Open, evidence-backed AI policy records for public reuse.
Beijing, China (Mainland)
Tsinghua University is listed as QS 2026 rank =17. Tsinghua University has 11 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
v1 public contract
Tsinghua University is listed as QS 2026 rank =17. Tsinghua University has 11 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Candidate claims are source-backed records pending review. They are not final policy conclusions and are not legal or academic integrity advice.
11 reviewed public claim
Other
Original evidence
Evidence 1鼓励同学们在遵守课程规定的前提下积极探索人工智能工具辅助学习，但严禁将人工智能生成的文本、代码等内容直接复制或简单转述后作为学业成果提交。
Other
Original evidence
Evidence 1禁止用人工智能代替本应由本人进行的学术训练，严禁使用人工智能实施代写、剽窃、伪造等行为。
Other
Original evidence
Evidence 1「数据安全」原则划出清晰红线，严禁师生使用敏感信息、涉密数据或未授权数据训练或驱动人工智能模型。
Other
Original evidence
Evidence 1「总则」部分明确了学校「积极而审慎」的基本立场，并提出「主体责任」「合规诚信」「数据安全」「审慎思辨」「公平包容」五大核心原则。
Other
Original evidence
Evidence 1「主体责任」原则强调人工智能始终是辅助工具，师生才是教学与学习的主导者。
Other
Original evidence
Evidence 1「合规诚信」原则要求师生对人工智能使用情况及生成内容依规进行披露声明，严禁学术不端。
Other
Original evidence
Evidence 1建议教师们基于教学目标自主制定人工智能的应用方式与程度，在课程开始时向学生明确说明使用规范，并对人工智能生成的教学内容负责。
Other
Original evidence
Evidence 1研究生指导教师需在此过程中提供规范性指导并进行全过程监督，确保学术训练的完整性和学位论文及实践成果的原创性。
Other
Original evidence
Evidence 1「审慎思辨」原则提醒师生警惕人工智能「幻觉」，应通过多源验证防范因过度依赖导致的思维惰化。
Other
Original evidence
Evidence 1「公平包容」原则呼吁主动识别并努力降低算法偏见与数字鸿沟，推动技术向善。
Other
Original evidence
Evidence 1学校积极鼓励并支持全体师生勇于探索人工智能在教育教学中的创新性应用，并将对优秀实践给予肯定与推广。
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
2 source attribution
tsinghua.edu.cn
tsinghua.edu.cn