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Citations and Disclosure Statements - Generative AI - LibGuides at University of Tulsa

Anbar Journal of Agricultural Sciences - Artificial Intelligence (AI) Usage and Disclosure Policy

Journal of Zhejiang University - Policy Statement and Author Disclosure Requirements for the Use of Generative AI

At the University of Chicago, entering sensitive data into AI tools without review and approval by security, privacy, and the appropriate data steward may create an unauthorized data disclosure that may violate University policy, federal and state law, sponsor or contract obligations, and data use agreements.

Use of generative AI tools at MIT must comply with all applicable federal and state laws and orders (including FERPA, HIPAA, Massachusetts Data Protection Standards, export control laws, and the Executive Order on Safe, Secure, and Trustworthy Development and Use of AI), Institute policies (including 10.1 Academic and Research Misconduct, 11.0 Privacy and Disclosure of Personal Information, and 13.0 Information Policies), Information Protection guidelines, and the Institute's Written Information Security Program (WISP), plus any additional policies established by the user's department, lab, center, or institute (DLCI).

The ANU Library LibGuide references the ARC policy requiring disclosure of generative AI use in grant applications, accuracy verification, and originality compliance.

KU researcher guidance says researchers should comply with sponsor, publisher, institutional, and disciplinary rules when using GenAI and should consider confidentiality, privacy, intellectual property, and disclosure requirements.

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.

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

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.

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.

U-M requires AI use in teaching and learning to align with principles of honesty, candor, openness, and integrity in scholarship and research, including appropriate disclosure and citation.

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.

University-approved enterprise AI tools (Microsoft Copilot Chat for all, M365 Copilot via licences) must be used whenever there is a risk of inappropriate disclosure. Free-to-use public AI services should only be used with extreme caution due to data disclosure risks.

University of Munster central guidance says it orients itself to the DFG statement on generative models for text and image creation in research, including disclosure of whether, which, why, and how extensively generative models were used when results are made publicly accessible.

Westminster doctoral researcher guidance says doctoral assessments and research outputs must be the researcher's own original work, and that using GenAI to generate doctoral research content without agreement and disclosure is academic misconduct.

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.

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.

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.

NSYSU's student generative AI guidance says students may not use generative AI tools for plagiarism or ghostwriting, cheating on exams, or privacy disclosure.

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.

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.

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.

UNC-Chapel Hill's research guidance treats entering private or confidential information, research data, grant proposals, or analytical results into public generative AI tools as a public disclosure of that information.

For the University of Zurich Faculty of Arts and Social Sciences, teaching staff determine for each module the extent to which AI is permitted for assessments; use of tools or generative AI without explicit consent and disclosure is punished as academic misconduct.

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.

Tufts' generative AI usage guidelines state that community members must be transparent about AI use and that instructors and units are strongly encouraged to clarify permitted AI use and disclosure expectations.

UNE's HDR generative AI guidance warns that failure to reference generative AI content may be considered academic or research misconduct, and lists risks including unacknowledged AI output, inaccurate AI-generated references, substantive AI-generated thesis or publication content, peer review or ethics-clearance use, and disclosure of sensitive or confidential material to generative AI.

University of Pretoria Library guidance states that submitting AI-generated content as one's own work without explicit lecturer permission and proper disclosure constitutes academic misconduct under UP's Academic Integrity Policy.

The Fasilkom UI ethics committee legal-basis page summarizes GenAI-based research expectations as including open disclosure of GenAI and new technologies in research methodology and providing access for KEP or a supervisory body to review the use process.