Tsinghua University Issues AI Academic Rules, Restricts Misuse
- ByStartupStory | November 30, 2025
Comprehensive Framework Balances Innovation With Academic Integrity Amid AI Boom
Tsinghua University, China’s premier engineering institution, has released the “Guiding Principles for the Application of Artificial Intelligence in Education,” marking its first university-wide policy regulating AI use across teaching, learning, and research. Unveiled after extensive consultations involving over 100 faculty and students, the framework adopts a “proactive yet prudent” stance, positioning AI strictly as an auxiliary tool while teachers and students remain primary agents in educational processes. The guidelines establish clear “red lines” against misconduct while providing “green lights” for responsible experimentation, addressing real campus challenges like AI-assisted assignments and data processing.
Five Core Principles Define Responsible AI Engagement
The document’s “General Provisions” outline five foundational principles: principal responsibility, compliance and integrity, data security, prudence and critical thinking, and fairness and inclusiveness. AI must serve educational goals without replacing human intellectual labor, with mandatory disclosure of its use in all academic outputs to prevent ghostwriting, plagiarism, or fabrication. Sensitive, classified, or unauthorized data is explicitly banned for training or operating AI models, underscoring data sovereignty and ethical sourcing.
Prudence demands vigilance against AI “hallucinations”—generating plausible but incorrect information—through multi-source verification and avoidance of cognitive complacency from overreliance. Fairness addresses algorithmic bias and the digital divide, ensuring equitable access and mitigating exclusionary impacts. These principles apply campus-wide, fostering a healthy ecosystem where AI enhances rather than undermines learning outcomes.
Teaching And Learning: Faculty Autonomy With Strict Boundaries
In the “Teaching and Learning” section, instructors gain flexibility to integrate AI based on course objectives, but must explain usage rules to students at semester start and retain responsibility for any AI-generated materials. Teachers are encouraged to cultivate critical AI understanding, developing competencies like ethical evaluation and innovative application. Students may leverage AI for auxiliary support—such as brainstorming or data analysis—provided they adhere to course-specific guidelines.
Direct submission of AI-generated text, code, or outputs as personal work is strictly prohibited, treated as academic misconduct. This balances exploration with accountability, promoting AI literacy while safeguarding evaluation integrity. The policy recognizes emerging tools like AI-powered courses, disciplinary knowledge engines, and campus companions such as Qing Xiaoda, developed since 2023, but insists on human oversight.
Graduate Theses: Full-Process Supervision Prevents AI Dependence
The “Theses, Dissertations and Practical Achievements” section targets graduate research, where AI cannot substitute independent academic training. Ghostwriting, plagiarism, data fabrication, or other misuse is forbidden, with supervisors mandated to offer explicit AI guidance and maintain end-to-end oversight. This ensures originality in theses, where students must demonstrate personal intellectual contributions despite AI aids for processing or visualization.
The framework responds to practical dilemmas: distinguishing AI assistance from cheating, defining grading responsibility, and setting boundaries for code generation. By prohibiting mechanical paraphrasing, it preserves the rigor expected in advanced degrees.
Development Process Reflects Global Best Practices
Drafting began in summer 2024, led by the Undergraduate Academic Affairs Office, Graduate School, School of Education, and academic units. A research team surveyed 70 AI guidelines from 25 top universities in the US, Europe, and Asia-Pacific, incorporating frontline feedback from humanities, sciences, engineering, and medicine disciplines during March-May 2025 consultations. Respondents sought clarity on integrity boundaries and supportive innovation.
Wang Shuaiguo, director of Tsinghua’s online education center and lead drafter, described the principles as a “living system” evolving with technology, not a static constraint. Implementation will involve AI literacy platforms, teaching workshops, and interdisciplinary forums to promote exemplary practices.
Broader Implications For Global Higher Education
Tsinghua’s move positions it at the forefront of AI governance in academia, influencing peers amid generative AI’s rapid proliferation. Unlike some Western institutions mandating explicit permissions, Tsinghua emphasizes proactive norms while enabling experimentation—recognizing AI’s potential in redefining education without eroding core values.
As universities worldwide grapple with similar tensions, Tsinghua’s balanced approach offers a blueprint: harness intelligent technologies for public good while safeguarding human agency. The university plans ongoing evolution, preparing students to innovate alongside AI in an era demanding both technical prowess and ethical discernment. This 600+ word framework not only regulates misuse but illuminates pathways for sustainable educational transformation.
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