对比五大区域教育AI法规，提出适配海湾国家的合规治理框架。
Trustworthiness of Legal Considerations for the Use of LLMs in Education
- 分析欧、美、中、英、海湾六国AI教育政策，提炼信任核心原则。
- 提出分级分类治理框架与机构检查清单，支持本地化合规落地。
- 聚焦海湾国家教育创新，兼顾国际标准与本土文化价值。
随着人工智能，尤其是大语言模型（LLMs）在全球教育系统中的深入应用，确保其伦理、法律及情境适宜的部署已成为关键政策议题。本文对比了欧洲联盟、英国、美国、中国及海湾合作委员会（GCC）等主要全球地区的AI相关监管与伦理框架，梳理透明性、公平性、问责制、数据隐私与人类监督等核心信任原则在区域立法与AI治理结构中的体现。特别关注海湾地区快速推进的国家AI战略与教育领域创新。为此，论文提出一个面向海湾地区情境的以合规为中心的AI治理框架，包含分级分类体系与机构检查清单，助力监管者、教育工作者与开发者将AI应用与国际规范及本地价值观相协调。通过融合全球最佳实践与区域特定挑战，本文为构建合法、伦理与文化敏感的教育AI系统提供实用指引，旨在推动未来监管协调，促进多元教育环境中负责任的AI整合。
原文摘要 · Abstract (English)
As Artificial Intelligence (AI), particularly Large Language Models (LLMs), becomes increasingly embedded in education systems worldwide, ensuring their ethical, legal, and contextually appropriate deployment has become a critical policy concern. This paper offers a comparative analysis of AI-related regulatory and ethical frameworks across key global regions, including the European Union, United Kingdom, United States, China, and Gulf Cooperation Council (GCC) countries. It maps how core trustworthiness principles, such as transparency, fairness, accountability, data privacy, and human oversight are embedded in regional legislation and AI governance structures. Special emphasis is placed on the evolving landscape in the GCC, where countries are rapidly advancing national AI strategies and education-sector innovation. To support this development, the paper introduces a Compliance-Centered AI Governance Framework tailored to the GCC context. This includes a tiered typology and institutional checklist designed to help regulators, educators, and developers align AI adoption with both international norms and local values. By synthesizing global best practices with region-specific challenges, the paper contributes practical guidance for building legally sound, ethically grounded, and culturally sensitive AI systems in education. These insights are intended to inform future regulatory harmonization and promote responsible AI integration across diverse educational environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。