Chapter 7: Research and Development provide environments where students can experience having difficult discussions across perspectives, an issue which is endemic to present society. A third researcher noted the insufficiencies of prior efforts to contend with algorithmic bias, ethics, and inclusion due to a classroom’s complex social dynamics. Researchers want to take a lead in going beyond checkbox approaches to take these issues seriously. And they also acknowledge that engaging with policy is often a new form of context for edtech and AI researchers, many of whom don’t have long experiences in policy arenas. Likewise, developers often do have experience with some policy issues, such as data privacy and security, but are now needing to become part of new conversations about ethics, bias, transparency, and more, a problem that the EdSAFE AI Alliance is addressing through multi- sector working groups and policy advocacy. 7.6. Key Recommendation: Focus R&D on Addressing Context Attendees who have participated in listening sessions leading up to this report were exceptionally clear that their view of future R&D involved a shift from narrow technical questions to richer contextual questions. This expansive shift toward context, as detailed below, is the foundational orientation that the listening session attendees saw as being necessary to advancing R&D. Attendees included these as dimensions of context: • Learner variability, e.g., in disabilities, languages spoken, and other relevant characteristics; • Interactions with peers, teachers, and others in the learning settings; 82 | P a g e
93 Publizr Home