AI in Human Neuroscience, Ethically Done: Neuroethical Risks, Safeguards, and Governance

Artificial intelligence is revolutionizing human neuroscience, enabling unprecedented advances in brain imaging analysis, neural decoding, predictive modeling, and personalized neurological interventions. However, the rapid integration of AI into neuroscience research and clinical applications raises critical ethical concerns that remain inadequately addressed. These include privacy vulnerabilities with neural data, algorithmic bias in brain-based diagnostic tools, issues of informed consent in AI-driven neuroscience studies, and the potential misuse of neural information for non-medical purposes. As AI systems become increasingly sophisticated and widely deployed, there is an urgent need for comprehensive frameworks that balance scientific innovation with robust ethical safeguards. This Research Topic brings together neuroscientists, ethicists, technologists, and policymakers to advance the responsible integration of AI in human neuroscience.This Research Topic aims to identify, analyze, and address the neuroethical challenges posed by AI in human neuroscience research and practice. We seek to tackle key questions: What are the principal ethical risks associated with AI applications in neuroscience? How can we design and implement effective safeguards to protect research participants and patients? What governance frameworks are needed at institutional, national, and international levels to ensure responsible AI use in neuroscience? This collection will showcase evidence-based solutions, ethical guidelines, and policy recommendations that empower researchers and clinicians to harness AI's potential while protecting human dignity, autonomy, and privacy. By fostering interdisciplinary dialogue, we aim to establish best practices and governance standards that guide the ethical future of AI in human neuroscience.We welcome original research, reviews, perspectives, and policy analyses addressing the intersection of AI, neuroscience, and ethics. Contributions should align with one or more of the following themes:• Privacy and Data Security: Neural data protection, de-identification of brain imaging, and safeguards against unauthorized access or misuse• Algorithmic Bias and Fairness: Detecting and mitigating bias in AI-driven diagnostic and prognostic tools for neurological conditions• Informed Consent: Ethical frameworks for AI-assisted neuroscience research and emerging consent models for dynamic, data-intensive studies• Interpretability and Transparency: Explainable AI methods in neuroscience and strategies for clinician and patient understanding of AI-derived insights• Governance and Regulation: International standards, institutional policies, and regulatory frameworks for responsible AI deployment in neuroscience• Neuroenhancement and Dual-Use Concerns: Ethical implications of • AI-enabled brain-computer interfaces and safeguards against harmful applications• Equity and Access: Ensuring fair distribution of AI-driven neuroscience benefits across diverse populations and resource-limited settings Topic editors: Gargi Mahapatra, Deborah Schneider, Elias Ebrahimzadeh Source: https://www.frontiersin.org/research-topics/82203/ai-in-human-neuroscience-ethically-done-neuroethical-risks-safeguards-and-governance