AI + Nutrition
Modernization of the global food supply chain is happening through the application of AI, robotics, biotech, and data analysis. In order to meet the demands of a rapidly changing planet, we believe a focus on this technology application space as a key economic cluster is an imperative.
Overview
Co-Chair: Open
Faculty Advisor: Dr. Elena Naumova, Friedman School of Nutrition, Tufts
As AI becomes more pervasive in our everyday lives, there arises the need to examine the role of artificial intelligence in creating/normalizing a nutrition-centered food system. This group explores questions around how AI can be leveraged to further this goal, as well as the risks and opportunities that AI presents. Sub-topics include establishing a standard of care with AI data and beginning to examine how this could be defined and eventually operationalized. The group works with Tufts students in developing AI strategies for a healthy food system.
Members
David Blais
David Blais
Elena Naumova
Elena Naumova
Nicole Ninteau
Nicole Ninteau
Swati Kalgaonkar
Swati Kalgaonkar
Zully Corona
Zully Corona
Course
NUTR 390: Introduction to AI-Based Applications for Nutrition and Health Research (AIRNH) offers an overview of AI-based applications beneficial for health and nutrition research. It emphasizes the use of knowledge graphs, conceptual maps, and causal diagrams to enhance understanding and practical skills. The course also focuses on ethical considerations in using AI-powered tools, addressing the impacts of structural missingness on algorithmic bias, and exploring data representation and model transparency within the context of nutrition science and policy.
