Artificial general intelligence (AGI) has gained global recognition as a future technology due to the emergence of breakthrough large language models and chatbots such as GPT-4 and ChatGPT, respectively. Compared to conventional AI models, typically designed for a limited range of tasks, demand significant amounts of domain-specific data for training and may not always consider intricate interpersonal dynamics in education. AGI, driven by the recent large pre-trained models, represents a significant leap in the capability of machines to perform tasks that require human-level intelligence, such as reasoning, problem-solving, decision-making, and even understanding human emotions and social interactions. This position paper reviews AGI's key concepts, capabilities, scope, and potential within future education, including achieving future educational goals, designing pedagogy and curriculum, and performing assessments. It highlights that AGI can significantly improve intelligent tutoring systems, educational assessment, and evaluation procedures. AGI systems can adapt to individual student needs, offering tailored learning experiences. They can also provide comprehensive feedback on student performance and dynamically adjust teaching methods based on student progress. The paper emphasizes that AGI's capabilities extend to understanding human emotions and social interactions, which are critical in educational settings. The paper discusses that ethical issues in education with AGI include data bias, fairness, and privacy and emphasizes the need for codes of conduct to ensure responsible AGI use in academic settings like homework, teaching, and recruitment. We also conclude that the development of AGI necessitates interdisciplinary collaborations between educators and AI engineers to advance research and application efforts.

翻译：通用人工智能（AGI）因GPT-4与ChatGPT等突破性大语言模型及聊天机器人的涌现，已作为未来技术获得全球认可。相较于通常为有限任务范围设计、需要海量领域特定数据训练、且未必充分考虑教育中复杂人际动态的传统AI模型，由近期大型预训练模型驱动的AGI在机器执行需人类级别智能的任务（如推理、问题解决、决策制定，乃至理解人类情感与社会互动）方面实现了重大飞跃。本立场文件系统评述了AGI在未来教育中的核心概念、能力边界与应用潜力，涵盖未来教育目标实现、教学法与课程设计、以及教育评估实施三大维度。研究表明，AGI可显著提升智能辅导系统、教育测评与评价流程；其系统能适应个体学生需求，提供定制化学习体验，并基于学习进展动态调整教学方法，同时全面反馈学生表现。论文强调，AGI对教育场景至关重要的能力在于理解人类情感与社会互动。文章讨论了AGI在教育中面临的伦理议题，包括数据偏差、公平性与隐私保护，并指出需建立行为准则以规范AGI在作业批改、教学实施及人才选拔等学术场景中的负责任应用。我们最终得出结论：AGI的发展需要教育工作者与AI工程师开展跨学科协作，以共同推进相关研究与应用实践。