Artificial Intelligence in Nutrition Science and Dietetics for Maternal and Child Health Benefits: Balancing Innovation with Ethical Risks.

Abstract

The present study critically assessed artificial intelligence (AI) in nutrition science and dietetics for maternal and child health, focusing on the balance between innovation and ethical issues. A systematic narrative review of 50 peer-reviewed studies published between 2020 and 2026 was conducted across multiple databases. Results: Accuracy, scalability, and predictive ability of AI applications for dietary assessment, personalized nutrition guidance, and public health surveillance were significantly increased. Meanwhile, new ethical and equity challenges emerged, such as data privacy issues, algorithmic bias, inequitable access in low- and middle-income countries, and professional displacement. We found research gaps in long-term evidence, Low and Middle Income Country-specific datasets, as well as ethical frameworks. AI has the potential to drive better maternal and child health outcomes, but its responsible adoption depends on governance, inclusion, and professional accountability; the study concludes. Key recommendations include strengthening governance of data through global health agencies, addressing bias at research institutions, expanding digital infrastructure through development banks, securing professional roles through dietetic associations, and encouraging longitudinal research underwritten by international research councils. Limitations are restricted to English-language studies from 2020-26 and a narrative synthesis instead of a meta-analysis, leading to less generalizability.