London, United Kingdom

Royal Holloway, University of London

Royal Holloway, University of London has 7 source-backed AI policy claims from 8 official source attributions. Review state: agent reviewed; 7 reviewed claims. Last checked May 16, 2026.

Royal Holloway, University of London AI policy short answer

v1 public contract

Royal Holloway, University of London has 7 source-backed AI policy claims from 8 official source attributions, including 7 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 16, 2026. Discovery context: Royal Holloway, University of London is listed as QS 2026 rank =461.

Citation-ready summary

As of this public record, University AI Policy Tracker lists Royal Holloway, University of London as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 7 source-backed claims, including 7 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/royal-holloway-university-of-london.json. The entity-level confidence is 96%. 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.

Claim coverage7 reviewedSource languageenPublic JSON/api/public/v1/universities/royal-holloway-university-of-london.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes Research claims.
  • Evidence includes Privacy claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Source status 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.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims7Reviewed7Candidate0Official sources8

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.

Coverage score100/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence78%

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.

Teaching guidance

Royal Holloway, University of London has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence66%Evidence1Sources1

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

7 reviewed evidence-backed public claim

Academic Integrity

Royal Holloway academic misconduct regulations list requesting or engaging an artificial intelligence tool to write or rewrite work for unfair advantage, and presenting AI-generated content as one’s own unless authorised and acknowledged, as examples of assessment offences.

Review: Agent reviewedConfidence96%

Normalized value: ai_commissioning_and_unauthorised_ai_in_regulations

Bukti asal

Evidence 1
Commissioning, which is requesting or engaging another person or artificial intelligence tool whether paid or unpaid to write or rewrite work in order to obtain an unfair advantage for oneself. Presenting content generated by artificial intelligence tools as your own unless specifically authorised in writing as part of the assessment brief and appropriately acknowledged.

Paparan setempat only

Commissioning, which is requesting or engaging another person or artificial intelligence tool whether paid or unpaid to write or rewrite work in order to obtain an unfair advantage for oneself. Presenting content generated by artificial intelligence tools as your own unless specifically authorised in writing as part of the assessment brief and appropriately acknowledged.

Research

Royal Holloway Doctoral School guidance for postgraduate researchers says AI may not author or generate research claims, thesis prose, or other academic content, and that researchers are responsible for every output they submit.

Review: Agent reviewedConfidence95%

Normalized value: pgr_ai_may_not_author_research_claims_or_thesis_prose

Bukti asal

Evidence 1
Originality: AI may not author or generate research claims, thesis prose or other academic content. Transparency: declare that any AI use is within the permitted guidance outlined in this document. Accountability: you, the student, are responsible for every output that you submit.

Paparan setempat only

Originality: AI may not author or generate research claims, thesis prose or other academic content. Transparency: declare that any AI use is within the permitted guidance outlined in this document. Accountability: you, the student, are responsible for every output that you submit.

Academic Integrity

Royal Holloway requires students to include declaration statements for generative AI use or non-use, and says a list of all prompts entered into any large language model must be provided.

Review: Agent reviewedConfidence94%

Normalized value: ai_declaration_and_prompt_list_required

Bukti asal

Evidence 1
Explicit acknowledgment of use of generative AI tools such as Large Language Models like Microsoft Copilot, Google Gemini or ChatGPT or any other media generated through similar tools is required. If you have not used any such tools in any way a declaration statement is still required. Prompt List: A list of all prompts entered into any large language model must be provided.

Paparan setempat only

Explicit acknowledgment of use of generative AI tools such as Large Language Models like Microsoft Copilot, Google Gemini or ChatGPT or any other media generated through similar tools is required. If you have not used any such tools in any way a declaration statement is still required. Prompt List: A list of all prompts entered into any large language model must be provided.

Privacy

Royal Holloway Doctoral School guidance says postgraduate researchers should not expose confidential, personal, or sensitive data to third-party AI tools unless there is an approved data processing agreement and explicit consent where required.

Review: Agent reviewedConfidence94%

Normalized value: pgr_no_confidential_personal_sensitive_data_to_third_party_ai_without_dpa_consent

Bukti asal

Evidence 1
Data protection: do not expose confidential, personal, or sensitive data to third-party tools unless there is an approved data processing agreement and explicit consent where required. Uploading Personal, Special-category, or Confidential Data to Public AI Services: Any content that could identify individuals, organisations, or sensitive locations. No.

Paparan setempat only

Data protection: do not expose confidential, personal, or sensitive data to third-party tools unless there is an approved data processing agreement and explicit consent where required. Uploading Personal, Special-category, or Confidential Data to Public AI Services: Any content that could identify individuals, organisations, or sensitive locations. No.

Ai Tool Treatment

Royal Holloway tells Foundation, undergraduate, and postgraduate taught students that module assessment briefs take precedence for AI use; if a brief says AI is not permitted, students must not use it and must declare any AI use clearly and honestly.

Review: Agent reviewedConfidence93%

Normalized value: assessment_brief_precedence

Bukti asal

Evidence 1
This guidance provides a broad overview, but all students must follow specific instructions in module assessment briefs as local guidance always takes precedence. If the brief says AI is not permitted, you must not use it. You must declare any AI use clearly and honestly.

Paparan setempat only

This guidance provides a broad overview, but all students must follow specific instructions in module assessment briefs as local guidance always takes precedence. If the brief says AI is not permitted, you must not use it. You must declare any AI use clearly and honestly.

Ai Tool Treatment

Royal Holloway recommends Microsoft Copilot for generative AI use when students log in with Royal Holloway account details, and warns students to be extremely careful when entering data into other generative AI tools.

Review: Agent reviewedConfidence92%

Normalized value: microsoft_copilot_recommended_with_rhul_login

Bukti asal

Evidence 1
From the many generative AI tools, Royal Holloway recommends that you use Microsoft Copilot, logging in with your Royal Holloway account details. Please be extremely careful when entering data into a generative AI tool: this is particularly important if you are using one other than MS Copilot and your RHUL login.

Paparan setempat only

From the many generative AI tools, Royal Holloway recommends that you use Microsoft Copilot, logging in with your Royal Holloway account details. Please be extremely careful when entering data into a generative AI tool: this is particularly important if you are using one other than MS Copilot and your RHUL login.

Source Status

The official AI guidance verified in this crawl is scoped to Foundation, undergraduate, postgraduate taught students, and postgraduate researchers; this crawl did not verify a separate staff-wide binding AI teaching policy.

Review: Agent reviewedConfidence78%

Normalized value: verified_sources_student_and_pgr_scoped_no_staffwide_policy_found

Bukti asal

Evidence 1
Guidance for our Foundation, Undergraduate and Postgraduate Taught Students. This guidance outlines how students at the University may and may not use Artificial Intelligence (AI) tools in their academic work.

Paparan setempat only

Guidance for our Foundation, Undergraduate and Postgraduate Taught Students. This guidance outlines how students at the University may and may not use Artificial Intelligence (AI) tools in their academic work.

Bukti asal

Evidence 2
This guidance sets out expectations for the ethical and responsible use of generative artificial intelligence by postgraduate researchers. It aligns with institutional research integrity, data protection, and academic misconduct regulations.

Paparan setempat only

This guidance sets out expectations for the ethical and responsible use of generative artificial intelligence by postgraduate researchers. It aligns with institutional research integrity, data protection, and academic misconduct regulations.

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

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.

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

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.

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