Inteligencia artificial en psiquiatría: usos y promesas

This article examines the integration of Artificial Intelligence (AI) into psychiatry, highlighting both its transformative potential and its ethical, clinical, and philosophical challenges. AI applications (ranging from diagnostic algorithms and predictive models to therapeutic chatbots and neuroimplants) are reshaping mental healthcare by improving early detection, personalizing treatments, and expanding access to services, particularly in resource-limited settings. Advanced techniques such as machine learning and natural language processing enable the analysis of multimodal data, enhancing clinical decision-making and enabling preventive interventions. However, the adoption of AI raises significant concerns. These include risks to privacy, algorithmic bias, lack of transparency, and challenges in ensuring informed consent, particularly in vulnerable psychiatric populations. Neurotechnologies such as deep brain stimulation (DBS), especially when assisted by AI, introduce further ethical dilemmas related to autonomy, identity, and long-term safety. The article argues that these challenges cannot be addressed without a deeper conceptual understanding of mental disorders. It advocates for a pluralistic and enactivist framework, which views mental health conditions as dynamic interactions between brain, body, and environment. Ultimately, the responsible integration of AI in psychiatry requires robust ethical governance, interdisciplinary collaboration, and a human-centered approach.