Artificial Intelligence and Machine Learning in Healthcare


Book Description

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, Governance, and Policies in Artificial Intelligence


Book Description

This book offers a synthesis of investigations on the ethics, governance and policies affecting the design, development and deployment of artificial intelligence (AI). Each chapter can be read independently, but the overall structure of the book provides a complementary and detailed understanding of some of the most pressing issues brought about by AI and digital innovation. Given its modular nature, it is a text suitable for readers who wish to gain a reliable orientation about the ethics of AI and for experts who wish to know more about specific areas of the current debate.




The Oxford Handbook of Ethics of AI


Book Description

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.







WHO consultation towards the development of guidance on ethics and governance of artificial intelligence for health


Book Description

The present document is the report of the first expert meeting, which was held 2–4 October 2019 at WHO in Geneva. Participants discussed current and potential artificial intelligence (AI) applications for global health in the context of existing frameworks and human rights standards. The participants considered the main challenges of ethics, governance and equitable access and discussed potential solutions. The expert meeting has established a foundation for the second meeting which was held on 5 and 6 March 2020 in Copenhagen, Denmark. The publication of the WHO guidance document on Ethics and governance of AI for health is envisaged for completion in 2021.




Ethical Governance of Artificial Intelligence in the Public Sector


Book Description

This book argues that ethical evaluation of AI should be an integral part of public service ethics and that an effective normative framework is needed to provide ethical principles and evaluation for decision-making in the public sphere, at both local and international levels. It introduces how the tenets of prudential rationality ethics, through critical engagement with intersectionality, can contribute to a more successful negotiation of the challenges created by technological innovations in AI and afford a relational, interactive, flexible and fluid framework that meets the features of AI research projects, so that core public and individual values are still honoured in the face of technological development. This book will be of key interest to scholars, students, and professionals engaged in public management and ethics management, AI ethics, public organizations, public service leadership and more broadly to public administration and policy, as well as applied ethics and philosophy.




AI Ethics and Governance


Book Description

This book deeply analyzes the theoretical roots of the development of global artificial intelligence ethics and AI governance, the ethical issues in AI application scenarios, and the discussion of artificial intelligence governance issues from a global perspective. From the perspective of knowledge, the book includes not only the metaphysical research of traditional Western ethics, but also the interpretation of AI-related practical cases and international policies. The purpose of this book is not only to study AI ethics and governance issues academically, but to seek a path to solve problems in the real world. It is a very meaningful monograph in both academic theory and reality. This book responds to the implementation of China's digital economy governance and other topics. It is a cutting-edge academic monograph that combines industry, policy, and thought. In this book, the author not only discusses the humanities thoughts such as ethics, political economy, philosophy, and sociology, but also involves computer science, biology, and medicine and other science and engineering disciplines, effectively using interdisciplinary thinking as readers clarify how to explore ethical consensus and establish smart social governance rules in the era of artificial intelligence, so as to provide the most comprehensive and unique scientific and technological insights for smart economy participants, related practitioners in the artificial intelligence industry, and government policy makers. For academia, this is a representative book of Chinese scholars' systematic thinking on AI ethical propositions from a global perspective. For the industry, this is a book that understands the policies and ethical propositions faced by the development of AI industry. An important reference book, for policy makers, this is a monograph for understanding how policies in the AI industry make decisions that conform to AI industry practices and people's moral order.




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