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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
Artificial Intelligence (AI) can benefit our society and economy, but also brings with it new challenges and raises legal and ethical questions. According to the author of this comprehensive analysis, it is imperative to ensure that AI is developed and applied in an appropriate legal and regulatory framework that promotes innovation and investment and, at the same time, addresses the risks associated with certain uses of AI-related technologies. Essential to understanding the relationship between policy and law, this book traces the evolution of EU policy on artificial intelligence and robotics, focusing in particular on the EU’s ethical framework for AI, which defines trust as a prerequisite for ensuring a human-centric approach. The main part of the book provides a thorough and systematic analysis of the Commission’s 2021 proposed AI Act, which establishes harmonised rules for the development, placement on the market and use of AI systems in the EU. The author painstakingly compares the Commission’s proposed AI Act with the numerous “compromise” proposals of the Council of the European Union, leading to the final version of the Council’s AI Act (general approach) and its formal adoption on 6 December 2022. The author also examines with extraordinary detail the amendments proposed by the relevant committees and political groups of the European Parliament, revealing the position the Parliament is likely to adopt in the forthcoming negotiations with the Commission and the Council on the text of the AI Act. Numerous legislative and policy documents are presented in detail, while the analysis also considers the comments made by all interested parties (e.g. the European Commission, Council of the European Union, European Parliament, governmental organisations, national competent authorities, and stakeholders/actors with different/conflicting interests, such as corporations, business and consumer associations, civil society and other non-profit organisations). In the course of its in-depth analysis, this book will provide readers with crucial insight into the reasons behind the European Institutions’ different approaches and the often contradictory interests of stakeholders. Because the policy arguments are carefully balanced and drafted with scrupulous care, this volume will establish itself as a reference resource to be consulted for years to come.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
This collection gathers a set of seminal papers from the emerging area of ethics and climate change. Topics covered include human rights, international justice, intergenerational ethics, individual responsibility, climate economics, and the ethics of geoengineering. Climate Ethics is intended to serve as a source book for general reference, and for university courses that include a focus on the human dimensions of climate change. It should be of broad interest to all those concerned with global justice, environmental science and policy, and the future of humanity.
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
A provocative contribution to the climate justice debate Climate change and justice are so closely associated that many people take it for granted that a global climate treaty should—indeed, must—directly address both issues together. But, in fact, this would be a serious mistake, one that, by dooming effective international limits on greenhouse gases, would actually make the world's poor and developing nations far worse off. This is the provocative and original argument of Climate Change Justice. Eric Posner and David Weisbach strongly favor both a climate change agreement and efforts to improve economic justice. But they make a powerful case that the best—and possibly only—way to get an effective climate treaty is to exclude measures designed to redistribute wealth or address historical wrongs against underdeveloped countries. In clear language, Climate Change Justice proposes four basic principles for designing the only kind of climate treaty that will work—a forward-looking agreement that requires every country to make greenhouse-gas reductions but still makes every country better off in its own view. This kind of treaty has the best chance of actually controlling climate change and improving the welfare of people around the world.
In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.
How well are European firms responding to the new opportunities for growth, and in which global value chains are they developing these new activities? The policy discussion on the future of manufacturing requires an understanding of the changing role of manufacturing in Europe's growth agenda.
Artificial Intelligence (AI) has augmented human activities and unlocked opportunities for many sectors of the economy. It is used for data management and analysis, decision making, and many other aspects. As with most rapidly advancing technologies, law is often playing a catch up role so the study of how law interacts with AI is more critical now than ever before. This book provides a detailed qualitative exploration into regulatory aspects of AI in industry. Offering a unique focus on current practice and existing trends in a wide range of industries where AI plays an increasingly important role, the work contains legal and technical analysis performed by 15 researchers and practitioners from different institutions around the world to provide an overview of how AI is being used and regulated across a wide range of sectors, including aviation, energy, government, healthcare, legal, maritime, military, music, and others. It addresses the broad range of aspects, including privacy, liability, transparency, justice, and others, from the perspective of different jurisdictions. Including a discussion of the role of AI in industry during the Covid-19 pandemic, the chapters also offer a set of recommendations for optimal regulatory interventions. Therefore, this book will be of interest to academics, students and practitioners interested in technological and regulatory aspects of AI.
This book provides practical insights into applications of the state-of-the-art of Machine Learning and Artificial Intelligence (AI) for solving intriguing and complex problems in procurement and supply chain management. The application domain includes perishable food supply chain, steel price prediction, electric vehicle charging infrastructure design, contract price negotiation, reverse logistics network design, and demand forecasting. Further, the book highlights the advanced topics in the procurement field, like AI in green procurement and e-procurement in the pharma sector. Furthermore, the book covers applications of well-established methodologies such as heuristics, optimization, game theory, and MCDM based on the nature of the problem. The inclusion of the vaccine supply chain digital twin and blockchain-based procurement signals the significance of the book. This book is a comprehensive guide for industry professionals to understand the power of data analytics, enabling them to improve efficiency and effectiveness in the procurement and supply chain sectors.