Policy presence
Queen's University Belfast has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Belfast, United Kingdom
Queen's University Belfast
Queen's University Belfast is listed as QS 2026 rank =199. Queen's University Belfast has 12 source-backed AI policy claim records from 8 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Queen's University Belfast is listed as QS 2026 rank =199. Queen's University Belfast has 12 source-backed AI policy claim records from 8 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Queen's University Belfast as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 12 source-backed claims, including 12 reviewed claims, from 8 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/queens-university-belfast.json. The entity-level confidence is 92%. 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.
Policy signals in this record
- Evidence includes Research claims.
- Evidence includes Academic integrity claims.
- Evidence includes Teaching claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Privacy claims.
- Named AI services detected in public claims: Microsoft Copilot.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
- Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Review: Agent reviewed
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.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
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.
AI disclosure
Queen's University Belfast has 2 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
Queen's University Belfast has 5 source-backed public claims for coursework; deterministic analysis status: blocked.
Exams
Queen's University Belfast has 5 source-backed public claims for exams; deterministic analysis status: blocked.
Privacy and data entry
Queen's University Belfast has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Queen's University Belfast has 2 source-backed public claims for academic integrity; deterministic analysis status: recommended.
Approved tools
Queen's University Belfast has 2 source-backed public claims for approved tools; deterministic analysis status: blocked.
Named AI services
Queen's University Belfast has 4 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Queen's University Belfast has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
Queen's University Belfast has 4 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
No source-backed public claim about AI security review or procurement is present in this profile.
The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
12 reviewed evidence-backed public claim
Research
Queen's responsible AI research guidance applies to staff, postgraduate research students, visiting researchers, and contractors conducting research under the auspices of the University.
Review: Agent reviewed
Normalized value: research AI guidance scope
Original evidence
Evidence 1This guidance applies to: All Queen’s researchers (staff, postgraduate research students, visiting researchers, and contractors) conducting research under the auspices of the University. All types of research activities across the research lifecycle including planning, funding proposal development, data collection and analysis, publication and dissemination, peer review and evaluation, and research management.
Localized display only
The research guidance applies to Queen’s researchers across the research lifecycle.
Academic Integrity
Queen's assessment guidance says module staff will clarify if and how AI can be used in assessment, and students should consult their tutor if in doubt.
Review: Agent reviewed
Normalized value: module-level clarification for AI use in assessment
Original evidence
Evidence 1This academic year, those delivering modules will clarify if and how AI can be used when completing assessment. If students have any doubt about how AI can be used, they should consult with their tutor.
Localized display only
Module staff clarify if and how AI may be used; students should ask tutors if unsure.
Teaching
Queen's AI position page says its staff and student AI guidance is based on RAISE principles: responsible use, AI best practice, integrity, support, and equitable access.
Review: Agent reviewed
Normalized value: RAISE principles frame staff and student AI guidance
Original evidence
Evidence 1This section brings together tailored QUB guidance for staff and students. This includes recommendations on how to get started as well as more specific guidance on the use of AI, for example within assessment. Our guidance is based on the following principles: R esponsible use, A I best practice, I ntegrity, S upport and E quitable Access – collectively RAISE.
Localized display only
QUB describes its staff and student AI guidance as based on Responsible use, AI best practice, Integrity, Support and Equitable Access.
Academic Integrity
Queen's assessment guidance says students who misuse AI will be subject to the University's academic misconduct regulations.
Review: Agent reviewed
Normalized value: AI misuse subject to academic misconduct regulations
Original evidence
Evidence 1Students need to be fully aware of when and how they can use AI in assessments, including any limitations on certain tools or the need to cite or document how AI has been used. If students misuse AI, they will be subject to the University's academic misconduct regulations .
Localized display only
AI misuse in assessment is linked to the University’s academic misconduct regulations.
Research
Queen's responsible AI research guidance expects material AI use in research to be clearly documented and acknowledged, with researchers validating AI-generated content.
Review: Agent reviewed
Normalized value: document acknowledge and validate material AI use in research
Original evidence
Evidence 1All use of AI in research must be clearly documented and acknowledged, especially where it constitutes material use in the research process/output. Researchers are expected to validate AI-generated content and uphold the standards of academic honesty, avoiding misrepresentation or plagiarism.
Localized display only
Material research AI use should be documented and acknowledged, and AI-generated content validated.
Ai Tool Treatment
Queen's assessment guidance says text-based AI detectors are not recommended because current tools cannot definitively identify AI-authored content and can produce false positives.
Review: Agent reviewed
Normalized value: text-based AI detectors not recommended
Original evidence
Evidence 1Current tools that attempt to detect AI generated text – whether by analysing writing styles, using machine learning classification, or watermarking – cannot definitively identify AI-authored content. Worryingly, these systems often produce an unacceptably high rate of false positives. In the future, with the integration of AI writing tools into platforms like Microsoft Word and Google Workplace, it is anticipated that much of our writing will include AI-generated elements. This will be similar to how we currently benefit from algorithm-driven spell checkers and grammar tools. Considering these factors, the use of text-based AI detectors is not recommended.
Localized display only
The assessment page says current AI text detectors cannot definitively identify AI-authored content and are not recommended.
Research
Queen's research AI guidance says AI use in projects involving human participants, personal data, or sensitive information must be outlined in ethics applications.
Review: Agent reviewed
Normalized value: AI use involving participants or sensitive data in ethics applications
Original evidence
Evidence 1Researchers using AI in projects involving human participants, personal data, or sensitive information must explicitly outline AI usage in their ethics applications. Ethics applications must include clear details about how AI will be used in data collection, analysis, or management, and how participants’ data privacy will be protected.
Localized display only
AI use with human participants, personal data, or sensitive information must be outlined in ethics applications.
Ai Tool Treatment
Queen's tools guidance identifies Microsoft Copilot Chat as available for Queen's University faculty and staff using a @qub.ac.uk email login.
Review: Agent reviewed
Normalized value: Copilot Chat available to faculty and staff with QUB login
Original evidence
Evidence 1Microsoft Copilot Chat is available for use by Queens University Faculty and staff. To use Copilot, please log in using your @qub.ac.uk email address. Copilot Chat is supported officially on Microsoft Edge and Chrome (using the latest Stable Channel update).
Localized display only
Microsoft Copilot Chat is available for Queen’s faculty and staff with a @qub.ac.uk login.
Privacy
Queen's responsible-use guidance tells users to make an ethical judgment about the information submitted to AI tools and whether they have permission to submit it.
Review: Agent reviewed
Normalized value: ethical judgment and permission before submitting data to AI tools
Original evidence
Evidence 1When using an AI tool, it is necessary to make an ethical judgment about the data or information that you put into the system when you use it to complete a task. Any information that is submitted to an AI tool then becomes part of the data that the tool draws upon to complete future tasks for anyone who uses the tool. You need to consider whether you have permission to submit the information that you do.
Localized display only
Users are told to judge whether they have permission before submitting information to AI tools.
Research
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.
Review: Agent reviewed
Normalized value: do not present AI responses as own in research
Original evidence
Evidence 1Whilst work is ongoing within the University to develop guidance on its use, the fundamental principle is NOT to present any responses from AI as if they were your own, be clear, open and transparent in your use.
Localized display only
The Research Integrity page says not to present AI responses as your own and to be clear, open, and transparent.
Privacy
Queen's tools guidance says the AI tools listed on the page are for exploration and exclusively with publicly available data.
Review: Agent reviewed
Normalized value: listed AI tools for exploration with publicly available data only
Original evidence
Evidence 1Users are advised to use Artificial Intelligence tools responsibly. It is important to emphasise that the AI tools featured on these pages are intended solely for exploration, and exclusively with publicly available data.
Localized display only
The tools page limits listed AI tools to exploration with publicly available data.
Teaching
Queen's student AI support page provides student-facing resources including guidance on generative AI in studies, academic success, citing AI, acceptable use, and AI confidence.
Review: Agent reviewed
Normalized value: student AI support resources available
Original evidence
Evidence 1These dedicated resources include an AI Glossary for understanding foundational AI concepts, a guide titled, ‘How to use AI for Academic Success’, and a guide on ‘How to U se Generative AI in your studies at Queen’s’. More resources will be added over time, so stay tuned for future updates. AI Glossary How to use Generative AI in your studies How to use AI for Academic Success Top AI Tools for Students AI Myth Busting AI and Creativity AI and Accessibility Acceptable and Unacceptable AI Use at QUB Sustainable AI Use: Top Tips for Students
Localized display only
The student support page lists guides for AI academic success, generative AI in studies, citing AI, and the Student RAISE guide.
Candidate claims
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.
Official sources
8 source attribution
AI in Assessment and Feedback: Opportunities and Challenges - Queen's DigiHub
blogs.qub.ac.uk
AI Support for Students - Queen's DigiHub
blogs.qub.ac.uk
Artificial Intelligence | Research | Queen's University Belfast
qub.ac.uk
Artificial Intelligence Hub - Queen's DigiHub
blogs.qub.ac.uk
Queen’s Guidance on the Responsible Use of AI in Research - Queen's DigiHub
blogs.qub.ac.uk
Responsible Use of AI in Education: Ensuring Ethical AI - Queen's DigiHub
blogs.qub.ac.uk
Understanding QUB's Position on AI - RAISE Principles - Queen's DigiHub
blogs.qub.ac.uk
Using AI in Education: Tools and Systems at QUB - Queen's DigiHub
blogs.qub.ac.uk
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.