From neurons to networks: ethical dimensions of AI-infused neural interfaces

Abstract

The convergence of artificial intelligence (AI) with neural interfaces, including brain-computer interfaces, deep brain stimulation devices, and neuroprosthetics, has significantly advanced medical science by enabling innovative diagnostic, therapeutic, and rehabilitative applications. AI integration enhances these technologies through adaptive learning, real-time data analysis, and personalized treatment strategies, thereby improving patient outcomes and expanding the scope of medical interventions. However, this technological synergy introduces complex ethical challenges that necessitate careful consideration to ensure responsible deployment. Key concerns include data privacy and security, informed consent and patient autonomy, algorithmic biases, equitable access to advanced technologies, and the long-term safety and accountability of AI-driven interventions. This review critically examines these ethical dilemmas, evaluating current practices and identifying potential risks associated with AI-integrated neural interfaces. Additionally, it explores proposed solutions such as robust safety protocols, shared accountability frameworks, comprehensive regulatory guidelines, and the adoption of responsible research and innovation practices. By advocating for interdisciplinary collaboration among developers, clinicians, policymakers, and ethicists, the paper emphasizes the importance of establishing ethical standards that balance technological innovation with patient welfare and societal trust. Ultimately, this review underscores the imperative of addressing ethical considerations to harness the full potential of AI-enabled neural interfaces while safeguarding fundamental ethical principles in medical practice.