The work of the EDSAFE centers around the SAFE Benchmarks Framework as we engage stakeholders to align equitable outcomes for all learners and improved working experiences for dedicated and innovative educators. We intend to clarify the urgency and specific areas of need to prevent failures in data management that compromise the potential for how responsible AI can be a lever for equity and innovation while protecting student privacy. Frameworks and benchmarks are important to innovation as a means of targeted guidance, focusing disparate efforts towards shared objectives and outcomes and ensuring the development of appropriate guidelines and guardrails.
Informing product leads and their teams of innovators, designers, and developers as they work toward safety, security, and trust while creating AI products and services for use in education.
This innovative report brings together the main developments driven by artificial intelligence (AI), a powerful tool for teachers, students, parents and academic institutions.
C. Peters, F. Reichert, and B. Gläsel. Human Friendly Automation: Arbeit und Künstliche Intelligenz neu denken, Frankfurter Allgemeine Buch, Frankfurt, Germany, 1 edition, (2023)
L. Johannsen, S. Ramm, Y. Reckleben, and S. Doerfel. Informatik in der Land-, Forst- und Ernährungswirtschaft, volume 344 of Lecture Notes in Informatics, page 107-118. (2024)
L. He, M. Mavrikis, and M. Cukurova. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, page 327--333. Cham, Springer Nature Switzerland, (2024)
J. Whittlestone, R. Nyrup, A. Alexandrova, and S. Cave. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, page 195–200. New York, NY, USA, Association for Computing Machinery, (Jan 27, 2019)