Policy presence
University of Bristol has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Bristol, United Kingdom
University of Bristol
University of Bristol is listed as QS 2026 rank 51. University of Bristol has 4 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
University of Bristol is listed as QS 2026 rank 51. University of Bristol has 4 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
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
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Coursework
University of Bristol has 3 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of Bristol has 3 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
No source-backed public claim about privacy or data-entry restrictions is present in this profile.
The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.
Academic integrity
University of Bristol has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Approved tools
No source-backed public claim identifying approved or licensed AI tools is present in this profile.
The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.
Named AI services
University of Bristol has 1 source-backed public claim for named ai services; deterministic analysis status: blocked.
Teaching guidance
University of Bristol has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Bristol has 2 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
4 reviewed evidence-backed public claim
Research
PGR students at University of Bristol are not permitted to use generative AI tools such as ChatGPT to write any text used in their thesis or APM reports, as research degree students must demonstrate ability to write about research in their own words.
Review: Agent reviewed
Normalized value: PGR students prohibited from using generative AI to write thesis or APM report text
Original evidence
Evidence 1To be awarded a research degree, you must meet several key standards in your research training. One of these is the ability to write about your research in your own words. This critical research skill is tested through your thesis and through your annual progress monitoring (APM) reports. For this reason, you are not permitted to use generative AI tools, such as ChatGPT, to write any text that is used in your thesis or in your APM reports.
Localized display only
PGR students not permitted to use generative AI to write thesis or APM text
Academic Integrity
University of Bristol considers the use of AI or translation tools to be cheating if used for more than generating the occasional short phrase within a sentence or checking basic grammar and spelling, unless assessment instructions allow more comprehensive use.
Review: Agent reviewed
Normalized value: AI use beyond occasional phrases and grammar checking is considered cheating
Original evidence
Evidence 1We consider the use of AI or translation tools to be cheating if used for more than: generating the occasional short phrase within a sentence, checking basic grammar and spelling. Some assessments may allow more comprehensive use of these tools, but this will be detailed in your assessment instructions.
Localized display only
AI use beyond occasional phrases and grammar checking is cheating
Teaching
University of Bristol has published official guidance on generative AI use in taught degree programmes, stating that generative AI should not replace activities that develop intellectual rigour, student agency, and students' capacity to work through complex problems themselves.
Review: Agent reviewed
Normalized value: University has official generative AI guidance for taught programmes
Original evidence
Evidence 1This guidance sets out the University of Bristol's approach to using generative AI on taught degree programmes. The responsible use of generative AI is foundational to our educational vision to inspire students, and to equip well-rounded graduates with skills for the future. Generative AI should not replace activities that develop intellectual rigour, student agency, and students' capacity to work through complex problems themselves.
Localized display only
University guidance for generative AI on taught degree programmes
Teaching
University of Bristol uses a four-category system for AI use in assessments: Category 1 (prohibited - no AI use), Category 2 (minimal - spelling/grammar only, default), Category 3 (selective - certain tasks as specified), and Category 4 (integral - AI required for assessment).
Review: Agent reviewed
Normalized value: Four-category AI assessment system: prohibited, minimal, selective, integral
Original evidence
Evidence 1Category 1: prohibited (not allowed) - You cannot use AI tools at all, including spelling and grammar checkers. Category 2: minimal (a little) - You can use AI tools for spelling and grammar check. You can use it for rewording occasional phrases, but not sentences, large parts of text or paragraphs. Category 3: selective (certain tasks) - AI tools can be used in certain ways. Your lecturer will tell you what you can use it for. Category 4: integral (important) - AI tools are needed for the assessment.
Localized display only
Four AI assessment categories: prohibited, minimal, selective, integral
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
4 source attribution
Academic integrity | Current students | University of Bristol
bristol.ac.uk
Guidance for PGR students on the use of AI tools in thesis writing
bristol.ac.uk
Guidance on AI | Bristol Institute For Learning and Teaching
bristol.ac.uk
Using artificial intelligence (AI) in assessments and for studying
bristol.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.