Special report: AI Institute for next generation food systems (AIFS)

Ilias Tagkopoulos, Stephen F. Brown, Xin Liu, Qing Zhao, Tarek I. Zohdi, J. Mason Earles, Nitin Nitin, Daniel E. Runcie, Danielle G. Lemay, Aaron D. Smith, Pamela C. Ronald, Hao Feng, Gabriel David Youtsey

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial Intelligence (AI) has the potential to transform US food systems by targeting its biggest challenges: improving food yield, quality, and nutrition, decreasing resource consumption, increasing safety and traceability, and eliminating food waste. Despite big leaps in AI capacity, food systems present several challenges for the application and adoption of AI: (1) Food systems are highly diverse and biologically complex, (2) ground-truth data is sparse, costly, and privately held, and (3) human decisions and preferences are intricately linked to every stage of food system supply chains. To address these challenges and transform U.S. food systems, the AI Institute for Next Generation Food Systems (AIFS) aims to develop AI technologies and nurture the next generation of talent to produce and distribute more high-quality nutritious food with fewer resources. AIFS has six research clusters, including two Foundational Research Areas (Use-Inspired and Foundational AI, and Socioeconomics and Ethics) and four Application Research Areas spanning the entire food supply chain: Molecular Breeding, Agricultural Production, Food Processing and Distribution, and Nutrition. AIFS is developing generalizable, data efficient, and trustworthy AI solutions based on a knowledge-driven and human-in-the-loop learning paradigm designed to handle food system diversity and biological complexity, efficiently capture, and utilize food system data, and garner user trust via explainability, safety, privacy, and fairness.

Original languageEnglish (US)
Article number106819
JournalComputers and Electronics in Agriculture
Volume196
DOIs
StatePublished - May 2022

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture

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