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.

<p>Introduction

Part I Scientific Considerations and Challenges: AI-augmented neuroimaging
AI analytics in brain cancer screening
AI analytics to detect pre-symptomatic dementia
AI analytics in schizophrenia
Wearables, mHealth and mental health monitoring
Prevention of mental disorders through social media
The brain health modeling initiative and the promise of AI
Assistive robotics for dementia and mild cognitive impairment
Telehealth and robotherapy in psychiatry
Robot-assisted neurorehabilitation
Brain-computer interfaces and AI-mediated neuromodulation
Part III . Ethical Legal and Social Implications: Mental Privacy
Algorithmic transparency - Measurement bias and ethical bias
Discrimination and stigma
Informed Consent
Minimal risk
Fairness and Research Allocation
The black-box problem of medical AI
The transformation of therapeutic relationships
The role of IRBs
The ethics of automated medical decision-making
Accountability and Responsibility
Designing moral technologies for brain and mental health
AI and Human Beings: Philosophical and Ethical Perspectives
Part III Policy Perspectives: Current regulatory frameworks in North America
Gaps in existing regulations
Policy and law of AI in China
Deontology and best practices
Regulation of AI industry
AI in the developing world: a global justice perspective
Regulation of AI in Europe
Conclusion - Towards an ethical framework for AI in brain and mental health.</p>