Which universities mention AI disclosure?

UNSW uses a Levels of AI Assistance framework with six categories for assessments: No Assistance, Simple Editing Assistance, Planning or Design Assistance, Assistance with Attribution, Generative AI Software-based Assessments, and Not Applicable.

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

UNSW defines six high-level categories for permitted AI use in assessments: No Assistance, Simple Editing Assistance, Planning/Design Assistance, Assistance with Attribution, Generative AI Software-based Assessments, and Not Applicable.

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

At UNSW, the unauthorised or unacknowledged use of AI in assessments is classified as cheating and considered student misconduct under the Code of Conduct and Values.

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

ANU prohibits using AI to collect, use, store, or disclose personal information without express consent from the individual(s).

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

Students retain IP ownership of their assignments at ANU; staff may not upload student work to AI platforms without express student consent.

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.

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 recommends that faculty clearly communicate their generative AI policies in their syllabus, in assignment instructions, and verbally in class to support student learning and reduce academic integrity violations.

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

Cornell's committee report recommends that the Code of Academic Integrity be updated with clear and explicit language on the use of generative AI, indicating that individual faculty have authority to determine when AI use is prohibited, attributed, or encouraged.

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

Grammarly is listed for University of Pennsylvania in an official university AI tools source. Derived availability: conditionally allowed. Derived endorsement type: institutionally licensed or procured.

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

ChatGPT Edu is listed for University of Pennsylvania in an official university AI tools source. Derived availability: conditionally allowed. Derived endorsement type: institutionally licensed or procured.

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

Penn requires all community members (educators, staff, researchers, and students) to be transparent about the use of AI and to disclose when a work product was created wholly or partially using an AI tool.

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

The University of Auckland's Assessment of Courses Procedures state that AI use in assessment tasks may only be restricted when the task is a controlled assessment, identified as Lane 1; AI may be used without restriction in other assessment tasks, identified as Lane 2.

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

The University of Auckland's Assessment of Courses Procedures require courses to use the two-lane nomenclature, including telling students which assessments align with Lane 1 or Lane 2, and require courses and programmes to implement the two-lane approach in assessment design by 2027.

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.

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.

For Stanford Graduate School of Business (GSB) MBA and MSx courses, instructors may not ban student use of AI tools for take-home coursework, including assignments and exams. Instructors may choose whether to allow AI for in-class work. For PhD and undergraduate courses, GSB follows the university-wide Generative AI Policy Guidance from the Office of Community Standards.

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.

The UC Berkeley Academic Senate recommends that all faculty include a clear statement on their syllabus about course expectations regarding the use of Google Gemini or any other generative AI tool for course-related work. In the absence of such a statement, students may be more likely to use these technologies inappropriately.

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

The UC Berkeley Academic Senate provides three sample syllabus statement frameworks for faculty: 'Full AI' (GenAI required), 'Some AI' (limited permitted use with restrictions), and 'No AI' (all GenAI use prohibited). Faculty should modify these to fit their course requirements.

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.

Adelaide University's Academic Integrity Policy treats inappropriate use of AI that subverts an assignment or gives unfair academic advantage as an example of academic misconduct, including submitting AI-produced work as the student's own or using AI-generated information without acknowledgement.

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

Adelaide University's Authorship Procedure states that generative AI can be used to improve readability and clarity in publications, but must not be considered or listed as an author and its use must be disclosed transparently.

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

Adelaide University's Graduate Research School guidance says graduate research students' use of generative AI must be transparent and responsible, including discussing use with a supervisor, keeping records, and acknowledging AI use in thesis acknowledgements, presentations, and publications.

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

KTH tells students that generative AI use in graded assignments and exams should follow the course-specific information, and that the teacher's course rule takes precedence over general guidance.

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

KTH staff guidance says that, according to the Faculty Council recommendation, each course at KTH must include course-specific generative AI information in Canvas and the course memo.

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

KTH student guidance says course-specific generative AI information usually follows one of four approaches: no use, only specific assignments, allowed with guidelines, or free use.

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

NTHU's Chinese AI collaboration and literacy guideline recommends that faculty and students use AI in educational settings transparently and responsibly, with instructors clearly stating course AI rules and both students and instructors honestly disclosing AI use when relevant.

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

For educator teaching, NTHU's Chinese AI guideline says the university respects instructors' course AI-tool strategies and that instructors should state student AI-use rules in syllabi, especially correct AI citation and disclosure of the use process.

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

NTHU CTLD's course-syllabi generative-AI guidance encourages faculty members to specify course logistics and AIGC policies using four options: unrestricted use with no disclosure required, conditionally open, prohibited use, or not applicable.

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

SNU's AI Guidelines require transparent disclosure of AI use, fact and source verification, copyright/privacy/information security compliance, bias correction, and awareness of accountability.

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

SNU Library cites COPE's position that AI tools cannot be listed as authors because they cannot take responsibility for research results and lack legal personality.

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

SNU Library cites COPE requiring authors to clearly disclose in their methods section which AI tools were used and how, covering manuscript writing, image creation, and data analysis.

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 defines four approaches to AI use in courses: (1) prohibit all use, (2) use only with prior permission, (3) use only with explicit acknowledgement, and (4) free use without acknowledgement requirement.

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

CUHK penalties for academic dishonesty involving AI tools may include reviewable/permanent demerits, failure grade, suspension, lowering degree classification, and termination of studies.

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

The University of Manchester does not ban generative AI. The university's position is that when used appropriately, AI tools have the potential to enhance teaching and learning, and can support inclusivity and accessibility.

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

Manchester has adopted five core principles for AI use: transparency, accountability, competence, responsible use, and respect. All staff and students using or developing AI are personally responsible for adhering to these.

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

Students at Manchester must cite or acknowledge the outputs of generative AI tools when they use them in their work, including quoting, summarising, paraphrasing, editing, translating, data processing, re-writing, and idea generation.

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

The University of Sydney Academic Integrity Policy 2022 states students may only use assistance, including automated writing tools, if the unit of study outline expressly permits it, and must acknowledge assistance provided when preparing submitted work.

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.

University of Sydney states that students who use AI in assessments are required to acknowledge it, including any tools that use generative AI such as translation tools, paraphrasing tools or referencing tools; failing to provide acknowledgement can lead to a breach of the Academic Integrity Policy 2022.

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

The [genIA] ethics guide says practical AI use should clearly define what is allowed, ask for declaration and citation of tool use when appropriate, verify student understanding and original contribution, and avoid entering sensitive information into external services.

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

UdeC's [genIA] ethics page presents institutional guidelines and interactive tools for deciding how to incorporate generative AI in teaching and research while safeguarding transparency, authorship, privacy, and equity.

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

The [genIA] teacher annex presents three orienting institutional template options for course or assignment instructions: generative AI allowed with conditions, restricted by stages, or prohibited except with explicit authorization.

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.

Oxford requires postgraduate research students to include a statement on their use of generative AI in their final thesis submission.

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.

UVM's Code of Academic Integrity says course expectations may vary by instructor and students must understand expectations for each assignment and course.

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

UVM's faculty AI guidance says there is not a mandated one-size-fits-all classroom AI approach and tells faculty to clearly communicate how their AI stance shapes course policies and assignments.

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

UVM's student AI guidance tells students that the key course-context question is what the instructor has said about AI use, and that students should check syllabi and assignment instructions.

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

University of Zilina prohibits employees and students from entering sensitive data into publicly available GenAI tools, including non-public university data, non-public study materials, test assignments, intellectual-property-protected materials, personal data without explicit written consent, preliminary research results, and trade-secret data of partners.

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

For seminar, semester, and final theses, University of Zilina students must clearly state whether and to what extent they used GenAI tools, including the tool name/version, a brief use description, and prompts in an appendix.

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

University of Zilina prohibits students from submitting work generated by GenAI in substantial or full scope without their own creative contribution, and requires students to respect instructor restrictions on GenAI use in a course.

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

Boston University student guidance tells students to disclose GenAI use and states that submitting GenAI-generated or GenAI-assisted output without attribution is plagiarism that an instructor will treat as academic misconduct.

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

Boston University student guidance says instructors have broad discretion to set GenAI rules within each course, and students are responsible for complying with those instructions and should consult the course GenAI policy or ask the instructor before assuming GenAI use is allowed.

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

Boston University faculty and staff guidance says academic and administrative GenAI users should retain human oversight, evaluate and verify generated content, and disclose GenAI use in materials, documents, or publications.

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

Duke student-facing AI guidance says whether a student may use AI in coursework depends on instructor permission; unauthorized generative AI use is considered academic misconduct under the Duke Community Standard.

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

Duke CTL guidance tells instructors to update syllabi with clear guidance on generative AI use and says instructors may define how, if, and when generative AI may be used in their courses.

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

Duke CTL assignment-design guidance says AI assignments should be accompanied by course and assignment-specific AI policies, with the primary consideration being whether AI use helps students achieve course learning goals.

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

Emory Responsible AI guidance says public-facing AI platforms create disclosure risks for Sensitive Information and directs users to use Emory-approved secure AI tools when handling such information.

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

Emory Responsible AI guidance says students must review course syllabi, program handbooks, and faculty expectations regarding AI use because instructors may specify whether tools such as ChatGPT, Grammarly, or other generative technologies are permitted for assignments and under what conditions.

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

Emory College Learning Design guidance cites Honor Council language stating that, where AI is not allowed, using an AI program to generate assignment content constitutes plagiarism and an Honor Code violation, and unauthorized AI use may also constitute unauthorized assistance or other Honor Code violations.

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

HGSE (Harvard Graduate School of Education) school-level policy: Unless otherwise specified by the instructor, using generative AI to create all or part of an assignment (e.g., paper, memo, presentation, short response) and submitting it as one's own work violates the HGSE Academic Integrity Policy. Permissible uses include seeking clarification on concepts, brainstorming ideas, or generating scenarios that help contextualize learning.

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

HGSE (Harvard Graduate School of Education) school-level policy: For any permitted use of generative AI tools, students must acknowledge and document that use in their assignment submission by explaining what tool(s) were used, prompts provided, and how the output was integrated into the work. Direct citations must use proper citation format.

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

HGSE (Harvard Graduate School of Education) school-level policy: It is forbidden to make personal recordings of any course meetings, with or without AI tool integrations. Uploading substantial course content is only allowable through the Harvard-approved AI Sandbox.

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

KIT's SCC KI-Toolbox is available to KIT employees, KIT students from April 2026, and guests/partners after completing the required self-study course.

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

KIT's public German guidelines frame generative AI as a responsible and transparent-use decision aid for KIT, while stating that existing internal rules remain unaffected and take precedence.

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

KIT ZML says its KI-Policy and form-generator tools are not official or mandatory KIT requirements; final rules for coursework remain with the relevant faculty and instructor.

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

Kyushu University's basic stance says students should check in advance whether use of generative AI output is permitted for papers or works, and if permitted, should clearly indicate AI use or AI quotation.

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

Kyushu University's basic stance says course instructors may set generative AI use rules for individual classes according to each program or course objective, and should indicate those rules to students, such as in the syllabus.

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

Kyushu University's teacher-facing guidance says that when generative AI use is allowed, instructors should direct students to state quoted AI output, the AI service name, and version, and may request prompts and outputs.

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

Under the Economics Faculty rules, a student who uses AI tools for work must explicitly declare that use and identify the AI model, the parts of the work where AI was used, and the purposes and methods of use.

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

The Economics Faculty rules allow each teacher, within a discipline, to require detailed prompts or restrict AI-tool use up to a full ban, with restrictions recorded in the discipline's rating system and communicated by the first class.

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

The Economics Faculty rules place responsibility on students for correctness of facts, wording, citations, links, and interpretation of AI-assisted results, and treat unchecked use of AI results as an academic-ethics violation.

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

McMaster's teaching and learning generative AI guidelines say undergraduate and graduate course outlines should state acceptable and unacceptable generative AI use, and students should seek clarification and written confirmation if no syllabus statement is included.

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

McMaster's student generative AI coursework tip sheet tells students not to use generative AI unless a course syllabus or professor explicitly allows it, and to disclose and cite AI-generated content when allowed.

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

McMaster's teaching and learning guidelines say generative AI tools should not provide letter or numeric grades for student work, while AI-generated feedback may be used only under stated conditions such as syllabus inclusion and an opt-out ability.

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

National Taiwan University guidance says it takes a positive and constructive view of AI tools, encourages teachers to adjust course planning and learning assessment, and says students should understand AI-tool limitations for future learning.

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

National Taiwan University guidance recommends that instructors clarify AI-use principles and rules early in the course, preferably in the syllabus, including which activities and assignments may or may not use AI tools.

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.

NMBU's generative AI guidelines require students to clearly indicate how and where AI-based programs have been used, and to account for AI use in assignments or other work submitted for assessment or compulsory activity.

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

NMBU's generative AI guidelines state that AI-based programs are permitted in accordance with the guidelines, while individual course descriptions may state that AI-based programs are not permitted for exams or other assessed work.

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

NMBU's generative AI guidelines state that AI-based programs will normally not be permitted in written examinations on campus; for take-home exams, students must follow the AI-use specifications in the exam paper and course description.

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

Pusan National University's AI ethics charter/guidelines state that students may use AI as a supplemental learning or research aid, but should not undermine academic integrity and should disclose the source and scope when using generative AI.

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

Pusan National University's AI utilization guideline tells instructors to clearly announce in the syllabus or early in the course whether AI tools may be used, the permitted scope, and evaluation criteria.

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

Pusan National University's AI utilization guideline says instructors should communicate permitted or prohibited AI use for assessments, and it warns against deciding a student's grade solely from an AI plagiarism or AI-detection tool result.

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

Ohio State responsible-use guidance says students should use GenAI tools for coursework only with the explicit permission of each instructor, and only in the ways allowed by that instructor.

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

Ohio State Arts and Sciences guidance quotes the OSU Committee on Academic Misconduct policy that generative AI tools should not be used to complete course assignments unless the course instructor specifically authorizes their use.

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

Ohio State teaching guidance recommends that instructors establish expectations for academic integrity and AI use early, include university academic-integrity policies in the syllabus, and communicate course-specific GenAI expectations.

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

UQ course profiles must clearly state if, when, and how AI (including Machine Translation) is allowed. Two options exist: Option 1 prohibits AI in in-person assessment; Option 2 permits AI use with mandatory referencing.

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.

Student academic-integrity guidance says a full disclosure of GenAI-produced content should always be acknowledged, and passing off that content as one's own work counts as academic misconduct.

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

The PGR guidance permits students to use generative AI in thesis writing, provided the use is consistent with the guidance and properly declared, and warns that exceeding the guidance risks breaching the Academic Misconduct Policy.

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

Assessment guidance says that when GenAI use is allowed, students may be asked to provide full disclosure using an Acknowledge, Describe, Evidence template, while noting that some schools may use a different process.

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

The University of Tennessee system AI policy says course-related communications must inform students that unpermitted AI use is a form of academic misconduct subject to the campus student code of conduct.

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

The University of Tennessee system AI policy, which includes UT Knoxville, expects course faculty or staff to communicate permitted AI uses for a course and says students are responsible for following those course-specific AI requirements.

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

UTK Writing Center guidance tells students that when an instructor allows GenAI for writing assignments, they should use it to assist rather than replace their writing process and should document and describe the use.

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

CITEP/UBA presents La Brújul-IA as teaching guidance that offers conceptual keys and concrete strategies for critical, situated integration of AI in higher-education teaching.

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

The CITEP/UBA guidance frames ethical AI use as distinguishing legitimate support from improper appropriation and includes source attribution and recognition of AI co-creation.

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

The CITEP/UBA guidance says AI use in education should consider personal-data protection and digital security, noting that not all AI tools safeguard entered information.

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

For final documents submitted for evaluation at Unifesp or sent for publication, the generative-AI guidelines require an explicit declaration about the use of generative AI tools, including how the tool was used.

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

Unifesp's Resolution 17/2025 establishes guidelines for use of generative artificial intelligence in research and postgraduate work, with the stated aim of responsible and transparent use in scientific and academic production.

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

Unifesp states that researchers are responsible for critically reviewing texts, results, code, or images produced by generative-AI systems for correctness, coherence, originality, citation/reference compliance, and intellectual-property respect.

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

For students, unless course objectives or explicit instructor authorization allow it, UNamur proscribes delegating reflective analysis to generative AI, submitting work entirely or mostly generated by AI, and using copied, paraphrased, translated, or AI-generated material without indicating the source.

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

For students, unless course objectives or explicit instructor authorization allow it, UNamur says they cannot introduce non-anonymized or non-pseudonymized personal data into prompts addressed to generative-AI tools.

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

For students, UNamur allows some generative-AI uses without referencing when they are not contrary to course objectives, including brainstorming or organizing ideas without content creation, translation or summarization for comprehension, and short language improvement of text written by the student.

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

University of Regina policy OPS-080-050 says all University use of generative AI must be ethical, reliable, transparent, secure, and compliant with applicable laws and regulations; the policy primarily addresses governance and operations uses by employees.

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

The University of Regina Provost's message to students says individual instructors may determine whether and to what extent AI is permitted in course work, and warns that improper or unauthorized AI use can constitute academic misconduct.

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

University of Regina CTL guidance for faculty and instructors recommends that instructors set clear GenAI rules and syllabus statements, require students to disclose AI use when incorporated into coursework, and protect student privacy and intellectual property in teaching uses of GenAI.

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

University of Szeged student guidance says students using AI for assignments or other coursework must disclose the AI tool, purpose, method, and extent of use.

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

University of Szeged student guidance says AI may be used as an auxiliary tool but cannot replace students' own work; submitting an entirely AI-made work as one's own is treated as a serious academic ethics violation.

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

University of Szeged has an official 2025 framework for regulated and transparent AI use in education, with guidance published for instructors and students.

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

University of Wyoming Regulation 2-114 says submissions generated in whole or in part by an Artificial Intelligence-based application without attribution to the application will be treated as plagiarism.

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

UW Libraries AI Support guidance says users should cite AI tools and AI-generated outputs when quoting, paraphrasing, or incorporating AI-generated ideas into their own work.

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

UW Libraries AI Support student guidance advises students to use generative AI chatbots as supplementary tools, avoid copy-pasting chatbot responses into work, and check with instructors before using AI chatbots for assignments.

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

The Vilnius University AI guidelines treat undisclosed use of a generative AI model in academic work as academic dishonesty.

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

Vilnius University's AI guidelines state that use of generative AI models in research, written work, applications, and similar work must be clearly indicated.

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

Vilnius University Business School guidelines allow students to use AI tools in academic works, while requiring disclosure and treating failure to specify AI use and provide a transcript in annexes as academic dishonesty.

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

The Wageningen University Examining Board rules treat AI-created ready-made assignment content as an irregularity that may lead to suspicion of fraud unless AI use is explicitly allowed in the assignment description and adequately documented.

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

WUR's student GenAI rules tell students to check the course guide for whether and how GenAI is permitted; if the guide has no information, using GenAI to generate assignment content is not allowed and may be irregularity or fraud, including for theses.

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

WUR's student GenAI rules say students are never allowed to submit work entirely generated by GenAI as their own or fabricate research data, and they must be transparent about GenAI's role in submitted work.

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

Aalto University guidance says AI-based technologies are allowed as support for teaching and learning unless the course teacher instructs otherwise, and the teacher may set course- or task-specific restrictions when learning objectives require them.

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

Aalto University guidance says teachers who restrict AI use must give clear limitations connected to assessment criteria, and teachers may only require student work to be submitted through systems approved by Aalto University.

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

Aalto student guidance says students should contact the course teacher if AI use is unclear, mark AI-generated content in their text, and not present AI-generated content as their own.

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

ADA University's Honor Code treats violating exam, test, and assignment rules, accepting unauthorized help, and using someone else's intellectual work without proper credit as unacceptable behavior.

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

ADA University's Student Assessment Regulations say assignments are to be designed and conducted to minimize plagiarism and cheating risk, including contract cheating, and that students are to receive clear instructions on avoiding academic-integrity breaches.

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

ADA University's Student Assessment Regulations require submitted take-home exams to include a signed and dated academic-integrity declaration confirming the work is the student's own and that all sources used were acknowledged.

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

ABU's Research Policy is described as university-wide for research practice and defines plagiarism as research ethical misconduct; this is adjacent research-integrity context and not AI-specific guidance.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

Official ABU news pages say university leaders discussed updating teaching and learning policy for AI transparency/accountability and later stated that ABU had put strategies in place for use of AI in teaching and learning; the pages do not publish the full strategy or student-use rules.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

An official ABU conference news page reports a keynote statement that tools like ChatGPT can complete assignments instantly and challenge assessment and originality, but it does not state an ABU rule permitting or prohibiting student AI-tool use.

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

University of Bologna citation guidance says substantial GenAI contributions in teaching and research should be acknowledged and declared, with the statement identifying tools or models, date or period of use, modes of use, and where the tool was used.

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

Under the University of Bologna GenAI policy, students are responsible for checking permitted uses, following teaching staff instructions, verifying GenAI output, acknowledging original sources, and being able to explain work produced with GenAI support.

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

For GenAI use in assessed student work such as dissertation structure, dissertation writing, or programming code, University of Bologna guidance says the uses comply with policy principles only with active supervision, critical thinking, accountability for results, citation where required, and checking with the teacher whether the use is permitted.

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

American University guidance says students are responsible for course AI policies in syllabi, and misuse of AI or use without permission or disclosure may constitute an Academic Integrity Code violation.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

American University publishes responsible-use guidance for AI tools that applies general principles of transparency, accountability, human oversight, data protection, privacy, teaching, research, staff, and student use.

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

American University research guidance says researchers should be transparent about AI use, verify AI-generated content against trusted sources, protect data privacy, and not list AI systems as co-authors.

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

AUS policy says students are forbidden from using generative AI tools to produce assessment work unless the course instructor explicitly permits that use.

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

AUS policy says instructors must specify permitted generative AI tools, rationale, allowed assignments or activities, and an academic integrity statement in the course syllabus when AI tools are used.

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

AUS policy says students must acknowledge generative AI tool use in submitted course-credit material, including the tool name and version number.

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

AUTH's GenAI principles say use by members of the academic community should align with existing internal regulations, preserve academic integrity, and be explicitly declared when requested.

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

AUTH guidance encourages teaching staff to state clearly the GenAI-use policy adopted for a course, include it in the course outline, and modify it by assignment when needed.

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

AUTH student guidance says course teams define the GenAI policy for each course or assignment, and examples distinguish potentially permitted learning-support uses from uses such as submitting generated content as-is or using GenAI during an exam.

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

Auburn student-facing academic-integrity guidance tells students to review the syllabus and ask the instructor before using AI on coursework.

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

Auburn Graduate School guidance says graduate-student AI use in research and writing must be disclosed and approved by the student's advisory committee.

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

Auburn guidance says instructional faculty may encourage or restrict student AI use in courses and should give students clear expectations and disciplinary-consequence awareness.

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

Bilkent advises students to check course syllabi and instructors for whether and how GenAI tools may be used in specific courses or assignments.

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

Bilkent's GenAI guideline says students should attribute AI-generated content and should not submit AI-generated content without proper attribution.

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

Bilkent's GenAI guideline tells students not to use GenAI when a professor has not explicitly allowed it in the course syllabus.

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

In Caltech's Humanities and Social Sciences (HSS) division, students may use generative AI tools only in ways explicitly allowed by the course instructor in the course materials. Any usage not specifically allowed should be assumed to be disallowed.

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

The Caltech HSS generative AI policy applies to all assignments including major papers, exams, discussion board posts, reflections, and problem sets.

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

Caltech HSS students are expected to follow specific course guidance for documenting any permitted use of generative AI tools.

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

For Case Western Reserve University School of Medicine medical students in the University and College Programs, submitted or presented content must be the student's own work and not the product of generative AI or other individuals.

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

CWRU Provost classroom guidance gives faculty members discretion over the extent to which students may use AI tools in their courses.

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

CWRU's Writing Program does not recommend AI detection services and prefers classroom expectations, assignment design, and discussion with students when concerns arise.

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

Columbia Business School requires students to disclose to faculty their use of generative AI platforms and the manner of use in coursework.

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

Teachers College provides five example syllabus statements ranging from no AI use permitted to generally permitted with attribution, allowing instructors to choose their stance.

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.

Dalhousie's course syllabus guide says syllabi should include a statement about instructor expectations around generative AI and large language models such as ChatGPT.

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

Dalhousie's CLT course design guidance tells instructors concerned about student generative AI use in coursework to talk with students about what they can and cannot use it for and how to use it appropriately.

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

A Dalhousie CLT generative AI teaching handout says current academic integrity policy already covers generative AI use because students complete assignments on their own and must acknowledge sources of information or ideas that are not their own.

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

For Dartmouth AB undergraduates and special non-degree students, GenAI tools are disallowed by default for submitted coursework unless expressly permitted by the course instructor.

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

When GenAI tools are permitted in a Dartmouth undergraduate course, students are expected to disclose or acknowledge the use according to instructor guidance or a discipline-appropriate citation method.

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

Dartmouth instructors may define course-specific parameters for GenAI use, and their course GenAI policies define academic-integrity expectations for that course.

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

Lecturers determine whether and how GenAI may be used in their courses and for respective assessments. Teaching materials created with GenAI must be subjected to quality control by the lecturer.

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.

Students must refrain from disclosing copyrighted, private, or confidential information to commercial GenAI clients unless expressly permitted, and must respect privacy and copyright of content they work with.

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

Flinders states that students are responsible for using AI consistently with University, course, topic, assessment, and academic integrity requirements, including acknowledging generative AI use.

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

Flinders' student academic integrity page states that misusing AI tools includes using tools such as ChatGPT, Gemini, or DALL-E without topic coordinator permission and without appropriate acknowledgement or citations.

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

Flinders provides staff with AI assessment scale template instructions that range from no AI permitted through prompted, assisted, task-completion, and full AI use, with acknowledgement expectations attached to permitted use.

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

Hiroshima University tells course and thesis supervisors to judge whether generative AI may be used in classes or assignments and explain that decision to students through syllabi, guidance, or similar channels.

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

Where generative AI use is allowed, Hiroshima University's policy says students should be told that using AI output as-is may amount to copyright infringement or plagiarism, and that any use or quoted output should be made clear in reports and similar assignments.

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

Hiroshima University's basic policy frames student use of generative AI in coursework around students identifying problems and considering solutions themselves, while users understand AI's mechanisms, benefits, risks, and changing literacy requirements.

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

Jouf University says its University Council approved adding an "Artificial Intelligence" course as a basic course in the study plans for all students, starting in academic year 1447 AH.

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

Jouf University says the adopted AI course gives special attention to ethical and social aspects, including algorithmic bias, privacy, data protection, and legal and regulatory challenges linked to AI technologies.

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

Jouf University's adopted AI course is described as covering machine learning, deep learning, natural language processing, and computer vision through interactive lectures, dynamic discussions, and real case studies.

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

The Vice-Rectorate orientation guidelines say teachers are responsible for deciding which text-generating AI systems may be used in what form, and that the scope and form of use should be stated in the course description before the course starts.

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

For assessed writing, University of Graz guidance says AI use should be transparent: students should label and document AI use and follow the AI guidelines of the relevant course.

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

The University of Graz does not set a blanket prohibition on AI technologies for writing assignments; lecturers decide for each course which text-generating AI systems may be used and how.

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

Keio University says students need to clearly indicate when reports or similar assignments are created using generative AI.

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

Keio University says generative AI is not permitted for class assignments or exams when students are required to work independently.

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

Keio University tells students to use generative AI appropriately under the relevant faculty or instructor policy when a course, faculty, graduate school, or instructor encourages or permits its use.

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

Khon Kaen University's Graduate School states that failure to disclose AI use in a thesis or independent study is regarded as a violation of academic ethics and may be subject to penalties under relevant regulations.

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

Khon Kaen University's Graduate School states that AI is only a supporting tool for thesis or independent study work, and students who use AI must specify the type and content of the AI use in the thesis or independent study report.

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

Khon Kaen University's Graduate School classifies proofreading, grammar or spelling correction, readability rephrasing without altering core content, and translation for comprehension or cross-language communication as low-risk acceptable AI uses in thesis or independent study preparation, provided the use is disclosed.

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.

Korea University instructs instructors to decide course AI-use policies based on course purpose, teaching method, and assignment nature, and to state the policy in the syllabus.

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

Korea University tells learners to check each course’s AI-use guideline before coursework and ask the instructor if permission is unclear.

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

KU Leuven student guidance says students remain fully responsible for what they submit and must ensure assignments allow teaching staff to assess their acquired competences.

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

KU Leuven student guidance says clear misuse of GenAI, where output is largely generated by GenAI and the student is not transparent about tool use, can be considered an irregularity under Article 84 of the Education and Examination Regulations.

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

KU Leuven teaching guidance expects teaching staff to clearly inform students whether GenAI may be used for assignments and expects students to be transparent about GenAI use so assessment can be fair and correct.

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

Lehigh's human-subjects research guidance says use of AI to analyze or process data must be disclosed to participants during consent.

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

Lehigh says students are expected to follow instructor-set course rules and university academic integrity rules when using generative AI.

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

Lehigh advises instructors to give students clear guidance on how generative AI tools may be used in coursework and research.

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

Macquarie student guidance categorises assessment tasks as Open or Observed: Open tasks allow generative AI with acknowledgement and student responsibility, while Observed tasks may restrict or prohibit AI use.

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

Macquarie's research guidance says researchers using generative AI should mitigate sensitive-data risks, keep oversight and control, critically review outputs, and disclose or acknowledge generative AI use in research.

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

Macquarie Library referencing guidance says students who use generative AI in assessments should clearly state how they used it and fact-check AI responses against reliable sources.

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

MSU guidelines say students may use generative AI tools for coursework or research activities only when the instructor or research advisor explicitly permits that use.

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

MSU expects instructors to include course-specific generative AI guidance in every syllabus, including whether AI use is permitted, the contexts in which it may be used, and expected acknowledgment or citation practices.

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

MSU guidelines say integration of generative AI into research outputs, manuscripts, artistic endeavors, and grant applications must be disclosed according to relevant guidance or policies, and that intentional and substantial AI uses should be disclosed when no stated guidance exists.

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

Middlesex guidance tells students to consult their module tutor before using AI for studies or assignments and says submitting AI-generated work as their own is a breach of academic integrity.

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

Middlesex states that generative AI tools may be used in assessments only as specified by the module leader, and allowed use requires written acknowledgment, extent of use, generation details including prompts, and citation or referencing where generated material is not adapted.

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

Middlesex guidance says assessment criteria should make clear when and how students can use AI for each assessment, and how to acknowledge AI use appropriately.

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 states that instructors should be transparent about where and how they deploy AI in courses, including for generating content, virtual tutoring, and assessment feedback.

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

NUS policy sets the default assumption that AI tool use is permitted for unsupervised (take-home) assessments, provided use is duly acknowledged; assessments forbidding AI must be conducted in-person and instructor-supervised.

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

Oregon State University Student Community Standards states that misuse of GenAI on an assignment could violate the university's Academic Integrity Policy, including plagiarism, cheating, or fabrication.

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

Oregon State University strongly encourages instructors to include a syllabus statement about whether and how students should engage with GenAI in their course learning and assignments.

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

Oregon State University tells students that faculty may set course-specific AI expectations and that students must follow the specific expectations for each course.

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

Princeton University requires students to disclose the use of generative AI when permitted by the instructor, rather than cite or acknowledge the use, since generative AI is an algorithm rather than a source (Rights, Rules, Responsibilities section 2.4.7).

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

Princeton University states that inappropriate uses of generative AI on any work submitted to fulfill an academic requirement, including directly copying the output, representing output as the student's own, exceeding instructor parameters, or failing to disclose its use, would constitute violations of academic integrity (Rights, Rules, Responsibilities section 2.4.6).

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

Princeton University states that the decision to allow, limit, or prohibit generative AI in a course or in undergraduate independent work remains with the faculty; faculty members have the discretion to set their own generative AI policy for their courses.

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

RMIT academic integrity guidance says students cannot use AI to complete or contribute to an assessment task unless specifically allowed, pass off unreferenced AI-produced ideas as their own, or submit AI-produced content they cannot understand or explain.

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

RMIT assessment guidance tells students to review and fact-check AI outputs and acknowledge AI tools when those tools contribute ideas, text, images, or other content to assessment work.

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

RMIT says whether students may use AI in assessments depends on their course and Course Coordinator instructions, and students should check with the Course Coordinator if unsure.

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

Royal Holloway academic misconduct regulations list requesting or engaging an artificial intelligence tool to write or rewrite work for unfair advantage, and presenting AI-generated content as one’s own unless authorised and acknowledged, as examples of assessment offences.

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

Royal Holloway Doctoral School guidance for postgraduate researchers says AI may not author or generate research claims, thesis prose, or other academic content, and that researchers are responsible for every output they submit.

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

Royal Holloway requires students to include declaration statements for generative AI use or non-use, and says a list of all prompts entered into any large language model must be provided.

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

Rutgers Academic Integrity Policy 10.2.13 applies to all schools and academic units and says students must ensure submitted course, research, or other academic work is their own and created without impermissible technologies, materials, or collaborations.

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

Rutgers OIT guidance says AI use in academic settings typically varies by discipline, course, or instructor; students should not consider AI tools permissible for coursework unless instructors clearly state or communicate permission.

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

Rutgers teaching guidance recommends clear and transparent course policies around generative AI, class discussion of those policies and rationales, and, when GenAI is permissible, student disclosure and reflection on use plus submission of prompts and outputs.

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

Sapienza's final-paper originality declaration requires students who used AI, automatic translators, grammar checkers, or data-analysis software to transparently declare the tool function and specific use, and says AI was not used to generate substantial content or automate any section.

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

For Sapienza CAD Psychology undergraduate final papers, generative AI tools such as ChatGPT and Gemini may be used as drafting support only with careful, transparent use and personal critical revision by the student.

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

For Sapienza CAD Psychology undergraduate final papers, the guidance treats uses such as relying on AI for bibliographic discovery, unverified citations, article summaries, critical analysis, delegated writing, automatic responses to supervisor feedback, data manipulation, fake results, or uncited AI content as illicit.

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

Shenzhen University guidance says serious violations of instructor AI-use rules, concealment, presenting AI-generated content as original work, or failing required disclosure/marking can affect course grades and may be handled under academic misconduct rules.

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

Shenzhen University guidance says course instructors should tell students whether AI technologies are permitted in coursework, papers, assessments, exams, and the permitted scope.

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

Shenzhen University guidance says researchers using AI technology in research activities should disclose the AI tool name, version, parameter settings, use, and verification process in appropriate parts of the work and follow publisher rules during publication.

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

SFU guidance says AI detectors cannot be used for grading decisions or academic misconduct investigations.

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

SFU tells students that use of generative AI for coursework depends on instructor permission, and students should not assume it is permitted when guidance is unclear or absent.

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

When an SFU instructor permits generative AI use, SFU tells students to cite or disclose that use appropriately as part of academic integrity.

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

Stockholm University's AI resources page says employees signed in to Microsoft 365 with a university account have data protection for Copilot, but it also says information at confidentiality level 3 or 4 should not be entered into Copilot.

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

Stockholm University's central chatbot guidance recommends that teachers and examiners decide what AI-chatbot use is allowed or impermissible, noting that this may differ from course to course.

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

Stockholm Business School says use of generative AI in examinations or mandatory assignments is prohibited unless explicitly allowed in the study guide or examination instructions.

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

Tampere University tells students to openly and transparently acknowledge AI use in assignments, coursework, or theses and to describe how AI was used.

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

Tampere University's academic ethics guideline treats presenting AI-produced work as one's own without proper mention as academic misconduct.

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

Tampere University generally permits students to use generative AI applications to support learning and assignment completion, while allowing teachers to set course or assignment principles.

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

DTU states that it permits generative AI in teaching and open-internet exams, while current exam use is limited to selected courses and exams.

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

DTU tells students they may use AI in their studies if they clearly state when and how they use it and follow source-citation rules.

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

DTU Library guidance says generative AI use in project reports and final project assignments must be distinctly declared, including how it was used.

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

The University of Arizona student AI guidance tells students they can use AI for assignments only if the instructor says it is OK, and says unpermitted use could violate the Code of Academic Integrity.

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

The University of Arizona's central AI guidance states that there is currently no single university-wide policy specific to AI use in coursework, while instructors are encouraged to set clear course-material expectations.

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

The University of Arizona says generative AI use in coursework is guided by the Code of Academic Integrity, and submitting AI-generated work as one's own without permission is included in the academic-dishonesty concern described by the university.

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

At the University of Melbourne, using GenAI tools to produce work submitted for assessment without acknowledgement constitutes academic misconduct under cl. 4.13 of the Student Academic Integrity Policy (MPF1310).

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

University of Melbourne students must appropriately cite any use of GenAI tools in the preparation of assessment submissions.

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

At the University of Melbourne, generative AI tools can only be used in research outputs where the material generated or substantially altered by these tools is acknowledged according to the University's policy and the Australian Code for the Responsible Conduct of Research.

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

For assessments, UON's GenAI teaching, learning and assessment policy says students should follow teaching-staff directions about GenAI use and appropriately disclose and reference GenAI use.

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

UON's GenAI teaching, learning and assessment policy says use of GenAI in assessment does not automatically constitute academic misconduct, but may do so where lecturers or course coordinators have explicitly prohibited it.

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

UON's GenAI teaching, learning and assessment policy says GenAI should not be used to mark student work unless the output is reviewed and approved by the course marker or coordinator, and any GenAI marking use must be clearly communicated with an opt-out opportunity for students.

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

Warwick's student-facing guidance says students are required to state whether AI was used in the submission process and explain why, where, and how it was used.

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

Warwick's student-facing guidance says students may use AI only within requirements set out in assessment briefs and course handbooks, which may restrict or prohibit AI use.

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

Warwick's AI in research guidance says researchers are responsible for misconduct-type practices involving AI, including improper handling of information or use of another person's ideas, even if such practices occur inadvertently through an AI tool.

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

UAEU prohibits student use of GenAI in specified assessment contexts unless the course instructor states otherwise.

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

UAEU tells students that information gained from GenAI should be checked against recognized sources and that those sources should be cited.

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

UAEU states that students must complete a training session as part of orientation to comply with the GenAI policy.

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

The Biotechnology bachelor's thesis guideline says that if a student used AI tools at any stage of thesis writing, the student is required to explicitly declare the tool, version if available, date, and nature of use in a methodological note.

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

The Biotechnology bachelor's thesis guideline says students should not insert automatically generated scientific text into the thesis, replace bibliographic research with AI, or use AI-generated text without critical and personal reworking.

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

The Biotechnology bachelor's thesis guideline says non-compliance with its AI-use indications is treated as comparable to plagiarism and may lead to disciplinary sanctions under the university regulation.

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

The guidance states that if active use of an AI tool in a course requires registration with personal data, that use must be voluntary because GDPR must be observed.

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

The central guidance recommends that instructors formulate clear course guidelines governing generative AI use and discuss them with students.

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

Universität Konstanz has public central AI-in-teaching guidance, but the collected official sources should be treated as guidance and resource pages rather than a staged canonical finding of a formal university-wide binding AI policy.

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

UGA's AI reference framework says students using generative AI must mention the use of generative AI and its name, identify the parts generated by or with AI, and cite sources correctly to avoid plagiarism.

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

UGA's AI reference framework says use of tools mobilizing AI is prohibited by principle for knowledge assessment unless explicitly authorized, with study regulations and assessment modalities specifying the AI-use framework.

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

UGA's AI reference framework says researchers using generative AI must verify whether generated ideas come from existing sources, add appropriate references, mention the use and name of the generative AI, and identify parts generated by or with AI.

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

Université Lumière Lyon 2's règlement intérieur prohibits using an artificial-intelligence tool in university work without explicit mention, and prohibits presenting AI-generated content as personal human work, under disciplinary proceedings.

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

Lyon 2 SPS guidance says AI should not do assessed work in place of the student; AI assistance may be possible only when it respects university ethics and the specific instructions for the exam or assignment.

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

Lyon 2 SPS guidance recommends that instructors explicitly state expected conditions for student work, including obligations, permissions, recommendations, prohibitions, whether generative AI may be used, and how any use should be signaled.

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

UCD's Academic Integrity Policy says AI-generated content may not be submitted without explicit permission and attribution, and that generative AI outputs must be used critically, ethically, cited, and acknowledged.

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

University College Dublin publishes University Management Team-approved AI Governance Principles for institutional AI use, including human oversight, fairness, transparency, compliance, ethical design, AI literacy, stakeholder engagement, and risk assessment.

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

UCD Teaching and Learning assessment guidance advises educators to be transparent with students about permitted AI use and to apply more robust approaches for high-stakes graded assessments.

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

The University of Basel AI citation guidelines state that AI tools must always be cited like other tools and sources, and that student papers without complete attribution may be seen as attempted plagiarism or cheating.

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

The University of Basel AI citation guidelines say AI-supported tools may only be used in a supporting role for work submitted for credit, with students retaining a controlling role and responsibility for their own work.

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

For regulating AI use in exams and assessments, the University of Basel lists task adaptation, preventing tool access, and declaration-of-independent-authorship restrictions as measures.

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

The UC Davis School of Medicine policy says medical students may not use generative AI to directly author submitted assignments or generate answers for closed-book assessments unless faculty or course leadership gives written permission.

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

UC Davis guidance tells students to confirm with instructors before using AI in coursework and not to use AI to complete assignments unless explicitly permitted.

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

The UC Davis School of Medicine policy says medical students are not permitted to use external generative AI tools for patient care documentation except as allowed under UC Davis Health policy, and PHI must not be entered into a generative AI tool outside a secure institutionally supported system.

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

UCR's student-facing AI announcement says students should discuss generative-AI expectations with professors, use AI to assist or enhance rather than replace original work, avoid generating entire deliverables, and cite AI-generated content or data when used.

Evidence records: 3. Original evidence remains canonical on the linked university record and public JSON.

UCR XCITE advises instructors to discuss when AI may be used in coursework and how it should be cited, and its sample syllabus language treats uncited AI use as a potential academic-integrity issue.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

UCR's public generative-AI guidance for instructional settings places course-level use decisions with the Instructor of Record rather than setting one universal student-use rule in the evidence reviewed here.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

Within UNIGE's Faculty of Science, sensitive data such as personal data must not be disclosed to a public AI tool that does not guarantee confidentiality.

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

Within UNIGE's Faculty of Science, a formal declaration of generative AI use is required for all bachelor's, master's, or doctoral work and for academic assessment or production leading to a degree or official title.

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

UNIGE formally expects full transparency about AI tool use in academic work through appropriate citation rules, with possible description of the methodology used with AI support.

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

Regulation 32 says use of websites or generative AI software that generates answers or references is prohibited, while some Schools may allow AI tools for specific purposes and any AI use must be referenced.

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

University of Glasgow student guidance says using AI or other computational aids in university work without acknowledging the input counts as academic misconduct.

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

University of Glasgow student guidance says the university does not seek to prohibit student AI-tool use generally and instead supports effective, ethical, critical, and transparent use.

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

University of Göttingen AI ethics and law guidance tells users not to enter personal data into AI applications unless it has first been securely and completely anonymized, and says students may not be required by lecturers to use or register for such systems in courses.

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

For unsupervised examinations, University of Göttingen guidance says AI models should generally be permissible aids, but use of AI tools must be transparent.

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

University of Göttingen guidance says students need clarity about AI-use rules in courses, and that those rules should be discussed at the beginning of each semester in all courses.

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

UIC College of Medicine policy states that students are expected to draft submitted assignments on their own; AI may assist with idea generation and editing, but AI directly authoring a response is considered a violation of academic integrity and professionalism.

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

UIC College of Medicine policy prohibits students from generating patient care notes with AI applications except EHR-supported applications explicitly permitted by course leadership, and says protected health information should never be entered into outside generative AI tools.

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

UIC CATE recommends that instructors develop and include an AI usage policy in their syllabus after sharing their stance on AI writing tools in the course.

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

University of Luxembourg guidance says generative AI use should be disclosed according to each course and assessment, with course guidelines serving as the primary point of reference.

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

University of Luxembourg guidance lists non-permitted AI practices, including undisclosed submission of AI output as one's own work, using AI to replace the central assessed intellectual contribution, fabricating data or citations, and trying to conceal AI involvement.

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

University of Luxembourg assessment guidance says chatbot use in assignments should align with academic integrity and scientific judgement, and students should disclose where and how the chatbot influenced the text.

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

For coursework, UMD tells students to assume GenAI use for assignments and assessments is not allowed unless the syllabus or assignment instructions specify otherwise.

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

UMD strongly encourages instructors to establish course-specific policies defining appropriate and inappropriate GenAI use.

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

UMD's Division of Academic Affairs advises against incorporating GenAI detection tools into course policies and says detection results should be treated only as potential indicators, not definitive proof or the sole basis for grading decisions.

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

For 2026 NSFC applications submitted through USTC, the university notice says applicants who use generative AI to track research trends or collect and organize references must manually verify the truth and accuracy of generated information and references, take responsibility for generated content, and fully and truthfully declare AI use.

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

For smart-course projects under USTC's 2026 undergraduate teaching-project guide, completion standards include at least two online teaching cycles and mandatory AI learning or teaching support plus knowledge-graph functions, with two additional optional digital or AI functions.

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

USTC's 2026 undergraduate teaching-project guide encourages new-course projects to integrate AI technologies with core professional competencies and to include AI application techniques, cases, and practical training in lectures and practice teaching.

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 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.

UT Austin classroom guidance recommends that instructors requiring generative AI understand and abide by UT acceptable-use guidance, identify syllabus policies clearly, and submit specific software requirements through the University Co-Op.

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

UToledo's Academic dishonesty policy lists representing the words, ideas, or information of an artificial intelligence program as one's own without proper documentation as an example of academic dishonesty, and says faculty are expected to tell students what materials and procedures, including artificial intelligence programs, are authorized.

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

UToledo's Simple Syllabus guidance says the AI Tool Usage section is required and private, and instructors must select or enter a statement explaining how generative AI tools may be used, limited, or prohibited in the course.

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

Within the University of Toledo College of Law default rule, generative AI may be used for research-like search, grammar correction, and other functions attendant to completing an assignment, but may not compose submitted assignment text and may not be used for any exam purpose unless an instructor deviates in writing with notice.

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

UVA Provost guidance says that if an assignment involves students uploading original work into a GenAI tool, instructors must provide alternative ways to complete the assignment.

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

UVA guidance says students who use AI in completing an assignment should clearly indicate the tool used, how it was used, prompts used, and, when appropriate, fact-checking efforts.

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

UVA guidance says instructors should make explicit in syllabi and assignment descriptions which GenAI uses are permitted or prohibited, and that using GenAI in ways prohibited by the instructor may violate the Honor Code.

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

Utah State University's AI Use & Compliance guidance says AI-generated content must be reviewed for accuracy, bias, and copyright compliance before use in coursework, research, or administrative communications.

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

Utah State University's teaching guidance says instructors have autonomy to determine class AI guidelines, but those guidelines must be clearly defined in the syllabus and enforced through Article VI of the Student Code.

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

Utah State University's student AI resources say ChatGPT and other generative AI tools should be treated like other sources for plagiarism and academic integrity, and students should check each professor's policies for when and how AI tools may be used in assignments.

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

VU Amsterdam's framework says the lecturer or examiner indicates in the study guide, syllabus, or Canvas whether and how use of generative AI is allowed for a course, with course learning objectives remaining leading.

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

VU Amsterdam's research guidance says GenAI use in research must meet scientific-research standards, take existing VU policies on ownership, scientific integrity, privacy, personal data, and knowledge security into account, and be transparent about which parts of research used GenAI.

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

VU Amsterdam's Dutch academic-integrity page states that work made by generative AI is not the student's own work and lists using an AI writer to write an assignment as an example of fraud.

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.

Yale expects faculty to give clear instructions on permitted AI use and attribution, and expects students to follow instructor guidelines for coursework.

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

Yale states that instructors have authority within each course to determine whether and how students may use AI on assignments.

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

Yeshiva University's undergraduate academic integrity policy treats unsanctioned use of Generative AI or Assistive AI as a potential academic integrity violation and tells students to assume generative-capable platforms are prohibited unless allowed for the course.

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

Yeshiva University's undergraduate policy permits faculty to allow Generative AI in courses or assessments if they specify in writing how it may be used; content produced using Generative AI must be cited according to the relevant subject conventions.

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

Yeshiva University's faculty and staff AI acceptable use policy says individuals using Generative AI in research must be transparent about its use and researchers must avoid uploading unpublished research data or Internal or Restricted Information into Generative AI tools.

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

Aarhus University student guidance says students who use GAI in an exam project must submit a declaration naming the applications and explaining how they were used, and unchanged GAI output used in an exam project must be cited like other secondary-source quotations.

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

Aarhus University student guidance says the main rule is that students are allowed to use GAI unless their academic regulations or the course catalogue explicitly state that GAI is not allowed.

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

AU Educate guidance for teaching staff says that from fall 2024 students are allowed to use GAI in all AU exams unless academic regulations or the course description explicitly state that they may not, and it advises teachers to read those rules for their courses.

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

Åbo Akademi University's Open University teacher guidance says teachers cannot require students to use AI to complete an assignment because AI requires registration on an external service.

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

Åbo Akademi University's research data guidance says researchers are responsible for their own work, should check all AI-produced results, and should be transparent about AI-tool use.

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

Åbo Akademi University's Open University teacher guidance says students in courses should be informed about the principles and disadvantages of AI or language-model use, and teachers should make clear what applies in each specific course.

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

Adam Mickiewicz University has Rector order 426/2023/2024 setting rules for student use of AI systems in education, including theses and coursework/assessment work.

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

For classroom/course work, AMU recommends that the course coordinator choose the appropriate level of AI-use control based on the syllabus, and that the instructor inform students about permission or prohibition at the first class.

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

AMU classroom guidance says that, in course contexts where permission or marking is required, use of generative AI tools without permission or without appropriate marking is treated in the same way as plagiarism.

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

AAU's AI instructions allow students to use AI tools for self-learning, initial project and research ideas, and text or data analysis, but prohibit submitting AI outputs as-is, generating complete or nearly complete assignment/project answers without being able to explain them, or using tools that lead to cheating or breach academic integrity.

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

AAU's AI instructions require students to document AI use by explicitly identifying the tool used and where and how it was used in assignments, research, and projects, while observing intellectual-property rights.

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

AAU's AI instructions allow faculty members to use AI tools for educational content, learning activities, rubrics, and student-performance analysis, while requiring the faculty member to remain the course's primary scientific source and not rely fully on generated outputs without review.

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

ASU Provost guidance says data for the described generative-AI teaching support is securely maintained within ASU infrastructure, supporting privacy and transparency.

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

ASU Provost FAQs direct students to confer with their instructor about class policy before using AI tools in coursework.

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

ASU Library guidance says acknowledging the use of generative AI tools is a key part of maintaining academic integrity.

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

Ashoka University's Academic Integrity Policy applies to students doing coursework, research, thesis work, partner-university coursework, study-related internships or placements, and work with University Centers; it expects original work, source acknowledgement, independent assignment completion where applicable, and honesty during examinations.

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

In the Ashoka University course catalogue entry for Economy, Politics and Society (FC-0412-5), the course-level AI/ML policy discourages use of machine-learning tools such as ChatGPT in that class and asks students who use such a tool to declare its use and specify the extent of use.

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

Ashoka University's public Academic Integrity Policy page gives general academic-integrity and citation guidance, including mandatory academic-integrity workshop language, but the extracted public page text did not contain AI-specific, ChatGPT, or generative-AI rules.

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

For ACU coursework students, unauthorized or undisclosed use of generative AI, paraphrasing or translation tools is listed as academic misconduct unless use is authorized in the assessment requirements and properly acknowledged.

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

ACU research guidance says HDR candidates should declare GenAI use for thesis copyediting/proofreading, discuss intended research use with supervisors, record and acknowledge tool usage and prompts, and should not input sensitive or confidential information into GenAI tools.

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

ACU Library guidance tells students that GenAI may be permitted in some contexts, but assessment use should be clearly authorized and acknowledged, and final work should reflect the student's own analysis and understanding.

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

Bar-Ilan University guidance requires students to declare whether they used generative AI tools in an assignment and to explain the specific contribution made by GenAI.

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

Bar-Ilan University guidance leaves whether and how students may use generative AI tools to instructor discretion; if an instructor has not explicitly prohibited use, use is permitted by default when the student explicitly discloses all use.

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

Bar-Ilan University guidance instructs users not to disclose personal or sensitive information to generative AI platforms and says generative AI tools must adhere to Bar-Ilan data security guidelines.

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

Beijing Jiaotong University's 2023-2024 undergraduate teaching quality report says the university opened liberal-arts/science-track AI general courses and aimed for AI course coverage for the 2024 undergraduate cohort, except where programs already include AI courses.

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

For the Zhan Tianyou College-related 2024 undergraduate training model described in the report, BJTU required majors in the information ability module to add AI-specialized courses categorized as AI foundation, AI expansion, and AI frontier courses.

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

BJTU's undergraduate teaching quality report says the university developed AI-enabled course pilots using large-model technologies around knowledge graphs, 24-hour intelligent learning companions, AI teaching assistants, and AI mentors, with experience to be promoted across the university.

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

Bournemouth University academic-offences guidance lists using artificial intelligence software to write all or part of an assignment and claiming the work as your own as an example of an academic offence.

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

Bournemouth University student guidance says using generative AI when writing coursework is not, by itself, an academic offence, while directing students to use the resource responsibly and appropriately.

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

Bournemouth University's 6H taught-awards policy defines academic offences as attempts to gain unfair advantage in assessment by deception or fraudulent means and frames academic integrity around responsibility for one's own work, acknowledging others' work, honest reporting, and avoiding unfair advantage.

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

VUT requires users to properly state when a result was achieved using generative AI, including the extent of use, and warns that incorrect or undisclosed use may be treated as an ethical violation such as ghost-writing or contract-cheating.

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

For creative activity, VUT supports generative-AI use by academic and research staff, but says employees must state which tools were used and the extent of use when creating scientific or artistic outputs.

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

For operational-administrative work, VUT supports employee use of generative AI and says employees may use it to perform work duties, while stating which tools were used and the extent of use.

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

Brown Provost guidance says any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Graduate Student Edition Academic Code.

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

Brown University Provost guidance says the University is not prescribing specific AI policies, and that faculty should give clear, unambiguous information about what AI use is and is not allowed in their courses.

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

Brown Sheridan Center guidance says instructors should be explicit with students about expectations for generative AI use, including how students should, might, or cannot engage with it.

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

For thesis work, Chalmers says AI tools may be permitted, but students are required to take full responsibility and make AI-tool use clear and transparent, including how and to what extent the tools were used.

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

Chalmers Library's student guidance connects AI use to plagiarism or ghostwriting risk and says students need to be fully transparent, describe what they did, and cite the AI tool used.

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

Chalmers Library's student guidance says whether and how AI tools may be used in examinations is decided for each course by the coordinator and examiner, so students should ask at the beginning of each course.

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

Chang Gung University student guidance tells students to follow course AI-use rules, clearly mark AI use when permitted, avoid directly copying AI-generated content, and not use AI in exams unless specifically allowed.

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

Chang Gung University teacher guidance advises instructors to state AI-use rules in syllabi, choose whether AI use is fully open, conditionally open, or prohibited, and explain scope, marking requirements, and grading criteria.

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

Chang Gung University researcher guidance treats AI as a supporting tool, says core arguments and innovative results should be written by researchers, and calls for clear disclosure and verification of AI-generated content.

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

CDU requires students and employees to be transparent about and disclose GenAI use, with academic integrity guidance applying to students.

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

CDU's academic integrity guidance identifies inappropriate or unsanctioned GenAI use as academic misconduct and says CDU will not tolerate misrepresenting AI-generated content as a student's own work or failing to disclose AI use.

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

For HDR studies, CDU guidance says GenAI may assist but should not replace a candidate's original intellectual contribution, GenAI use should be clearly acknowledged, and supervisors or external examiners should not use GenAI to critique or assess candidate work.

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

China Medical University's Academic Affairs generative AI teaching guidance asks instructors to communicate with students about course-specific ways and limits for using generative AI.

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

China Medical University's Academic Affairs guidance tells teachers and students to consider academic-ethics concerns before using generative AI and to avoid plagiarism and copyright violations in assignments, exams, and research papers.

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

China Medical University's R&D reference guidance frames generative AI as a research-assistance tool and says researchers should verify AI-generated content, understand related policies, disclose use where required, and remain responsible for research outputs.

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

Chonnam's generative-AI writing assignment guideline tells instructors to state in the syllabus whether generative AI is allowed and, when allowed, to explain scope, misconduct criteria, the ethics pledge, and checklist use.

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

Chonnam's generative-AI writing assignment guideline identifies improper AI uses that can constitute misconduct, including submitting copied AI output without attribution, patchworking AI output without attribution, using AI to create or spread false information or experiences, infringing copyright or intellectual property, and using AI in a class where it is fully prohibited.

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

Chonnam's generative-AI writing assignment guideline cautions learners that information entered into generative AI may be stored on servers and used to improve performance, so they should be careful about security and information leakage.

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

Chungnam National University's learner guide states that not following syllabus or instructor-agreed generative-AI criteria, or inappropriate AI use, may be regarded as cheating; examples include presenting AI answers as one's own, failing to disclose AI use, or using AI in a class where it is fully prohibited.

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

Chungnam National University's learner guidance says learners should follow instructor-provided generative-AI criteria, use AI as a learning support tool, verify AI outputs against reliable sources, and clearly mark the source, generation method, and scope of AI-generated materials.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

Chungnam National University's instructor guidance says that when generative AI is used in class, instructors should state its purpose and scope in the syllabus, explain correct use and standards for cheating or plagiarism, and guide students to cite AI-generated outputs.

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

CUNY's Academic Integrity Policy says use of generative AI tools must align with the usage policy for specific assignments as defined in the syllabus or communicated by the instructor.

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

CUNY's Academic Integrity Policy includes unauthorized use of AI-generated content, including paraphrased AI-generated content without citing AI as the source, as an example of plagiarism.

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

CUNY's AI Academic Hub advises faculty to guide AI use with clarity by establishing responsible AI engagement in coursework.

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

Comillas states that using AI to create complete works or relevant parts without citing the source or tool, or without express permission in the assignment description, will be considered plagiarism under the university's general regulations.

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

Comillas permits students to use AI as a reference tool when the use is acknowledged and cited, and directs students to check each course guide and consult the instructor for activity-specific rules.

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

Comillas says teachers who incorporate AI tools in their courses should ensure that the conditions for use are clearly established in the course guide.

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

Concordia's CTL GenAI FAQ says the university does not currently have an official policy regarding the use of GenAI, and explains that GenAI has not officially been adopted by the university so its use cannot be required in coursework.

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

Concordia CTL encourages faculty to clearly state their position on GenAI use in courses, including in the syllabus and in class, and provides adaptable sample statements for encouraged, limited, or prohibited use.

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

Concordia Student Success guidance tells students not to assume GenAI is allowed if an instructor does not mention it, and says permitted use of generative tools for academic work must be cited.

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

DLSU's generative AI policy says faculty and students must provide a written disclosure statement when generative AI is used in producing material, presentations, or submissions.

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

Starting Term 1, 2025-2026, DLSU's policy says every course must include a dedicated Generative AI Use Policy section in the syllabus, including usage policy levels for grading components and a concise rationale.

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

DLSU's policy treats prohibited generative AI use and failure to disclose generative AI use as generative AI-related academic dishonesty, while also stating that AI detector results cannot be the sole basis for establishing such dishonesty.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

UNDIP's Jurnal Ilmu Sosial editorial policy allows authors to use AI tools supportively, but requires substantive AI use to be disclosed in an AI Declaration Statement and states that AI tools may not be listed as authors or co-authors.

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

UNDIP Library guidance tells students that submitted assignments remain their own responsibility, and that using AI software without acknowledgement is treated seriously under academic misconduct procedures.

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

UNDIP Library guidance says AI use in data analysis, writing, or draft preparation should be explicitly disclosed in publications, and AI-generated results should be manually reverified.

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

The University of Tübingen presents its generative-AI guideline for teaching and research as representing the university's stance, focused on critical-reflective, transparent, and responsible handling of generative AI.

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

The University of Tübingen guideline says that when generative AI is used in research, study, administration, or science communication, the procedure should be documented and made transparently visible in the relevant format.

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

The University of Tübingen download area says its model declaration must be adapted before distribution to students, with the faculty, department, or teacher choosing either a no-generative-AI-use option or a marking-duty option when AI use is allowed.

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

ECU's academic-misconduct guidance states that plagiarism includes unacknowledged use of a generative artificial intelligence tool such as ChatGPT.

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

ECU Library guidance says students who use generative AI as a study or research tool must acknowledge that use in their assessment, and that not giving credit to GenAI tools counts as plagiarism.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

ECU provides student-facing generative-AI learning support that covers responsible use, learning, academic integrity, prompt strategies, attribution, drop-ins, and workshops.

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

Effat University's library AI guide says using generative-AI text without proper citation is considered plagiarism according to Effat University, while policies for using and crediting AI tools may vary by class.

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

Effat University's library AI guide warns that generative-AI tools can produce inaccurate or false citations and advises users to verify citations for accuracy and credit the underlying source rather than the AI tool when citing sourced information.

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

Effat University's library AI guide advises users who decide to use ChatGPT or other AI technology for writing to be transparent with teachers and publishers and comply with applicable policies.

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

EPFL requires students to disclose the use of AI tools in assessment work. EPFL rules (Lex 1.3.3, Article 4) require that all assessment material that is not the student's personal and original contribution must be recognizable as such.

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

EPFL recommends that teachers make explicit to students what AI use is not legitimate in a course and what rules accompany AI tool use.

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.

Ewha's class-stage AI-use guidance says course guidance may state that copying generative-AI outputs directly into assignments or exams, fabricating or spreading false information with generative AI, infringing copyright with generative AI, or otherwise harming academic truthfulness and trust may be considered misconduct.

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

Ewha's class-stage AI-use guidance cautions that AI-detection programs can be used to check whether assignments used generative AI, but that such tools are not yet perfect and ethical use should be discussed with students.

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

Ewha's class-stage AI-use guidance presents course-level generative-AI use as something instructors may define by explaining whether and how AI use is allowed and by asking students to disclose how they used generative AI in assignments.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

FIU's Center for the Advancement of Teaching advises instructors to clearly define acceptable AI use in course expectations and syllabus policy, including which tools are permitted and how they may or may not be used.

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

An official FIU Syllabi sample AI-use PDF includes sample academic integrity language stating that AI-generated content without proper attribution or authorization is another form of plagiarism.

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

FIU Libraries' AI guide tells students who want to use AI in a course to ask their professor for that professor's individual AI-use policy.

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

GJU's AI principles permit AI tools for research support such as data analysis and research model development, require researchers to disclose AI tool use, and prohibit using AI tools to produce complete research papers, fabricate data, generate non-original literature reviews, or create content not based on genuine research effort.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

GJU's AI principles permit students to use AI tools for learning-supportive activities such as preliminary research, analysis, idea generation, writing improvement, and summarizing academic sources, provided that the use is disclosed; the principles prohibit using AI to fully prepare projects or theses without the student's actual contribution.

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

GJU's AI principles require disclosure of AI tool use in academic and research tasks and say sensitive data should not be entered into AI tools without consent from the relevant authorities and individuals concerned.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

For assignments completed at home from academic year 2024-2025, Ghent University student guidance permits responsible use of generative AI tools and says individual teachers can still prohibit use for a specific subject.

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

Ghent University teaching guidance says responsible GenAI use is always permitted unless a lecturer explicitly prohibits it for parts of an assignment that take place in a controlled environment, and it cautions that detection tools are unreliable.

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

Ghent University research guidance says members are expected to demonstrate research integrity, remain responsible for GenAI output, and be transparent about substantial GenAI use according to disciplinary standards.

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

Griffith's academic integrity page states that uncited content created using generative artificial intelligence software is conduct that always constitutes Academic Misconduct, and that representing AI-generated assessment content as a student's own work is Academic Misconduct.

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

Griffith's student generative AI guidance warns that many open or public tools do not guarantee confidentiality and advises users not to enter personal information, information about others, or course materials such as assessment tasks or marking rubrics.

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

Griffith's student-facing generative AI guidance says students may use generative AI for self-study without citation, but for assessment tasks they must acknowledge its use and include a short declaration if they use it while completing the task.

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

When generative AI is used to assist with grading submitted assignments, Hokkaido University's notes warn faculty not to enter students' personal or private information because entered data may be stored and output to other users.

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

For student use, Hokkaido University's notes say students preparing reports and other assignments should follow the instructor's guidance and instructions regarding generative AI use.

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

For faculty use, Hokkaido University's notes say instructors should explain in advance whether generative AI is permitted in class and how it is restricted, and should consider grading fairness when students use it in assignments or practical learning.

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

HKMU's student generative-AI guidelines say inappropriate AI use, including use without proper acknowledgment or in violation of course guidelines, will be treated as academic misconduct.

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

HKMU's student generative-AI guidelines require students completing assignments to submit an OLE declaration indicating whether generative-AI tools were used and, if used, which tool was used and how it contributed.

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

HKMU's AI@HKMU position statement frames ChatGPT and similar tools as supplements to coursework and says ChatGPT should not be relied upon solely to complete assignments.

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

HSE University requires students to disclose use of generative AI in written academic work, including the parts prepared with AI, the purpose and method of use, model name or source, and an effectiveness evaluation.

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

HSE University states that there is no university-wide prohibition on student use of AI, and students may use generative models in academic work when they follow disclosure requirements.

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

HSE University says an instructor may prohibit the use of generative models during assessment elements if the prohibition is stated in the course syllabus.

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

IE University's admissions integrity policy welcomes AI such as ChatGPT in the admissions process when candidates clearly identify AI-generated content, use quotation marks, and include sources and details.

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

A 2025-26 IE Humanities syllabus states that, for that course, ChatGPT or any other AI platform or tool is strictly prohibited for generating ideas or content, except spelling or grammar checking.

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

This crawl found official IE University AI-related sources for admissions, institutional AI positioning, and one course-level syllabus, but did not locate a public central enrolled-student generative-AI policy page in official-domain searches.

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

Illinois Tech's Academic Affairs guidance ties permitted use of generative AI or other outside resources to each course's learning objectives and syllabus expectations.

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

Illinois Tech's Center for Learning Innovation asks faculty to provide clear syllabus expectations for AI use and provides suggested syllabus language for no, some, and significant AI use.

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

Illinois Tech's suggested AI and assessment syllabus language says AI-assisted grading support should be explicitly stated in assignment instructions when such tools are used, with final grading oversight retained by the instructor.

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

Individual departments at Imperial may allow or prohibit the use of generative AI for specific assessments. Local (team/department/faculty) instructions take precedence over university-wide guidance. Students should check their department's current policy on using and disclosing generative AI in academic work and follow their module leader's instructions.

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

Students should include a statement acknowledging their use of generative AI tools for all assessed work, specifying the tool name and version, publisher, URL, a brief description of how it was used, and confirmation that the work is their own. Further requirements such as prompts used, date of output, the output obtained, and how it was modified may also be required by individual departments.

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

Users of Imperial's dAIsy platform must not upload third-party content they are not permitted to share. Reuse of AI outputs must comply with licensing and academic citation norms. When communicating externally, dAIsy outputs must not be presented as Imperial's position without approval.

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

For IIT Madras BS Degree program assignments, including any course or OPPE, the Honour Code says students are expected to produce original work based on individual understanding, and using LLMs such as ChatGPT or Gemini to generate any portion of code is considered plagiarism.

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

The IIT Madras BS Degree Honour Code applies to participation in the IIT Madras BS Degree program and says participants must agree to the Honour Code and any additional course- or program-specific terms posted on study.iitm.ac.in/ds.

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

For IIT Madras BS Degree Honour Code violations, the page says actions may include zero or no credit, withholding or revocation of a certificate or degree, unenrollment, termination of site use, additional action at IIT Madras' discretion, and no refunds.

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

Institut Polytechnique de Paris's 2025-2026 Master programs academic regulations prohibit the use of generative AI in assessments for those programs unless explicitly authorized by the instructor in written instructions. Unauthorized use constitutes academic misconduct.

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

Le règlement des études 2025-2026 des masters de l'Institut Polytechnique de Paris interdit l'utilisation de l'intelligence artificielle générative dans les évaluations de ces programmes, sauf autorisation explicite de l'enseignant dans ses consignes écrites. Tout manquement est considéré comme une fraude.

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

Under Institut Polytechnique de Paris's 2025-2026 Master programs academic regulations, when generative AI use is explicitly permitted by an instructor, students must clearly acknowledge its use in accordance with standard citation practices.

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

FITB guidance says declaration of AI use for coursework outputs is mandatory rather than optional, and undeclared AI use may be considered a serious violation with academic consequences.

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

FITB guidance states that, by default, using AI during exams, quizzes, or other evaluations is academic cheating and can be sanctioned unless the instructor allows or recommends AI use for a particular part of a course.

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

FITB guidance says instructors need to set AI-use policies for their courses and communicate them at the start of the course; when AI use is allowed, permission should be clear and explicit, with boundaries and transparency.

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

Iowa State research guidance warns that users cannot assume GenAI tools comply with HIPAA, FERPA, and similar confidentiality rules, and says uploading information to a public AI tool is equivalent to releasing it publicly.

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

Iowa State Student Conduct guidance says suspected AI-generated coursework referrals will be reviewed similarly to other forms of academic misconduct.

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

Iowa State CELT describes AI teaching resources for instructors, including GenAI syllabus considerations and a Canvas page on use of GenAI in Iowa State courses.

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

Istanbul University Press policy says authors should disclose details of any AI used in content creation in the appropriate part of the work.

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

An Istanbul University EBS syllabus for 'Yapay Zeka Araclari Kullanimi' states that the course aims to help students use AI tools consciously, ethically, and effectively.

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

An Istanbul University EBS syllabus for 'Sahne Sanatlarinda Yapay Zeka Uygulamalari II' includes generative AI, verification, bias, hallucination analysis, copyright, student data/privacy, institutional policy, and risk management as course content.

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

JGU library guidance says the university is generally open to AI tools, but instructors or institutes may decide whether tools are allowed for a given assessment, and allowed use should be disclosed as an aid.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

JGU library guidance warns AI-tool users to check legal and privacy conditions, avoid disclosing private or sensitive data, and consider server location, publisher restrictions, rights, and upload permissions.

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

JGU's digital teaching guidance encourages integrating AI literacy and transparent use of AI into teaching and, where appropriate, assessment design.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

Students may not submit content generated with generative AI as their own without disclosure, and using AI in exams, assignments, or academic assessments is treated as cheating unless the course instructor permits it.

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

Faculty members must state the course AI-use policy in the course description, including whether AI use is allowed for assignments, projects, and activities and how use should be disclosed.

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

King Saud University's 2025 Student Learning Assessment Policy supports use of generative AI tools in service of the educational process while emphasizing original submitted work, disclosure of AI use, and faculty authority to permit or prohibit generative AI use by assignment.

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

At King's College London, inappropriate use of generative AI without attribution is considered academic misconduct and can result in penalties ranging from formal warnings to expulsion.

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

King's College London does not require students to reference generative AI as an authoritative source in the reference list, but does require explicit acknowledgement of AI tool use in coursework.

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

King's College London permits doctoral students to use generative AI tools in their thesis writing processes for assistive purposes such as clarifying writing, provided use is declared and consistent with guidance.

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

Kingston University's 2025/26 Academic Integrity procedure defines unacceptable use of generative AI as presenting AI-generated content as one's own without proper acknowledgement, except when the assessment brief explicitly permits it.

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

Kingston University's AG2 guidance says that if generative AI is used as part of the editorial process, the student must acknowledge that use.

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

Kingston University's 2025/26 Academic Integrity procedure says contributions by artificial intelligence tools must be properly acknowledged.

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

Kyoto University tells students to follow the generative AI use policy set by the course instructor or research supervisor for coursework, reports, and thesis writing.

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

Kyoto University tells students to record and, when required, disclose how they used generative AI beyond wording revisions, and warns that using AI output in their own work may be judged misconduct.

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

Kyoto University expects instructors to state their generative AI use policy to students and, for courses focused on basic knowledge or skills, to preserve grading fairness through checks such as written or oral examinations.

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

La Trobe University policy says staff, students, contractors, honorary and adjunct staff must not disclose University information into publicly accessible or open-source AI systems.

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

La Trobe MyLaTrobe guidance says that when a subject allows AI use in an assessment, students need to submit an AI Acknowledgement, with the LMS indicating whether AI is permitted and what type of use is allowed.

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

La Trobe student guidance says AI rules may vary by school, subject, or task, and students should check with lecturers and acknowledge AI-generated content when they use it.

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

For the TDDC93/TDDC88/725G64 courses, the course policy says use of generative AI tools is permitted in 2025, while students remain responsible for submitted content.

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

Linköping University announced a strategic decision to implement an action plan for AI-ready education, including programme review, teacher skills development, AI ambassadors, and examination-design review for unauthorized AI use.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

An official Studieinfo syllabus page states that Linköping University has produced a guide for teachers and students on generative AI in education, and tells students that clarity about where and how generative AI has been used is important.

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

For education, Maastricht University says permitted GenAI uses are clearly defined at activity, course/module, study programme, and faculty levels.

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

For research output, Maastricht University says substantial GenAI use should be communicated transparently and referenced appropriately by researchers.

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

For operations, Maastricht University says GenAI tools are never used to process personal or organisation-sensitive data unless transparency and applicable safeguards are in place.

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

Mahidol University states that students must use Generative AI responsibly, avoid uses that may violate academic integrity, and clearly cite information or content derived from Generative AI.

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

Mahidol University's GenAI policy permits researchers to use Generative AI as a research tool, while requiring them to clearly identify the role of Generative AI in the research process and transparently report its use.

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

For Mahidol graduate-level thesis, thematic paper, and independent-study writing, the Faculty of Graduate Studies states that advisors may allow student AI use, but not for generating or drafting main content, analysis, research results, or main conclusions, and both advisor and student must disclose AI usage transparently.

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

When allowed or required to use AI in an assessment, students must follow all instructions and restrictions on its use, clearly document the type of AI used and how it contributed, and provide written acknowledgment of the use of AI and its extent.

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

Using AI in a way not permitted in an assessment, or failing to acknowledge its use correctly, may breach assessment conditions under the Student Academic Integrity Procedure.

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

Monash's AI responsible use principles include community benefit, education and research excellence, fairness, transparency, integrity and accountability, and data security and privacy.

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

Nanjing University undergraduate guidance prohibits using generative-AI tools to write key content in papers, assignments, reports, or works.

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

For listed allowed-use contexts, Nanjing University undergraduate guidance permits generative-AI tool use only after written signed or electronically signed consent from the course instructor or thesis/project supervisor.

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

For undergraduate thesis or project use of AI, Nanjing University guidance requires advance written application and a dedicated AI-use statement page when submitting the work.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

Nankai University's undergraduate AI tool norm permits students, with course teacher or supervisor consent and where core assessment or innovation is not affected, to use AI tools for literature search and management, grammar and formatting support with marked generated content, chart production from real data, and code assistance subject to author review and testing.

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

Nankai University's undergraduate AI tool norm says students should clearly explain and mark specific AI-generated content in coursework, graduation theses or designs, and lab reports, and should keep complete AI tool use records such as prompts, outputs, and selected use for checking.

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

Nankai University's undergraduate AI tool norm states that the university will provide an AIGC detection tool for teaching units to check AI tool use in coursework, graduation theses or designs, and lab reports, with results for teacher and supervisor reference; students who violate the norm may receive lower course or thesis grades, lose defense eligibility, or be handled under academic misconduct rules.

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

NTU states that the use of generative AI beyond basic spelling and grammar checks should be acknowledged and cited in research outputs, publications, and presentations.

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 requires students to disclose the use of AI tools in their submissions and to always refer to their module's AI use policy for specific expectations.

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

National Central University stated that, from academic year 112, courses would incorporate ChatGPT, including freshman English, calculus, the AI credit program, cultural technology course groups, and specialized courses across colleges.

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

National Central University stated that, to reduce plagiarism and academic-integrity issues from AI tool use, it would continue regulation and education on disclosure, citation, and use of AI tools in thesis or program writing.

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

National Central University's Computer Center announcement advised that generative AI use should avoid disclosing non-public official information or personal private information and should not completely trust generated information.

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

NSYSU's student generative AI guidance says students may not use generative AI tools for plagiarism or ghostwriting, cheating on exams, or privacy disclosure.

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

NSYSU's student guidance says students using generative AI tools should observe academic ethics and properly cite or explain the motivation, scope, sources, and AI-generated portions when teacher permission allows AI-assisted learning.

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

NSYSU's student academic integrity guidelines include cheating through unauthorized aids, tools, or electronic devices in coursework, assignments, or examinations when instructor consent has not been given.

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

Northeastern Policy 125 says faculty or staff seeking to use an AI system in University Operations or covered outside professional activities must provide required attribution, check AI outputs for accuracy and appropriateness, and validate anti-bias testing when the system processes personal information or affects legal rights or physical safety.

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

Northeastern teaching and learning standards say instructors should clearly communicate permitted generative AI uses to students in the syllabus, assignment guidelines, and verbally in class.

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

Northeastern's student AI guide advises students to check each syllabus, ask professors when an AI policy is unclear, use AI as a study partner rather than a substitute for their own thinking, and avoid using AI when assignment guidelines direct independent work.

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

Northwestern Polytechnical University reported that its graduate education digital transformation uses AI+ course construction and an AI+ knowledge graph course-learning model.

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

Northwestern Polytechnical University's Computer School reported a college-level teaching reform seminar on large models and agents, including plans to deepen AI-enabled teaching reform.

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

A reviewed official Northwestern Polytechnical University Higher Education Research Center page surfaced ChatGPT and academic-integrity content as research/practice material rather than a central university policy source.

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

Oxford Brookes student guidance states that students are required to declare which AI tools they used and how they used them in Moodle, then paste the emailed receipt into an appendix at the end of the assignment.

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

Oxford Brookes describes its university-wide position on generative AI in teaching, learning, and assessment as a progressive embrace-and-adapt approach, with module leaders having discretion to advise on AI use in module assessments.

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

Oxford Brookes guidance for schools, programmes, and modules says GenAI principles can be applied across disciplines and should be discussed at programme, course, and module level, with modules addressing equity and academic rigour and programmes advised to develop GenAI literacy and authentic assessment.

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

PUCV's academic-integrity policy states that use of AI tools such as ChatGPT without adequate citation is considered plagiarism.

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

PUCV teaching-development guidance says course syllabi and virtual classrooms should establish correct AI tool use in advance and specify which tools are authorized for the course.

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

PUCV teaching-development guidance says syllabi and virtual classrooms should establish norms, restrictions, and prohibitions for AI tools during assessment instances.

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

PMU's CCES Journal publication policies permit authors to use AI tools for research assistance, data analysis, language editing, and formatting, while requiring transparent disclosure and keeping authors responsible for the work.

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

PMU's CCES Journal publication policies state that AI systems or tools may not be listed as authors and that undisclosed or inappropriate AI use may lead to rejection or corrective action.

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

PMU's IT policy states that IT resources are primarily for university work and that PMU may monitor IT resource use and disclose necessary information for law, regulation, or government requests.

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

Purdue teaching guidance says instructors should determine and tell students when AI use is authorized or unauthorized; authorization is determined at the course level.

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

Purdue teaching guidance says instructors should include specific syllabus guidance on allowable AI-tool use, learning-process use, detection approaches, and potential consequences.

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

Purdue's AI toolkit lists GenAI Studio, Copilot Chat, Teams Premium, M365 Copilot, and Scite as Purdue University AI tools with access terms for users.

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

Queen's common course policies state that course outlines will include a statement indicating whether generative AI tools are permitted in a course and under what conditions.

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

Queen's CTL guidance says instructors should specify parameters for AI tool use in courses and advise on terms of use through a syllabus statement.

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

Queen's Library Generative AI guide says unauthorized use of generative AI tools is considered a departure from academic integrity.

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

Queen's assessment guidance says students who misuse AI will be subject to the University's academic misconduct regulations.

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

Queen's responsible AI research guidance expects material AI use in research to be clearly documented and acknowledged, with researchers validating AI-generated content.

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

Queen's Research Integrity AI page states the fundamental principle that users should not present AI responses as their own and should be clear, open, and transparent in AI use.

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

Rice Honor Council's AI policy page says using AI software to generate ideas and passing them off as one's own is plagiarism; it also says course-specific AI policies may supersede the Honor Council's general AI policy.

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

Rice University's Responsible AI student guidance says use of AI tools for coursework is allowed only when the instructor explicitly permits it, and students should check the syllabus or ask the professor before using AI on assignments.

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

Rice Office of the Provost guidance urges faculty to include a syllabus section stating their course stance on AI use and the extent of allowed use; it also notes Honor Council guidance that LLM use must be cited.

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

The English Seminar's AI guidelines require written coursework to use the seminar's declaration of authenticity, require GPT-created text passages to be marked, prohibit inserting whole GPT-created paragraphs, and state that unmarked use of GPT-generated text counts as an attempt to cheat.

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

The Geography Institute's AI guidelines say students may use AI-supported tools for topic development and language improvement, but AI-generated subject content, figures, and tables must be marked; otherwise this is treated as an attempt to cheat.

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

RUB's ZfW FAQ says generative AI tools can be used at RUB in research, teaching, and study, but that use can be restricted or tied to disclosure requirements in certain contexts such as written examinations.

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

Saarland University guidance says unauthorized use of generative AI in coursework or examinations, or failure to document it when required, is deception and may invalidate coursework or examinations and, in serious cases, lead to loss of examination entitlement.

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

Saarland University guidance says using generative AI as an aid for coursework and examinations is generally allowed, but instructors or examiners may restrict it to certain functions or prohibit it entirely.

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

Saarland University guidance says explicit documentation of generative AI use is generally not required beyond the declaration of independent work, but examiners may set transparent written documentation requirements in advance.

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

Sabancı University's student academic integrity handbook states that submitting text generated by text-generating AI applications such as ChatGPT in place of assignments students are supposed to write themselves violates the six principles of academic integrity.

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

Sabancı University's student academic integrity handbook says students can include text generated by applications such as ChatGPT in assignments if the instructor accepts it and the text is cited and referenced using the APA method for AI-generated text.

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

Sabancı University Information Center guidance says that if students use generative AI, they need to disclose which tool or tools they used and how they used them.

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

Sejong University's 2026 AI usage guideline tells students that if they use AI for learning or assignments, they must transparently disclose the fact of AI use, such as through footnotes, citations, or reference details.

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

Sejong University's 2026 AI usage guideline tells students not to enter sensitive personal information into AI systems and not to upload undisclosed research data or internal assignment materials because of leakage risk.

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

Sejong University's 2026 AI usage guideline says faculty and students should agree in advance on the principles and scope of AI use in classes or assessments, with course-specific rules communicated in the syllabus or first class.

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

SCUT Graduate School announced a trial AI general and practice online course for all 2025 graduate students, including part-time graduate students and international students.

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

SCUT's 2025 AI-enabled undergraduate teaching pilot call identified course agents, knowledge graphs, 24-hour intelligent learning companions, AI teaching assistants, intelligent grading, resource search, classroom assistants, preparation support, teaching management, digital humans, and internationalization as possible construction scenarios.

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

The SCUT undergraduate AI-enabled teaching pilot notice says the university would support pilot-course teams with AI technical guidance, teacher training and exchange activities, funding, production fees paid by the university, and priority teaching-assistant allocation during pilot delivery.

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

Southeast University's Graduate School opened 2026 school-level applications for AI-enabled graduate education projects in three categories: AI+ graduate courses, AI-enabled graduate teaching reform research projects, and AI-enabled graduate education application scenarios.

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

For AI+ graduate course project applications, the Graduate School notice says proposed course content must comply with national laws, policies, correct orientation requirements, confidentiality restrictions, and intellectual property requirements.

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

An official Southeast University repost reports that Vice President Jin Shi said the university built an AI-MUST curriculum system covering all majors and revised course syllabi to add AI literacy and technical-support objectives.

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

SUSTech's CS114 Introduction to Generative Artificial Intelligence course specification is course-level curriculum material that says the course covers generative AI history, principles, deployment, interdisciplinary applications, and ethical, security, and privacy discussions; it is not an institutional AI-use policy.

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

SUSTech's CS114 course calendar includes lessons on GAI privacy and security, GAI ethics, AI hallucination in large models, GAI-assisted programming, and AI agent engineering; this is course-level curriculum evidence rather than an institutional AI-use policy.

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

A 2026 SUSTech Library embedded AI-literacy teaching page reports that a library session for the Intelligent Ocean Exploration course introduced AI hallucination, algorithmic bias, AI academic writing norms, citation-labeling guidance, and AI academic application boundaries; this is course-session evidence rather than institutional policy.

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

Swansea University's AI assessment policy says staff and students are not permitted to present work completed by AI applications as their own without acknowledgement.

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

Swansea University's student AI guidance says AI-generated work submitted for assessment when not expressly authorised and declared could be investigated for academic misconduct.

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

Swansea University's student AI framework asks students to apply University policies on data protection, privacy, and academic integrity when selecting and using approved academic work, and to follow assessment instructions around permitted AI use and disclosure.

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

For suspected inappropriate generative AI use, Syracuse University's Academic Integrity Policy says an incident report cannot rely only on AI detection results and must explain course- and assignment-specific AI rules.

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

Syracuse University's Academic Integrity Policy says permitted AI use may vary by course or assignment, and treats inappropriate AI use as a failure to do one's own work.

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

Syracuse Academic Affairs tells instructors to choose one of three AI syllabus statements and says suspected AI academic-integrity cases will not be investigated unless the syllabus contains one of those statements.

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

TalTech tells lecturers to explain acceptable AI-based software use in assessment, teaching, learning, and homework, and course-level permission or prohibition should be specified in the extended syllabus.

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

TalTech says substantive AI output must be cited or described as a method, and learners remain responsible for accuracy, quality, analysis results, and references.

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

TalTech researcher guidance says AI-created texts and analyses should be clearly indicated and documented, and AI must not replace the researcher's critical thinking or act as a hidden author.

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

Tel Aviv University encourages responsible AI tool use, but AI use in a specific course is subject to the lecturers' sole discretion.

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

TAU guidance tells lecturers they can allow AI use without limits, allow it with defined limits, or prohibit it for a course or specific assignments.

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

TAU guidance says students may be instructed to attach an AI-use declaration and should check course instructions for whether and how AI use must be declared.

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

Texas A&M guidance says generative AI users must acknowledge nontrivial AI-generated content and avoid plagiarism, while faculty should provide clear course instructions about permissible AI uses.

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

Texas A&M presents AI Use Categories as a starting point for student-instructor conversation, not as a one-size-fits-all policy or replacement for instructor judgment.

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

Texas A&M CTE syllabus guidance recommends a hybrid approach that establishes clear course or assignment expectations for generative AI use, reinforces that AI use in coursework is governed by the Aggie Honor Code, and provides faculty support guidance.

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

AUC's AI statement says community members should clearly acknowledge AI tool use, and that claiming AI material as one's own is plagiarism and violates AUC academic integrity policies.

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

AUC's AI statement says a course instructor may authorize students to use AI tools in coursework, and in that case should provide written context and purpose for the allowed use.

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

AUC faculty AI resources advise faculty to clarify acceptable and unacceptable AI usage in their courses and discuss AI with students early and before major assessments.

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

LSE states that making generative AI tools available does not endorse unrestricted use, and users should check their specific course, programme, or department policy.

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

LSE requires departments or course convenors to classify authorised generative AI use in assessment as no authorised use, limited authorised use, or full authorised use, and to communicate the position to students.

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

For 2025/26, LSE requested departments to add assessment safeguards, including observed assessment methods, to help assure degree integrity and prevent unfair competitive advantage from generative AI.

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

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 advises faculty to test their own assignments with generative AI tools to understand how well AI can complete them, and use this understanding to inform assessment design.

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

UTokyo requires instructors to clearly state their AI stance per class/assignment, and when allowing AI use, to explain risks: information leakage, data concentration, copyright concerns, and potential bias.

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

For UWA coursework assessments, AI tools may only be used where the Unit Coordinator explicitly permits them; permitted use must be cited, referenced, and clearly acknowledged.

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

UWA askUWA guidance tells students to reference all AI-generated content used in assessments and says they may be asked to show the AI tools and prompts used.

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

UWA research-writing guidance states that AI and other machine-learning language models cannot be authors, and authors should transparently disclose when and how they used them.

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

In education, Science Tokyo's guideline says the university does not totally restrict learners' use of generative AI; the permitted degree of use, including whether it is banned, is left to course objectives, course content, and instructor teaching and assessment policies, and students should follow instructor instructions.

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

For courses, Science Tokyo's guideline asks instructors to teach students about generative AI limitations, consider assessment methods, and promptly reflect a course AI-use policy in the syllabus when the policy can be clearly stated.

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

For research papers, Science Tokyo's guideline says journal views on generative AI use differ and individual handling is needed, including cases where the fact of use should be disclosed; it also says researchers are responsible for text and content they use in their papers.

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

Trinity Library guidance says GenAI use as a functional tool in academic work must be acknowledged in an Appendix or Methods section, with minimum details including the system name and version, publisher, URL and context of use.

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

Trinity's research guidance says researchers remain responsible for scientific output, should cite GenAI usage in outputs, and should attend to privacy, confidentiality and intellectual-property issues when sharing sensitive information with AI tools.

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

Trinity College Dublin says specific uses of GenAI in an assessment must be disclosed, properly acknowledged, and referenced; students should explain what, when, and how they used GenAI.

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 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.

Tsinghua University advises instructors to determine how AI should be used according to course objectives, clearly explain AI usage norms to students at the start of each course, and remain responsible for AI-generated teaching materials.

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

The Universidad de Antioquia Political Science undergraduate program guidance states that AI tools must not be used to present automatically generated content as one's own, and that conventional citation systems should be used when referring to that content.

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

The Universidad de Antioquia Political Science undergraduate program guidance says AI use in academic products should be explicitly declared, with the declaration placed in the introduction, methodology section, or footnotes.

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

The Universidad de Antioquia Political Science undergraduate program guidance says students and teachers may use AI tools to support academic activities, but those tools should not be used to automatically generate the main writing of assignments.

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

The Faculty of Medicine guide proposes five principles for AI initiatives in that faculty: transparency and traceability, human supervision and non-delegation of critical judgment, equity and technological justice, academic integrity and responsible authorship, and participatory governance with continuous updating.

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

For health research publications, the Faculty of Medicine guide suggests declaring the type, timing and purpose of AI use, never attributing authorship to an AI tool, and validating AI-assisted production through human authors.

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

The FCFM guidance recommends that course teaching teams build a transparency policy with students around possible generative AI uses, including defining when and how the AI tool used should be cited.

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

The Faculty of Engineering guide says AI tool use should be transparent and recognized, including explaining permitted uses and how to declare tool use in submitted work.

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

The Faculty of Engineering guide says significant AI-contributed content should be declared, and presenting AI-generated content as one's own may be treated as a violation under the faculty's current regulations.

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

The Faculty of Engineering guide provides non-prescriptive categories for reduced, moderate, and extensive AI use in curricular units and assessments.

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

The Universidad de Sevilla Decálogo says AI users should be transparent about where and how they use AI, including details on the tool, prompt, and data provided.

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

The BUS ethical-use guide tells students to follow teaching-staff recommendations and evaluation limits for AI use, cite and declare AI use, avoid plagiarism, and verify AI-provided sources and biases.

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

The BUS AI-use declaration guide suggests adding an appendix after the bibliography that identifies the AI tool, purpose, prompts, integration, verification, and ethical limits.

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

For manuscripts submitted to the USFQ-hosted Iuris Dictio journal, generative AI use is permitted only as limited formal writing support and has to be explicitly declared.

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

USFQ’s “Inteligencia Artificial Generativa para Ciencias Sociales, Economía y Derecho” continuing-education program requires access to AI platform accounts, including premium OpenAI ChatGPT and Claude.ai subscriptions during the program.

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

USFQ’s March 2026 generative-AI content course includes a learning outcome on evaluating AI ethics challenges and applying good practices and ethical guidelines for responsible and transparent AI use.

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

The UnB-hosted Revista de Estudos e Pesquisas sobre as Americas allows generative AI for brainstorming and language improvement, but requires authors to clearly disclose any generative AI use with tool, version, use, and reason information in submission editor notes.

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

The UnB-hosted journal Sociedade e Estado says it does not currently use AI resources in publication evaluation and editing, and tells authors that any material or content generated by an AI application should be reported in the abstract and methods section or equivalent.

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

The UnB-hosted Anuario Antropologico author instructions state that the use and type of generative AI should be made explicit in submitted materials for evaluation when applicable, and recommend mentioning any AI-tool use in manuscript preparation.

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

Unicamp's generative AI deliberation says AI use in academic works, reports, articles, administrative documents, or any other intellectual production must be explicitly declared, and it assigns the user sole and full responsibility for AI-produced content.

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

Unicamp's generative AI deliberation allows students to use generative AI as support for information seeking, study, and learning, but says assessment activities must observe the limits and conditions defined by the course instructor when assessments exist.

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

The Unicamp Scientific Electronic Journals Portal AI-use policy says generative AI use in journal submission, assessment, and editing processes must be declared explicitly at manuscript submission and in the manuscript.

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

UniPG says every substantial use of GenAI must be declared and verifiable; for students, when AI use is allowed and substantial, it must be explicitly declared.

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

UniPG says students may use AI for a first draft or text reformulation if declared, but may not present an entirely AI-produced work as their own without personal contribution and adequate indication.

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

UniPG says teaching staff who use AI tools should make the mode and intensity of use explicit in the syllabus and communicate GenAI-use limits to students.

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

UB's good-practices document recommends that students clearly declare generative AI use when relevant and frames transparent, responsible AI use as a commitment to academic integrity.

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

UB's good-practices document says it is important for instructors to clarify at the beginning of each course what role generative AI may have, where it is permitted or not permitted, and under what conditions.

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

UB's teaching document recommends assessment designs that emphasize the process leading to an answer, set conditions under which AI-generated work may not pass, and use portfolios or reflective journals where students can declare which generative AI resources they used.

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

For teaching and examinations, Universität Innsbruck's FAQ says course leaders may decide which AI tools are permitted unless a faculty has its own rules, should communicate rules clearly, and should explicitly identify permitted aids including AI tools for examinations; unnamed aids are prohibited.

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

For research and scientific work, Universität Innsbruck's FAQ says good scientific practice applies to AI-tool use, AI use must be made transparent with tool name, scope, and purpose, and AI should not be cited as an author.

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

The Universität Innsbruck Faculty of Psychology and Sport Science guidelines say AI programs may be used in study work only as a supplement and support to learning, abusive AI use is a violation of good scientific practice, and generative AI use in written work must be described and cited.

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

Universität Mannheim assigns users responsibility for the correctness, legal permissibility, and dissemination of AI-generated content, says AI outputs should be checked and critically assessed before further use, and requires transparent disclosure where a notice obligation applies.

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

The University of Mannheim AI FAQ says AI systems may be used in teaching when the system is university-approved, or the use is voluntary with no disadvantage for non-use, or the use is in elective courses with sufficient non-AI alternatives; it expressly forbids contexts where students are disadvantaged for non-use without an equivalent alternative.

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

Universität Mannheim's Zentrum für Lehren und Lernen provides AI-in-teaching orientation, self-learning courses, workshops for teachers, students, and staff, and consultation for instructors, faculties, degree-program management, and departments developing AI strategies.

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

UPC library guidance tells students not to present AI-generated third-party content as their own, to ask instructors about each course’s AI rules, and to use AI as an assistant rather than as the author of academic work.

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

ESEIAAT allows generative AI use in final-study work writing only under stated conditions and requires a declaration section describing the tools, purpose, affected sections, student review, and responsibility statement.

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

ESEIAAT states that transparency about generative AI use is mandatory, but declaration alone does not make the use appropriate; assessment considers real authorship, critical thinking, and academic-level coherence.

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

Universite de Lorraine's 2025 exam charter states that use of tools, including generative artificial intelligence, is fraud when it is not explicitly authorized.

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

For the Master Urbanisme et Amenagement, parcours Intelligence Territoriale, the SHS Metz AI-use charter requires students to clearly indicate any AI use in submitted work and provide an AI-use declaration in an appendix.

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

Universite de Lorraine DACIP teaching guidance recommends favoring sovereign and secure generative AI, training on ethical issues, and transparency with students in pedagogical and assessment processes.

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

UdeM's teaching-integrity guidance says course plans should explicitly state when generative AI tools are permitted; without explicit authorization, the tools are deemed prohibited.

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

For UdeM graduate directed work, master's theses, doctoral essays, and dissertations, the graduate-studies guidance says generative AI use in research and writing must be transparent, and non-transparent use could be considered a disciplinary offence.

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

For administrative staff, UdeM Directive 10.70 says generative AI use should be disclosed, and use in a decision-making process should be disclosed to affected persons with consent obtained before use.

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

Université Laval guidance says AI-use expectations should be stated in the course plan and clarified in assessment instructions when AI use is authorized.

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

Université Laval guidance says using AI tools is not automatically an academic offence, but unauthorized use may constitute an academic offence under the student disciplinary regulation.

Evidence records: 2. Original evidence remains canonical on the linked university record and public JSON.

For Université Laval master's and doctoral theses, FESP says students making an initial deposit from winter 2026 must produce a declaration about their use of generative AI.

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

For student academic work, the charter directs students to systematically declare generative AI tool use, identify the tool and its contribution, and follow course-specific directives.

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

The official university site has a page on generative AI use that points readers to a good-use charter and a Moodle course on generative AI uses.

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

For teaching and assessment, the charter encourages teachers to integrate generative AI thoughtfully, adapt assessments, and clarify whether AI use is allowed, prohibited, or partly allowed for particular tasks.

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

Universiti Malaya's AI policy applies to academic staff and students across teaching and learning activities, including coursework, research projects, dissertations, final-year projects, theses, and online or blended learning activities.

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

Universiti Malaya guidance says lecturers specify the permitted level of AI use for each assignment or assessment, using levels from no AI use through integrated AI use.

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

Universiti Malaya guidance requires students to declare AI tools used in assignments or assessments and says failure to disclose AI use may be considered academic misconduct.

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

UMT announced that, beginning October 2025, its Basic AI Course would become a core university course for all students.

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

UMT's public training platform listed an academic AI-in-education course that guides lecturers on ethics and integrity considerations when addressing negative impacts of AI in education.

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

UMT's public training platform listed a ChatGPT student assessment course with learning outcomes covering question design, assessment creation, and using ChatGPT to generate questions and assessments.

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

For postgraduate theses, UPM's generative AI guideline requires students to clearly explain and appropriately attribute where and why generative AI was used, and to identify areas influenced by AI-generated content versus the student's direct contribution.

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

For UPM postgraduate viva sessions, the guideline says the chairperson must ensure that the student declares AI use in the research, specifies the areas assisted, and affirms that the originality and novelty of the research are the student's own work.

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

UPM's postgraduate thesis AI declaration form has students declare that AI technology used in thesis writing served as an assistive writing tool rather than a substitute for original thinking, analysis, or research, and that generated content was reviewed and modified.

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

Where a coursework item has no specified GenAI policy, UTB's guidance treats GenAI content generation as third-party assistance and says the assistance must be explained, declared, and referenced to avoid plagiarism.

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

For UTB module assessments, the GenAI guidance says the lecturer will specify the permitted level of GenAI usage for each coursework item.

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

The UTB coursework declaration in the Student Report Manual asks students to indicate whether they used GenAI and, for generated content, to include prompts and outputs as an appendix and cite the GenAI tool used.

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

UTM requires GAI use in assignments and works to be listed with developer information, tool name, version, access date, and URL when available; undisclosed use can be treated as plagiarism.

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

UTM requires academic staff to clearly state GAI use in course assessments, and prioritizes continuous assessments that demonstrate deep mastery.

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

UTM says GAI services beyond proofreading tools must be explicitly stated, and GAI tools cannot be listed as co-authors.

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

UB's Office of Academic Integrity states that UB has no universal policy about student use of artificial intelligence and that instructors have academic freedom to decide which tools students may use for course learning objectives.

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

Because UB has no universal AI policy for student use, the Office of Academic Integrity says instructors need to tell students what AI use is and is not allowed in the course or on each assessment, including in the syllabus.

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

UB CATT encourages faculty to add generative-AI statements to syllabi, avoid vague language, state specific parameters or limits, and distinguish permitted non-generative tools from generative AI tools.

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

Course Coordinators must provide students clear guidance on what GenAI tool use is permitted for work submitted for assessment.

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

Student guidance says learning materials and assessment information must not be entered into GenAI tools without explicit permission from the author, and students should never enter personal and sensitive data into GenAI tools.

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

When GenAI use is permitted for assessment, University guidance says students must acknowledge which tools they used, when they used them, and how they used generated content.

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

The University of Anbar Journal of Languages and Literature requires authors to explicitly disclose AI-tool use in the Acknowledgment or Methodology section, including the tool, version, and purpose.

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

The Anbar Journal of Agricultural Sciences prohibits AI use for generating scientific content without human verification, fabricating or manipulating data, obscuring authorship responsibility, or listing AI tools as co-authors.

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

The Anbar Journal of Agricultural Sciences requires manuscript AI-use disclosure at submission and bars reviewers from using AI tools to generate review reports while stating that editors must not rely on AI for editorial decisions.

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

University of Brighton PGR admissions guidance requires applicants who use AI to acknowledge how GenAI was used, and says applications may be withdrawn or studies terminated where false information or substantial GenAI fabrication is found.

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

University of Brighton guidance says the university has an institutional license for Microsoft Copilot chatbot, while noting that outputs still need to be verified and fact checked.

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

University of Brighton student guidance tells students to check whether GenAI is allowed before using it for an assignment.

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

Students may only use GenAI for assessed work (assignments, exams, projects, theses) if expressly permitted by their instructor, supervisor, or program.

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

Graduate students must obtain approval from their supervisor/committee for substantive GenAI use in research and thesis work, and must include a GenAI use statement in their thesis preface.

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

UBC says educators should tell students when and how to acknowledge GenAI use if GenAI tools are allowed in assessed work.

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

For graduate studies, the Faculty of Graduate Studies guidelines say students should obtain written, unambiguous authorization before planned GenAI use in graduate work, and students must disclose GenAI use in graduate study work.

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

University of Calgary teaching-and-learning guidance supports the use of generative AI in teaching and learning, while saying individual educators and instructors should decide if and how it is incorporated and clearly communicate student expectations.

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

For University of Calgary Continuing Education courses, student-facing guidance says GenAI tools should support work rather than replace student thinking and learning; students should check course outlines and instructor policies, and use of prohibited tools may constitute academic misconduct.

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

UC San Diego's Academic Integrity Policy says students may not let academic work or academic credit be completed for them by another human or by machine/artificial intelligence, and may not use unauthorized aids including artificial intelligence in coursework or assessments.

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

UC San Diego Academic Integrity Office guidance says students authorized to use a GenAI tool should use it only in the way authorized for that assignment, should not assume authorization extends to other assignments or courses, and are advised to save history and acknowledge use to the professor.

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

UC San Diego Library's GenAI academic-integrity guide says students might be cheating if they use a tool that has been prohibited or one that is not explicitly allowed by the course instructor.

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