  This paper explores educational interactions involving humans and artificial
intelligences not as sequences of prompts and responses, but as a social
process of conversation and exploration. In this conception, learners
continually converse with AI language models within a dynamic computational
medium of internet tools and resources. Learning happens when this distributed
system sets goals, builds meaning from data, consolidates understanding,
reconciles differences, and transfers knowledge to new domains. Building social
generative AI for education will require development of powerful AI systems
that can converse with each other as well as humans, construct external
representations such as knowledge maps, access and contribute to internet
resources, and act as teachers, learners, guides and mentors. This raises
fundamental problems of ethics. Such systems should be aware of their
limitations, their responsibility to learners and the integrity of the
internet, and their respect for human teachers and experts. We need to consider
how to design and constrain social generative AI for education.
