Artificial intelligence in nutrition science: Balancing innovation and ethical responsibility

Abstract

Artificial intelligence (AI) is increasingly applied in nutrition science to support clinical decision-making, prevent diet-related diseases such as obesity and type 2 diabetes, and improve nutrition care in both preventive and therapeutic settings. By analyzing diverse datasets, AI systems can support highly individualized nutritional guidance. We focus on machine learning applications and image recognition tools for dietary assessment and meal planning, highlighting their potential to enhance patient engagement and adherence through mobile apps and real-time feedback. Despite these advantages, challenges persist. AI-driven recommendations depend heavily on data quality and algorithm transparency, and biases may arise from unbalanced datasets that underrepresent certain populations or dietary patterns. These challenges can be mitigated through validated data sources, explainable AI systems, and mandatory professional oversight. We emphasize an approach that integrates AI responsibly within nutritional practice. It underscores the importance of ethical standards, interdisciplinary collaboration, and equitable access to ensure safe and effective implementation.

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