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.
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.
L. He, M. Mavrikis, und M. Cukurova. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, Seite 327--333. Cham, Springer Nature Switzerland, (2024)