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This paper reviews the diverse applications of AI in nutrition and food security research, highlighting its potential for data analysis, prediction, personalized recommendations, and food safety monitoring. It emphasizes the increasing importance of AI in data collection, decision-making, and policy development within these fields. The paper advocates for integrating data science and AI competencies into graduate education to prepare professionals for the growing complexity and adoption of AI technologies.
AI is poised to revolutionize nutrition research, but only if we equip the next generation with the necessary data science and AI skills.
Data analytics (DA) and artificial intelligence (AI) play increasingly vital roles in food, nutrition, environment, and public health research and practice. With the continued successful development, professionals in these fields could rely on data analytics and AI for tasks such as data collection, decision-making, and policy development. Proficiency in research methods, statistical analysis, and ethical considerations is crucial. As AI applications grow in complexity, it is essential for professionals and the public to embrace and regulate them effectively. This review outlines AI ’ s diverse applications in nutrition research, including data analysis, prediction, personalized recommendations, and food safety monitoring. Select illustrative examples demonstrate its potential across various domains and highlight common challenges. The narrative underscores the importance of integrating data science and AI competencies into graduate education to equip the modern workforce. Artificial intelligence (AI) refers to the development of computer systems capable of performing tasks that we typically attribute to human intelligence. 1 These tasks include understanding natural language, recognizing patterns, learning from experience, reasoning, and problem-solving. The goal of AI is to help humans solve complex problems, automate repetitive tasks, enhance decision-making processes, and inno-vate across various fields and industries. AI applications in food and nutrition research are revolutionizing the way data are collected, analyzed, and interpreted to better monitor nutritional status, identify trends, and inform policy decisions.
