Policy presence
The University of Manchester has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Manchester, United Kingdom
The University of Manchester has 12 source-backed AI policy claims from 6 official source attributions. Review state: agent reviewed; 12 reviewed claims. Last checked May 10, 2026.
v1 public contract
The University of Manchester has 12 source-backed AI policy claims from 6 official source attributions, including 12 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 10, 2026. Discovery context: The University of Manchester is listed as QS 2026 rank 35.
As of this public record, University AI Policy Tracker lists The University of Manchester as an agent-reviewed AI policy record last checked on May 10, 2026 and last changed on May 10, 2026. The record contains 12 source-backed claims, including 12 reviewed claims, from 6 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/manchester.json. The entity-level confidence is 98%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Deterministic source-backed dimensions derived from this record's public claims.
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
The University of Manchester has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
The University of Manchester has 3 source-backed public claims for ai disclosure; deterministic analysis status: required.
The University of Manchester has 5 source-backed public claims for coursework; deterministic analysis status: blocked.
The University of Manchester has 5 source-backed public claims for exams; deterministic analysis status: blocked.
The University of Manchester has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
The University of Manchester has 4 source-backed public claims for academic integrity; deterministic analysis status: blocked.
The University of Manchester has 5 source-backed public claims for approved tools; deterministic analysis status: restricted.
The University of Manchester has 5 source-backed public claims for named ai services; deterministic analysis status: restricted.
The University of Manchester has 4 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
The University of Manchester has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.
The University of Manchester has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
12 reviewed evidence-backed public claim
Ai Tool Treatment
Evidence originale
Evidence 1The University position is that, when used appropriately, AI tools have the potential to enhance teaching and learning and can support inclusivity and accessibility. Output from AI systems must be treated in the same manner by staff and students as work created by another person or persons, used critically and with permitted license, and cited and acknowledged appropriately.
Teaching
Evidence originale
Evidence 1The University has adopted the following principles, building on existing frameworks for academic integrity and emerging guidance on AI. All staff and students using or developing AI are personally responsible for adhering to these.
Ai Tool Treatment
Evidence originale
Evidence 1The University has announced a strategic collaboration with Microsoft, making Manchester the world's first university to deploy equitable Microsoft 365 Copilot access and training across its entire community. This means 65,000 colleagues and students will benefit from the full Microsoft 365 Copilot suite.
Privacy
Evidence originale
Evidence 1Copilot Chat is an AI-powered assistant available to everyone with a University account... Your prompts and uploaded files are private – no one else can see them and they are protected by the same security and encryption techniques as your emails and the contents of your OneDrive or SharePoint Sites. Copilot Chat's AI system does not learn from your prompts or data.
Academic Integrity
Evidence originale
Evidence 1Submitting work created by Generative AI as their own, or to misrepresent their understanding of the subject, is plagiarism and will be dealt with in accordance with the University's Academic Malpractice Procedure.
Academic Integrity
Evidence originale
Evidence 1Tools to detect AI-generated content are unreliable and biased and cannot be relied on to identify academic malpractice in summative assessment. Output from such tools cannot currently be used as evidence of malpractice.
Academic Integrity
Evidence originale
Evidence 1You must cite or acknowledge the outputs of generative A.I. tools when you use them in your work. Quotating, summarising and paraphrasing, editing, translating, data processing, re-writing your work and the generation of ideas.
Ai Tool Treatment
Evidence originale
Evidence 1Many generative AI tools are available as either free-to-use public services or paid-for enterprise services. Free-to-use public services often store user input, potentially disclosing the content to third parties. They should only be used with extreme caution... University-approved enterprise AI tools must be used whenever there is a risk of inappropriate disclosure.
Teaching
Evidence originale
Evidence 1With approval at School level, this position may be broadened or narrowed for specific Course Units or assignments to encourage, require, or disallow specific uses of AI. In such cases students must be given detailed information that explains the rationale for the variation from the default position, as well as what is and is not allowed.
Teaching
Evidence originale
Evidence 1Using an AI tool to correct grammar or spelling is acceptable, but where a student uses an AI tool for proofreading work submitted for assessment, they should ensure that use of the tool does not result in substantive changes to the content or meaning of their work.
Research
Evidence originale
Evidence 1The University recognises the potential of AI to power research and innovation... Any use of AI to generate data should be completely transparent... Using AI to fabricate or manipulate data such as experimental measurements, interview texts or research images, without clear declaration, constitutes research misconduct.
Ai Tool Treatment
Evidence originale
Evidence 1Microsoft Copilot: The University recommends using Microsoft Copilot for AI-related work. It is GDPR-compliant and protects University and personal data. Even though Copilot is GDPR compliant, you should ALWAYS carefully consider whether adding personal information into an AI tool is necessary.
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
6 source attribution
elearning.bmh.manchester.ac.uk
staffnet.manchester.ac.uk
teachingcollege.fse.manchester.ac.uk
itservices.manchester.ac.uk
staffnet.manchester.ac.uk
subjects.library.manchester.ac.uk
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