A planning committee of the National Academies of Sciences, Engineering, and Medicine will plan a 2-day public workshop to explore current knowledge and practice related to the application of advanced computation, big data analytics, and high-performance computing to support scientific advances in food and nutrition research. The workshop will feature invited presentations and discussions that will focus on providing guidance to researchers and policy-makers. Specific topic areas to be considered include:

• Definitions and methodology:
  • Clear definitions of artificial intelligence (AI) and related activities such as machine learning (ML), deep learning (DL), etc.;
  • Common methods, standards, and protocols; and
  • Roles of AI as a tool for developing study designs.
• Current applications of AI/ML in food and nutrition research:
  • Biomarker or bioactive discovery;
  • Data collection related to food intake and assessment and monitoring methods – tools such as sensors, wearables, smartphone applications;
  • Identifying relationships between foods/nutrients and health outcomes;
  • Behavioral research – advancing behavior change by teaching personalized health behaviors from personalized data;
  • Nutritional quality;
  • Food systems;
  • Food safety; and
  • Ways that AI is being applied in other disciplines relevant to food and nutrition.
• Considerations for diversity, equity, and inclusion:
  • Impact of AI, ML, and DL on underrepresented populations;
  • Bias in development of datasets, algorithms, and applications; and
  • Data privacy.
• Questions and considerations going forward, including research gaps:
  • What is the greatest limitation to AI now in research and what is the future potential?
  • What is the appropriate use of AI now and in the future? Hypothesis generation? Evidence” for decision-making? Where does it fit on the evidence hierarchy? Classifying subgroups, e.g. responders/non-responders?
  • How can AI be used to increase efficiency (costs) and resiliency in the food system?
  • What is needed to build trust in using advanced computation approaches within the food and nutrition research community?
  • Workforce needs:
    • Identify experience and skills for successful research teams. Identify training opportunities/exposure to data science methods for food and nutrition researchers.

The planning committee will organize the workshop, select and invite speakers and discussants and moderate the discussions. A Proceedings-in-Brief and a final workshop proceedings of the presentations and discussions from the workshop will be prepared by a designated rapporteur in accordance with institutional guidelines.