Which universities mention AI detection or detector tools?

UTokyo states it is unacceptable to present AI-generated text as one's own when submitting class assignments.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UTokyo states that submitting AI-generated answers by copy-pasting them entirely provides no learning effect and should basically not be permitted.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UTokyo warns faculty not to over-rely on AI detection tools, as they are insufficient evidence of inappropriate student AI use given the rapid evolution of generative tools.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Submitting AI-generated content as one's own work constitutes a breach of ANU's academic integrity rules.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At ANU, using AI-generated content when not permitted and claiming authorship without acknowledgment constitutes a breach of academic integrity.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

ANU treats generative AI as a permissible learning tool that can be cited as an information source, but强调 it is not a replacement for student thinking and originality.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Cornell's committee report recommends three policy approaches for generative AI use: prohibit GAI where it interferes with foundational learning, allow with attribution where it supports higher-level thinking, and encourage use where it enables exploration and creative thinking.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Cornell's committee report discourages the use of automatic detection algorithms for academic integrity violations using generative AI, stating they cannot decisively provide evidence and could lead to unfairly identifying violations, including bias against non-native speakers.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Cornell does not recommend using automatic AI detection algorithms for academic integrity violations, citing their unreliability and inability to provide definitive evidence, and the risk of wrongly accusing students.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Tsinghua University prohibits students from directly copying or mechanically paraphrasing AI-generated text, code, or other output and submitting it as academic coursework.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Tsinghua University prohibits using AI to replace academic training that graduate students are expected to complete independently, and strictly forbids AI-assisted ghostwriting, plagiarism, and fabrication in theses, dissertations, and practical achievements.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Tsinghua University requires teachers and students to disclose their use of AI and AI-generated content in accordance with regulations, as part of the 'compliance and integrity' principle.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Staff setting summative assessment must: declare whether/how students can use AI; review assessment design for alignment with permitted AI use; ensure equality of baseline AI tool provision where authorised; specify declaration forms for student AI use; only identify suspected unauthorised AI use through marking or university-endorsed detection tools (none currently endorsed); and handle misconduct under usual disciplinary regulations.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Students undertaking summative assessment must: complete assessment in line with the AI use declaration for each assignment; acknowledge their AI use via a formal declaration in the prescribed format; and understand that submitting work breaching AI specifications constitutes cheating and may constitute plagiarism, handled under usual disciplinary regulations.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

For PGR students, the following uses of generative AI are not permitted in summative assessments: substantive original writing by GenAI (verbatim or closely paraphrased for chapters or parts thereof) which constitutes plagiarism; using AI to produce plots or data visualisations directly from prompts; and entering private or confidential data into third-party AI tools.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Users of AI at Penn are accountable for AI-generated content and should validate its accuracy with trusted first-party sources, being wary of misinformation or hallucinations.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Penn educators should provide students with clear guidelines on the use of AI within coursework and should disclose to students when course materials have been created with AI or when AI detection software will be used.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At Wharton Academy, AI-generated work should be cited like any other reference material, including how and where students used AI-generated information; using AI-generated work without crediting the source is considered plagiarism.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At King's College London, submitting AI-generated text as one's own without written departmental permission is considered misconduct under third-party involvement or text manipulation offences.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

King's College London has disabled the AI detection feature in Turnitin due to concerns about reliability and false positives.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

King's College London doctoral examiners must not upload any part of a student's thesis into a generative AI tool or use external AI detection software when assessing the thesis.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Korea University states that submitting AI-generated content as one’s own, or using it without permission, is academic misconduct.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Korea University says AI-detection and plagiarism-prevention tools should be used only as supplementary references and not as the sole basis for misconduct findings.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Korea University tells learners to disclose the AI tool name, timing, and scope of use, distinguish their own work from AI contributions, and cite AI-generated content according to the required format.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NTU states that not citing or acknowledging the use of generative AI could be considered plagiarism (a form of research misconduct), especially if GenAI was used to generate ideas or for literature reviews.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NTU states that misrepresenting AI-generated content as one's own work is considered academic misconduct under the 2025 NTU Academic Integrity Handbook.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NTU guidelines state that AI detector tools should be used with caution due to frequent false positives and negatives, ease of bypass, and bias against non-native English writing patterns.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NTU DFLL guidance says instructors may decide whether students may use generative AI; if permitted, students should clearly label AI-generated content and follow academic ethics.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

National Taiwan University guidance says students using ChatGPT for assignments or reports should clearly label AI-generated content, fact-check it, and comply with academic ethics and academic-integrity requirements.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

National Taiwan University guidance says AI-detection tools have limited accuracy and are not sufficient evidence by themselves to confirm student AI use; it recommends caution before accusing students based only on such tools.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NUS policy states that verdicts from AI detection tools are not admissible as conclusive evidence in disciplinary processes to charge students with academic dishonesty or to penalize student work.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NUS policy states that representing AI output as one's own work without acknowledgement is plagiarism; students who submit AI-generated work without acknowledging its use can be sanctioned for academic dishonesty.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NUS requires students to cite AI-generated content according to style guide conventions and to check assignment guidelines for specific AI use instructions.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Stanford's BCA issued guidance on generative AI use, and the Office of Community Standards recommends that instructors give advance notice to students when using AI detection software.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Stanford School of Medicine MD and MSPA programs have a formal AI policy: students may use AI for learning, clarification, and grammar/style editing unless contrary to assignment instructions. AI use for closed-book exams or assignments where internet is restricted is prohibited unless explicitly authorized by faculty. Students are responsible for all AI-generated content they submit, must disclose and cite substantial AI contributions, and violations may result in disciplinary action.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Stanford University Communications (UComm) has issued AI guidelines for marketing and communications staff requiring: human oversight of all AI-generated content (non-delegable personal responsibility), adherence to university policies, prohibition on inputting confidential or legally privileged information into generative AI tools, prohibition on using AI to promote for-profit organizations or engage in political advocacy, and prohibition on using high-risk data in prompts. Stanford AI Playground is recommended as the primary platform. These guidelines apply to all regular staff, interns, casual employees, and consultants in marketing and communications functions.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At CUHK, improper or unauthorized use of AI tools in learning activities and assessments constitutes academic dishonesty and is subject to penalties including failure grade, suspension, or termination of studies.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

CUHK requires students to declare in each assignment that they have read and understood the University's policy on AI use, complied with course teacher instructions on AI tools, and consent to AI content detection software review.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

CUHK's student AI guide establishes ethical principles of accountability, transparency, and acknowledgement for AI tool use. Users are accountable for AI-generated outputs and must fact-check all outputs.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The University of Auckland's student AI advice states that AI has no agency, treats the student prompting an AI tool as the author, and says students are ultimately responsible for work submitted for assessment.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The University of Auckland TeachWell two-lane assessment guidance says the University does not endorse third-party AI detection tools, citing unreliability, false positives, and possible student-data training risks.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Auckland Law School's student AI guidelines for taught courses state that using AI to generate, draft, or assist in creating content for graded assignments is prohibited unless the instructor explicitly permits it in writing.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At the University of Edinburgh, presenting AI outputs as your own original work, submitting AI-generated text without acknowledgment, and using AI agents within university learning platforms constitute academic misconduct.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At the University of Edinburgh, staff presenting AI-generated content as their own original work, uploading personal data or confidential information to external AI tools, and relying on AI detection tools are listed as unacceptable uses.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The University of Edinburgh advises staff not to rely on AI detection tools to confirm authorship, as they misclassify human and AI content.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UNSW only authorises the use of Turnitin's AI Writing Detection Tool for detecting improper AI use in student work; UNSW IT has not approved other detection tools due to privacy and accuracy concerns.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Where unauthorised AI use in an assessment is admitted or determined at UNSW, a finding of serious student misconduct is made as a breach of Principle 3 of the Student Code of Conduct, with penalties consistent with Serious Student Misconduct and Serious Plagiarism (typically 00FL for the course, suspension, or exclusion).

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UNSW provides academics with access to Turnitin's AI detection tool for assessments submitted through Moodle Turnitin Assignment or Inspera, but notes this is not always conclusive evidence of improper AI use.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UQ has disabled the Turnitin AI writing indicator functionality for all assessments from Semester 2, 2025, citing that AI detection tools are flawed and unreliable.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At UQ, the use of AI outputs without attribution, and contrary to any direction by teaching staff, is a form of plagiarism and constitutes academic misconduct.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UQ says students must acknowledge where they used AI in assessment, including direct quotes or paraphrases of AI-generated content and use of AI tools for summarising, brainstorming, planning, editing, or proofreading.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Université PSL academic regulations state that, when an instructor authorizes the use of AI-based tools such as ChatGPT, that use must be explicitly disclosed like a source citation; failure to disclose AI use is considered plagiarism and sanctioned as such.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

PSL-affiliated guidance states that generative AI tools cannot be considered co-authors of scientific work, and users retain full responsibility for AI-generated content, codes, images, and texts.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

PSL-affiliated guidance advises that personal data should not be shared with third parties when generative AI is used, and that generated text should be checked so it does not constitute plagiarism or contain personal data.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UT Austin AI detection guidance prohibits third-party AI detection software from being used to evaluate student work or assignments unless a university contract or purchase order is in place.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UT Austin AI detection guidance says submitting student work into AI detection or other third-party software without a university contract or purchase order may violate student copyright, intellectual property, or FERPA privacy rights.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

UT Austin CTL teaching-policy guidance says using generative AI tools to create course-assignment responses in a way the instructor does not accept may be considered academic dishonesty by the university.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Yale academic integrity guidance treats inserting AI-generated text into an assignment without proper attribution as an academic integrity violation.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The Yale Poorvu Center says it does not endorse AI detection software or enable such features in Canvas.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Yale guidance tells users to review and verify AI-generated outputs, especially before publication.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Violations of GenAI guidelines such as use of unauthorised aids or non-disclosure of their use are subject to disciplinary action under existing performance assessment rules and the declaration of originality.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

ETH Zurich states that technical recognition of AI-generated output is currently unreliable and will probably remain so; trust in such methods is not appropriate.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

MIT advises community members to disclose the use of generative AI tools for all academic, educational, and research-related uses, and not to publish research results relying on AI-generated content without disclosing the nature of such use.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

MIT holds users responsible for the accuracy of any information they publish, including AI-generated content. Users must be aware that AI-generated information may be inaccurate, incomplete, misleading, biased, fabricated, or contain third-party intellectual property.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

SNU Library advises researchers to check target journal editorial policies from the planning stage, as policies vary on whether LLMs can be listed as authors and whether AI-generated text is permitted.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

SNU Library warns that not citing generative AI use in papers risks plagiarism charges; researchers must cite AI use according to journal-specific styles (MLA, APA, Chicago).

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Sorbonne University's 2024-2025 assessment rules treat unauthorized AI-generated work presented as one's own, or authorized AI use without source mention, as plagiarism.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Sorbonne University's CAPSULE resources page lists Compilatio Magister+ with CAS SU access as a resource for plagiarism prevention and detection of AI-generated content.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Submitting work created by generative AI as one's own, or misrepresenting understanding of the subject, is plagiarism at Manchester and will be dealt with in accordance with the University's Academic Malpractice Procedure.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Tools to detect AI-generated content are unreliable and biased and cannot be relied on to identify academic malpractice in summative assessment at Manchester. Output from such tools cannot currently be used as evidence of malpractice.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

University of Sydney guidance states that misusing generative AI can breach the Academic Integrity Policy 2022, with examples including using AI in assessments where prohibited, submitting AI-generated work without acknowledgment, and inputting University teaching materials or personal information into AI tools.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The University of Sydney advises that Turnitin's AI detection tool may be used if a marker suspects AI-generated work where its use was not permitted or not acknowledged, but the AI detector score would not be the only evidence relied upon for an academic integrity case.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The UC Berkeley Academic Senate states that generative AI detection tools are increasingly less accurate and that there are no validated generative AI detection tools available.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The UC Berkeley Academic Senate recommends that for assignments where GenAI is not permitted, instructors should adopt enforcement mechanisms such as in-person proctored exams, an additional oral exam component, or a written statement of academic integrity, since no validated GenAI detection tools exist.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

U-M does not recommend the use of AI-detection technology given their high error rate. False positives and negatives are possible, and even likely.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

U-M requires that AI-generated computer code is always reviewed by a human, with professionally trained peer code reviews for applications handling Restricted or High data.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Brown OIT research guidance says researchers should deeply review AI-generated code for quality and efficiency.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Caltech admissions prohibits applicants from copying and pasting directly from an AI generator, relying on AI-generated content to outline or draft essays, replacing their unique voice with AI-generated content, or translating essays via AI.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

CMU Eberly Center guidance recommends extreme caution when using AI-detection tools because no such tools have been established as accurate.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Teachers College example syllabus statements require citations or disclosure detailing specific AI tools and models used when AI use is permitted.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Duke CTL assignment-design guidance advises that personal information should not be shared when using AI in assignments, to minimize privacy threats to students and instructors.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

EPFL considers the use of AI-generated content in assignments without proper attribution as AI plagiarism. Tools that detect AI-generated content are not admissible as stand-alone evidence of AI plagiarism due to high risk of false positives.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

复旦大学学生工作部公开页面援引《复旦大学关于在本科毕业论文(设计)中使用 AI 工具的规定(试行)》称，本科毕业论文写作中使用 AI 工具辅助需经老师同意并披露使用情况，数据收集、核心观点提炼等创新工作不可依赖 AI，涉密和隐私内容禁止使用 AI。

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

University-wide: Users are responsible for any content they publish or share that includes AI-generated material. AI-generated content may be inaccurate, misleading, entirely fabricated (hallucinations), or contain copyrighted material.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Unless explicitly authorised, using generative AI to create assessed work may be treated as an academic offence such as contract cheating under Imperial's Plagiarism, Academic Integrity & Exam Offences regulations. Improper use of AI can be investigated under the University's Academic Misconduct procedures.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

École polytechnique (member school) provides teaching resources for AI integration including detection tools (Turnitin, AI Text Classifier, GPTZero) and curated expert articles on generative AI in higher education.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

LMU IfKW guidance treats verbatim or minimally changed AI-generated text without proper attribution as plagiarism, and says significant unattributed AI-generated text in assessed work can receive grade 5 (failed).

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Lund University's student guidance says students who want to use GenAI for a compulsory assignment or examination must check whether it is permitted and how to report its use; presenting GenAI-generated work as one's own may be treated as cheating.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

NYU does not license or endorse AI detection tools due to accuracy and reliability concerns.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Unauthorized use of ChatGPT or other Generative AI tools is considered cheating and/or plagiarism per Northwestern Academic Integrity guidelines.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Princeton University's McGraw Center for Teaching and Learning recommends that faculty do not use AI detection software to determine if student work is AI-generated, stating that detection tools are unreliable and biased.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

PolyU guidelines state that work submitted for assessment must be the student's own work and must not be a copy or version of other people's work or AI-generated material.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

A high AI score in Turnitin's writing detection report at the University of Melbourne is not proof that academic misconduct has taken place and does not on its own constitute grounds for making an allegation of academic misconduct.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

The use of applications to detect AI-generated content is strongly discouraged at UBC due to concerns about effectiveness, accuracy, bias, privacy, and intellectual property. Turnitin AI detection is not enabled.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Staff should not rely on AI detection software as it is not proven to be accurate or reliable and provides no evidence to support investigations into the use of GenAI.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

At the University of Chicago, AI-generated content may be misleading or inaccurate, and it is the responsibility of the tool user to review the accuracy and ownership of any AI-generated content.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.

Illinois CITL teaching guidance says faculty should define boundaries for AI use in student work and teach citation of AI-generated text and ideas.

Evidence records: 1. Original evidence remains canonical on the linked university record and public JSON.