Policy presence
University of Sussex has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Brighton, United Kingdom
University of Sussex
University of Sussex is listed as QS 2026 rank 278. University of Sussex has 6 source-backed AI policy claim records from 5 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 Sussex is listed as QS 2026 rank 278. University of Sussex has 6 source-backed AI policy claim records from 5 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 University of Sussex as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 5 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-sussex.json. The entity-level confidence is 94%. 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 Academic integrity claims.
- Evidence includes Privacy claims.
- Evidence includes Teaching 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
University of Sussex has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.
Coursework
University of Sussex has 4 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of Sussex has 5 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
University of Sussex has 1 source-backed public claim for privacy and data entry; deterministic analysis status: recommended.
Academic integrity
University of Sussex has 4 source-backed public claims for academic integrity; deterministic analysis status: restricted.
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 Sussex has 1 source-backed public claim for named ai services; deterministic analysis status: recommended.
Teaching guidance
University of Sussex has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
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
6 reviewed evidence-backed public claim
Academic Integrity
University of Sussex staff guidance says module convenors determine and communicate AI-use permissions via module Canvas sites and choose one of three assessment-level permissions: AI use prohibited, AI in an assistive role, or AI with an integral role.
Review: Agent reviewed
Normalized value: module_convenors_set_three_ai_permission_levels
Original evidence
Evidence 1It is up to module convenors to determine and communicate AI use permissions via module Canvas sites. For each assessment, choose one of three permitted levels of AI use: AI use is prohibited; AI can be used in an assistive role; AI has an integral role.
Academic Integrity
University of Sussex student misconduct guidance includes unauthorized or inappropriate use of digital technologies including AI, and gives examples including AI use where prohibited and submitting permitted AI-generated work without required acknowledgement.
Review: Agent reviewed
Normalized value: ai_misuse_can_be_academic_misconduct
Original evidence
Evidence 1Misuse of digital technologies includes artificial intelligence. Examples include: using AI or other digital tools, such as translation tools in an assessment where their use has been prohibited; submitting AI-generated work, where this is permitted, without required acknowledgment.
Academic Integrity
University of Sussex staff guidance provides a prohibited-use assessment statement saying generative AI tools must not be used to generate materials or content for that assessment, while allowing other assistive technology for registered reasonable adjustments.
Review: Agent reviewed
Normalized value: prohibited_assessment_statement_no_generative_ai_content
Original evidence
Evidence 1Generative AI tools must not be used to generate any materials or content for this assessment. The purpose and format of this assessment makes it inappropriate or impractical for AI tools to be used. Students registered with the Disability Advice team and in receipt of reasonable adjustments are still permitted to use other assistive technology as required.
Privacy
University of Sussex staff guidance says staff and students can access a data-protected Microsoft Copilot with Sussex credentials, and says university data such as learning and teaching content should be used in Copilot rather than less protected AI tools.
Review: Agent reviewed
Normalized value: sussex_copilot_preferred_for_university_data
Original evidence
Evidence 1Being logged into Copilot with your Sussex account means that your data is protected. Your chat results won't saved or made available to Microsoft, meaning any data isn't passed outside of the organisation. This is in contrast to both the free version of Copilot and other AI tools which may not be protecting your data. If you are using university data in an AI tool, such as learning and teaching content, then ensure you use Copilot.
Teaching
University of Sussex AI principles say decisions on whether AI use is permitted, not permitted, optional, or required in learning or assessment will be made explicit.
Review: Agent reviewed
Normalized value: ai_assessment_permissions_will_be_explicit
Original evidence
Evidence 1Whether AI use is permitted/not permitted, optional or required in learning or assessment will be made explicit.
Academic Integrity
University of Sussex staff guidance suggests telling students that AI detection tools are fallible and cannot be relied upon.
Review: Agent reviewed
Normalized value: ai_detection_tools_fallible_guidance_for_student_discussion
Original evidence
Evidence 1Acknowledge that AI detection tools already exist, many much more sophisticated ones are in development and, predictably, a web-based sub-culture of ways to fool the detection systems is also growing. Explain that all are fallible and cannot be relied upon.
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
5 source attribution
Academic misconduct
student.sussex.ac.uk
AI and academic integrity
staff.sussex.ac.uk
AI tools
staff.sussex.ac.uk
Artificial Intelligence (AI) in education
sussex.ac.uk
Talking with students about AI
staff.sussex.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.