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.

本文探讨了与人工智能进行的教育交流，不是作为提示和回应的序列，而是作为对话和探索的社交过程，在其中，学习者在互联网工具和资源的动态计算介质中不断与 AI 语言模型交谈。本文强调了构建用于教育的社交生成 AI 是需要开发强大的 AI 系统的，这些系统可以与人类以及彼此对话，构建如知识地图之类的外部表征，访问和贡献于互联网资源，并担任教师、学习者、导师和指南的角色。但人们也需要考虑将如何设计和约束这些社交生成 AI，以确保其意识到其限制、对学习者和互联网的尊重并尊重人类教师和专家的完整性的问题。