The FAIR Train for AI WG will advance workforce development by creating and piloting curriculum-embedded teaching and training materials that help learners produce, evaluate, and reuse FAIR, AI-actionable data. The group will translate FAIR principles into practical competencies, assignments, and assessment tools that instructors and trainers can adopt across academic, government, and industry settings. The WG follows on the successful approach of the current FAIR Train MaRCN WG producing curriculum-embedded modules and learning activities that teach learners to create and work with AI-actionable datasets. For more information or to join the WG 12, email info ‘@’ marda-alliance.org/
Term: 3/1/2026 – 9/1/2027
MaRDA Council Liaisons and Initial Leads: Olga Wodo, University at Buffalo and Brian Schuster, UTEP.