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- Provides a multidisciplinary and comprehensive analysis of the philosophical, ethical, and policy implications of AI
- Examines existing ethical challenges and regulatory gaps that could potentially hamper the responsible development and implementation of AI
- Marks an important milestone in the public understanding of the ethics of AI in brain and mental health
This volume provides an interdisciplinary collection of essays from leaders in various fields addressing the current and future challenges arising from the implementation of AI in brain and mental health. Artificial Intelligence (AI) has the potential to transform health care and improve biomedical research. While the potential of AI in brain and mental health is tremendous, its ethical, regulatory and social impacts have not been assessed in a comprehensive and systemic way. The volume is structured according to three main sections, each of them focusing on different types of AI technologies. Part 1, Big Data and Automated Learning: Scientific and Ethical Considerations, specifically addresses issues arising from the use of AI software, especially machine learning, in the clinical context or for therapeutic applications. Part 2, AI for Digital Mental Health and Assistive Robotics: Philosophical and Regulatory Challenges, examines philosophical, ethical and regulatory issues arising from the use of an array of technologies beyond the clinical context. In the final section of the volume, Part 3 entitled AI in Neuroscience and Neurotechnology: Ethical, Social and Policy Issues, contributions examine some of the implications of AI in neuroscience and neurotechnology and the regulatory gaps or ambiguities that could potentially hamper the responsible development and implementation of AI solutions in brain and mental health. In light of its comprehensiveness and multi-disciplinary character, this book marks an important milestone in the public understanding of the ethics of AI in brain and mental health and provides a useful resource for any future investigation in this crucial and rapidly evolving area of AI application. The book is of interest to a wide audience in neuroethics, robotics, computer science, neuroscience, psychiatry and mental health. Table of Contents- Introduction
- Big Data in Medical AI: How Larger Data Sets Lead to Robust, Automated Learning for Medicine
- Automatic Diagnosis and Screening of Personality Dimensions and Mental Health Problems
- Intelligent Virtual Agents in Behavioral and Mental Healthcare: Ethics and Application Considerations
- Machine Learning in Stroke Medicine: Opportunities and Challenges for Risk Prediction and Prevention
- Respect for Persons and Artificial Intelligence in the Age of Big Data
- Social Robots and Dark Patterns: Where Does Persuasion End and Deception Begin?
- Minding the AI: Ethical Challenges and Practice for AI Mental Health Care Tools
- Digital Behavioral Technology, Deep Learning, and Self-Optimization
- Mental HealthChatbots, Moral Bio-Enhancement, and the Paradox of Weak Moral AI
- The AI-Powered Digital Health Sector: Ethical and Regulatory Considerations When Developing Digital Mental Health Tools for the Older Adult Demographic
- AI Extenders and the Ethics of Mental Health
- The Importance of Expiry Dates: Evaluating the Societal Impact of AI-Based Neuroimaging
- Does Closed-LoopDBS for Treatment of Psychiatric Disorders Raise Salient Authenticity Concerns?
- Matter Over Mind: Liability Considerations Surrounding Artificial Intelligence in Neuroscience
- A Common Ground for Human Rights, AI, and Brain and Mental Health
- Brain and Mental Health in the Era of Artificial Intelligence
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