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This is the first book to provide a coherent overview over the ethical implications of AI-related technologies in medicine. It explores how these technologies transform practices, relationships, and environments in the clinical field. It provides an introduction into ethical issues such as data security and privacy protection, bias and algorithmic fairness, trust and transparency, challenges to the doctor-patient relationship, and new perspectives for informed consent. The book focuses on the transformative impact that technology is having on medicine, and discusses several strategies for dealing with the resulting challenges. It also introduces innovative methods of ethics research for addressing existing desiderata and future challenges. This book is written to inform health care professionals, policy-makers, and researchers in medicine, health sciences, nursing science, social sciences, and ethics, but may also function as a primary textbook for graduate as wellas undergraduate university courses.
Provides a coherent overview of ethical implications of AI-related technologies in medicine Contributes to the dynamic ethical discourse on digital health care Supports practitioners and policy-makers in the complex field of medical AI
Auteur
Giovanni Rubeis is full professor of Biomedical and Public Health Ethics at the Karl Landsteiner University of Health Sciences in Krems, Austria. As bioethicist and philosopher, the main focus of his research is the digital transformation of healthcare and its ethical implications. Prof. Rubeis is co-founder and coordinator of the working group "Digitalization and Health" within the German Academy of Ethics in Medicine.
Contenu
Part 1 : Foundations.- Chapter 1: Introduction.- Chapter 2: Artificial Intelligence: In search of a definition.- Chapter 3: MAI: A very short history and the state of the art.- Chapter 4: Ethical foundations: Medical Ethics and Data Ethics.- Part 2 : Ethical Analysis.- Chapter 5: Practices.- Chapter 6: Relationships.- Chapter 7: Environments.- Chapter 8: Instead of a conclusion: Seven lessons for the present.