Artificial Intelligence in Brain and Mental Health: Philosophical, Ethical & Policy Issues

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.

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• Neurociências
• Psiquiatria
• Neurologia e neurofisiologia clínica
• Ética e filosofia moral
• Filosofia
• Inteligência artificial

Artificial intelligence;Neurotechnology;Big data;Data ethics;Ethical framework;Discrimination and stigma;Robotherapy