Sheffield, United Kingdom

The University of Sheffield

The University of Sheffield has 18 source-backed AI policy claims from 8 official source attributions. Review state: agent reviewed; 18 reviewed claims. Last checked May 23, 2026.

The University of Sheffield AI policy short answer

v1 public contract

The University of Sheffield has 18 source-backed AI policy claims from 8 official source attributions, including 18 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 23, 2026. Discovery context: The University of Sheffield is listed as QS 2026 rank 92.

Citation-ready summary

As of this public record, University AI Policy Tracker lists The University of Sheffield as an agent-reviewed AI policy record last checked on May 23, 2026 and last changed on May 23, 2026. The record contains 18 source-backed claims, including 18 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/the-university-of-sheffield.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 coverage18 reviewedSource languageenPublic JSON/api/public/v1/universities/the-university-of-sheffield.json

Policy signals in this record

  • Evidence includes Source status claims.
  • Evidence includes Research claims.
  • Evidence includes Privacy claims.
  • Evidence includes Security review claims.
  • Evidence includes Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Teaching claims.
  • Evidence includes Other policy claims.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims18Reviewed18Candidate0Official 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 confidence80%

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.

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

18 reviewed evidence-backed public claim

Source Status

StudySkills@Sheffield guidance says GenAI detection tools are not used at the University of Sheffield because of error-rate and false-positive or false-negative concerns.

Review: Agent reviewedConfidence96%

Normalized value: genai_detection_tools_not_used_due_to_error_rate_concerns

Oryginalny dowod

Evidence 1
GenAI detection tools are not used at the University of Sheffield. This is due to concerns over their error rates and the potential for both false positives and false negatives when scanning for potential use of GenAI.

Research

Sheffield PGR guidance says postgraduate researchers' use of generative AI must align with the University's expectations for responsible research and academic integrity.

Review: Agent reviewedConfidence96%

Normalized value: pgr_genai_use_must_align_responsible_research_academic_integrity_expectations

Oryginalny dowod

Evidence 1
PGRs, as researchers, produce original knowledge for an assessment (thesis and viva) that leads to the PhD, and as such, you must be mindful of the principles of research integrity and academic integrity, and your use of generative AI must align with the University's expectations for responsible research and academic integrity.

Privacy

The PGR guidance says researchers must ensure confidential, proprietary, or personally identifiable information is never uploaded to any GenAI platform.

Review: Agent reviewedConfidence96%

Normalized value: researchers_must_not_upload_confidential_proprietary_or_identifiable_information_to_genai

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Evidence 1
Researchers must ensure that confidential, proprietary, or personally identifiable information is never uploaded to any GenAI platform.

Security Review

IT Services productivity principles say only University-approved AI tools should be used for official University business, and staff have access to Google Gemini as the institutionally supported GenAI tool.

Review: Agent reviewedConfidence96%

Normalized value: official_university_business_uses_university_approved_ai_tools

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Evidence 1
Only University-approved AI tools should be used for official University business. All staff have access to Google Gemini as the institutionally-supported GenAI tool.

Privacy

IT Services productivity principles say AI use must comply with GDPR and University data-protection policies, and sensitive or confidential information must not be entered into public or unregulated AI models.

Review: Agent reviewedConfidence96%

Normalized value: ai_use_must_comply_with_gdpr_and_no_sensitive_data_in_public_unregulated_models

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Evidence 1
All use of AI must comply with GDPR and the University's data protection policies. Sensitive or confidential information must not be entered into public or unregulated AI models.

Academic Integrity

Student academic-integrity guidance tells students to check school or department guidance and module assessment criteria before using GenAI, because use may be prohibited on some modules or assessments.

Review: Agent reviewedConfidence95%

Normalized value: students_check_module_assessment_criteria_before_genai_use

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Evidence 1
The golden rule: always check your school / department guidance and the specific module assessment criteria as the use of GenAI may be specifically prohibited on certain modules or assessments.

Academic Integrity

Student academic-integrity guidance says a full disclosure of GenAI-produced content should always be acknowledged, and passing off that content as one's own work counts as academic misconduct.

Review: Agent reviewedConfidence95%

Normalized value: genai_content_disclosure_required_passing_off_counts_academic_misconduct

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Evidence 1
A full disclosure of any content produced by GenAI should always be acknowledged in your work. Attempts to pass off content as your own work is counted as academic misconduct and may lead to action being taken against you.

Ai Tool Treatment

IT Services productivity principles say GenAI use is optional except where a team has adopted it for specific tasks, and it is a supportive resource rather than a mandatory requirement for any role.

Review: Agent reviewedConfidence95%

Normalized value: staff_productivity_genai_optional_supportive_not_mandatory

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Evidence 1
The use of GenAI, except where your team may have adopted use for specific tasks, is optional. This technology is intended to be a supportive resource, not a mandatory requirement for any role.

Ai Tool Treatment

The University of Sheffield identifies Google Gemini as the institutionally supported GenAI tool for learning and teaching, and says Gemini should be used where possible to support those activities.

Review: Agent reviewedConfidence94%

Normalized value: google_gemini_institutionally_supported_genai_tool_for_learning_and_teaching

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Evidence 1
All students and staff have access to Google Gemini as the institutionally supported GenAI tool. Where possible, Gemini should be used to support learning and teaching activities.

Teaching

The University of Sheffield says every undergraduate programme integrates GenAI literacy through structured teaching activities and formal assessment, while giving staff and students clarity about acceptable AI use across assessments.

Review: Agent reviewedConfidence93%

Normalized value: undergraduate_programmes_integrate_genai_literacy_and_assessment_clarity

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Evidence 1
The University has developed a Common Approach to ensure every undergraduate programme integrates GenAI literacy through structured teaching activities and formal assessment, while providing clarity to staff and students about acceptable AI use across all assessments.

Research

The PGR guidance permits students to use generative AI in thesis writing, provided the use is consistent with the guidance and properly declared, and warns that exceeding the guidance risks breaching the Academic Misconduct Policy.

Review: Agent reviewedConfidence92%

Normalized value: pgr_thesis_genai_use_permitted_if_consistent_and_declared

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Evidence 1
Yes, students are permitted to make use of generative AI tools in their thesis writing processes. You should declare your use of GenAI tools and take full responsibility for the content of your submitted thesis.

Academic Integrity

Assessment guidance says that when GenAI use is allowed, students may be asked to provide full disclosure using an Acknowledge, Describe, Evidence template, while noting that some schools may use a different process.

Review: Agent reviewedConfidence91%

Normalized value: allowed_assessment_genai_use_may_require_acknowledge_describe_evidence_disclosure

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Evidence 1
In assignments where you are sure that you are allowed to use GenAI, you may be asked to provide a full disclosure of how you have done so. You can provide this information by completing an Acknowledge, Describe, Evidence template.

Academic Integrity

The University of Sheffield tells students that GenAI outputs should not be used as sources for assessment and should never be cited as if they were sources.

Review: Agent reviewedConfidence90%

Normalized value: The University of Sheffield tells students that GenAI outputs should not be used as sources for assessment and should never be cited as if they were sources.

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Evidence 1
GenAI outputs should not be used as sources for assessment and you should never cite anything from a GenAI tool.

Academic Integrity

The University of Sheffield says it does not support use of sites that share lecture notes, essays, lab reports, or exam questions.

Review: Agent reviewedConfidence90%

Normalized value: The University of Sheffield says it does not support use of sites that share lecture notes, essays, lab reports, or exam questions.

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Evidence 1
The University does not support the use of sites that share content such as lecture notes, essays, lab reports or exam questions.

Privacy

The University of Sheffield tells students not to provide personal, private, or confidential information in GenAI prompts.

Review: Agent reviewedConfidence90%

Normalized value: The University of Sheffield tells students not to provide personal, private, or confidential information in GenAI prompts.

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Evidence 1
You should not provide any personal, private or confidential information in your prompts.

Academic Integrity

The University of Sheffield warns that unpermitted GenAI use may be treated as unfair advantage even if the student discloses it.

Review: Agent reviewedConfidence90%

Normalized value: The University of Sheffield warns that unpermitted GenAI use may be treated as unfair advantage even if the student discloses it.

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Evidence 1
Even if you make a full disclosure of your use of GenAI, if this is not specifically permitted in your assessment criteria... there is a risk of this use being considered an unfair advantage.

Security Review

For student-facing tools outside Google Suite, the University says the New IT Solution Request Process is followed to check data-protection and information-security compliance before those tools are made available on a use-case basis.

Review: Agent reviewedConfidence90%

Normalized value: student_non_google_ai_tools_use_case_it_solution_review_for_data_protection_security

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Evidence 1
Where tools other than Google Suite are made available to students on a use case basis, the New IT Solution Request Process has been followed to ensure they comply with data protection and information security policies.

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 23, 2026Last changedMay 23, 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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