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和ChatGPT等突破性大语言模型及聊天机器人的出现，已作为未来技术获得全球认可。相较于传统AI模型——通常针对有限任务设计、需要大量领域特定数据进行训练且未必考虑教育中复杂的人际动态，近期大预训练模型驱动的AGI在机器执行需人类智能的任务（如推理、问题解决、决策制定，甚至理解人类情感与社会互动）方面实现了重大飞跃。本立场文件梳理了AGI的核心概念、能力、范畴及其在未来教育中的潜力，包括实现未来教育目标、设计教学法与课程、开展评估等方面。研究强调，AGI能够显著改进智能辅导系统、教育评估与评价流程。AGI系统可适应个体学生需求，提供定制化学习体验；还能针对学生表现提供全面反馈，并根据学生进步动态调整教学方法。论文指出，AGI的能力延伸至理解教育场景中至关重要的人类情感与社会互动。本文探讨了AGI应用于教育时涉及的伦理问题（包括数据偏差、公平性与隐私），并强调需要制定行为准则以确保AGI在作业、教学、招生等学术场景中的负责任使用。我们同时得出结论：AGI的发展需要教育工作者与AI工程师之间的跨学科协作，以推进研究与应用工作。