THE PERSONALIZED PLATE FOR HEALTHY EYES: A REVIEW OF ETHICAL AND SOCIAL IMPLICATIONS OF NUTRIGENOMICS AND AI IN PREVENTIVE OPHTHALMOLOGY

Abstract

The convergence of nutrigenomics and artificial intelligence (AI) heralds a paradigm shift in preventive ophthalmology, moving from a reactive to a predictive and personalized approach. This review examines the transformative potential and the critical ethical and social challenges arising from the integration of these technologies to create tailored nutritional interventions for eye health. Technologically, the field is advancing rapidly. Nutrigenomics provides the foundation by deciphering how genetic variations influence individual responses to ocular-specific nutrients. AI and machine learning algorithms are crucial for analyzing complex multi-omics data, retinal images, and dietary patterns to generate precise recommendations. However, this technological promise is accompanied by significant ethical dilemmas. Primary concerns include data privacy and confidentiality of highly sensitive genetic and health information, the risk of algorithmic bias perpetuating health disparities, and challenges to informed consent due to the complexity of AI systems. The social implications are profound, with a risk of exacerbating healthcare disparities through high costs and the digital divide. Regulatory frameworks struggle to keep pace with adaptive AI, and the evolving roles of healthcare professionals require new competencies. This review concludes that while AI-driven nutrigenomics holds immense potential for preventing vision loss, its successful and equitable integration demands proactive development of robust ethical guidelines, inclusive policies, and interdisciplinary collaboration.