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Imperial College London

Imperial College London is listed as QS 2026 rank 2. Imperial College London has 10 source-backed AI policy claim records from 14 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Last checkedMay 6, 2026Last changedMay 6, 2026Review: Agent reviewedConfidence95%
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Imperial College London is listed as QS 2026 rank 2. Imperial College London has 10 source-backed AI policy claim records from 14 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Reviewed claims10Candidate claims0Official sources14

Candidate claims are source-backed records pending review. They are not final policy conclusions and are not legal or academic integrity advice.

Reviewed claims

10 reviewed public claim

Academic Integrity

Unless explicitly authorised, using generative AI to create assessed work may be treated as an academic offence such as contract cheating under Imperial's Plagiarism, Academic Integrity & Exam Offences regulations. Improper use of AI can be investigated under the University's Academic Misconduct procedures.

Review: Agent reviewedConfidence95%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Unless explicitly authorised, using AI to create assessed work may be treated as an offence such as contract cheating under Imperial's Plagiarism, Academic Integrity & Exam Offences regulations. Familiarise yourself with Imperial's Academic Misconduct Policy for rules on appropriate AI usage.
Source language
English (en)
Snapshot hash
abae555edd554e7837059feeb0e11971007f3a1fd5f27b644be02f87ae23d41a
Retrieved
May 6, 2026
Evidence locator
Library Services - Generative AI guidance: 'Appropriate academic use of generative AI' section

Teaching

Individual departments at Imperial may allow or prohibit the use of generative AI for specific assessments. Local (team/department/faculty) instructions take precedence over university-wide guidance. Students should check their department's current policy on using and disclosing generative AI in academic work and follow their module leader's instructions.

Review: Agent reviewedConfidence95%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Individual departments may allow or prohibit GenAI for specific assessments; local (team/department/faculty) instructions take precedence. Always check the brief and acknowledge permitted AI use as directed.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Section 5(i) - Responsible uses: Assessment-related use

Privacy

Imperial's dAIsy AI platform uses University SSO authentication with auditing. Prompts and metadata are logged for operational monitoring, and AI model providers are configured not to train on user data. Users' prompts and responses are not used to train external AI models. dAIsy is approved for use with unrestricted data within Imperial's secure infrastructure.

Review: Agent reviewedConfidence95%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
dAIsy uses University SSO and auditing. Logs (prompts/metadata) are retained for operational monitoring. Model providers are configured to not train on your data.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Section 6 - Data handling, security and privacy

Academic Integrity

Breaches of Imperial's dAIsy Use Policy may lead to action under Academic Misconduct procedures for students and HR/disciplinary processes for staff, as well as under Information Security and Data Protection policies. Sanctions may include removal of access, grade penalties, or formal disciplinary measures.

Review: Agent reviewedConfidence95%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Breaches may lead to action under Academic Misconduct (students) and HR/disciplinary processes (staff), as well as Information Security and Data Protection policies. Sanctions may include removal of access, grade penalties, or formal disciplinary measures.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Section 13 - Compliance and sanctions

Teaching

Students should include a statement acknowledging their use of generative AI tools for all assessed work, specifying the tool name and version, publisher, URL, a brief description of how it was used, and confirmation that the work is their own. Further requirements such as prompts used, date of output, the output obtained, and how it was modified may also be required by individual departments.

Review: Agent reviewedConfidence90%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
You should include a statement to acknowledge your use of generative AI tools for all assessed work, in accordance with guidelines from your department or course team. This statement should be written in complete sentences and include the following information: Name and version of the generative AI tool e.g. Copilot, ChatGPT-5; Publisher (name of company that provides the AI system) e.g. Microsoft, OpenAI; URL of the AI tool; Brief description (single sentence) of the way in which the tool was used; Confirmation that the work is your own.
Source language
English (en)
Snapshot hash
abae555edd554e7837059feeb0e11971007f3a1fd5f27b644be02f87ae23d41a
Retrieved
May 6, 2026
Evidence locator
Library Services - Generative AI guidance: 'Acknowledging and referencing use of generative AI tools' section

Research

Research at Imperial that involves people, personal data, or sensitive topics may require ethics approval, a Data Protection Impact Assessment (DPIA), and data-governance controls before using any AI tool. Researchers must verify whether their use of AI in research requires special approval, particularly when uploading private or confidential research data.

Review: Agent reviewedConfidence90%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Research that involves people, personal data, or sensitive topics may require ethics approval, a Data Protection Impact Assessment (DPIA), and data-governance controls before using any AI tool.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Section 5(iii) - Responsible uses: Research use

Other

All Imperial staff and students have access to Microsoft Copilot with Commercial Data Protection when signed in using their Imperial credentials. Microsoft Copilot has no access to organizational data in the Microsoft 365 Graph. Chat results are not saved or made available to Microsoft, and data does not pass outside the organisation.

Review: Agent reviewedConfidence90%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
All Imperial staff and students have access to Microsoft Copilot. You should ensure you sign in to use Copilot so that you are using the secure version of Microsoft Copilot with Commercial Data Protection. MS Copilot has no access to organizational data in the Microsoft 365 Graph. Your data is protected and the chat results are NOT saved or made available for Microsoft, so the data does not pass outside of the organisation.
Source language
English (en)
Snapshot hash
315c865f429a17a2085919a998fa5bf0d58a9e2342651f629314ad4f868ec8f1
Retrieved
May 6, 2026
Evidence locator
ICT page on Microsoft Copilot - access and data protection sections

Other

Users of Imperial's dAIsy AI platform must always apply critical judgment to AI outputs. Generative AI can produce inaccurate or biased outputs ('hallucinate'), omit context, or reflect training-data biases. Users remain accountable for the accuracy, legality, and appropriateness of any content they submit or share through the platform.

Review: Agent reviewedConfidence90%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Always apply critical judgement. GenAI can 'hallucinate', omit context, or reflect training-data biases. Users remain accountable for the accuracy, legality, and appropriateness of any content they submit or share.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Section 8 - Quality, bias and human oversight

Other

Users of Imperial's dAIsy platform must not upload third-party content they are not permitted to share. Reuse of AI outputs must comply with licensing and academic citation norms. When communicating externally, dAIsy outputs must not be presented as Imperial's position without approval.

Review: Agent reviewedConfidence90%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
Do not upload third-party content you are not permitted to share. Ensure that any reuse of AI outputs complies with licensing and academic citation norms. When communicating externally, do not present dAIsy outputs as Imperial's position without approval.
Source language
English (en)
Snapshot hash
af7248595f4e6390847e500476a0e0840e335c3205db15df5ed3c70b042e480c
Retrieved
May 6, 2026
Evidence locator
dAIsy Use Policy Sections 11 (Copyright and IP) and 12 (Communications and transparency)

Teaching

Imperial College London has established five Generative AI Principles (aligned with Imperial Values: Respect, Collaboration, Excellence, Integrity, Innovation) to provide a foundational framework for approaches to using generative AI in teaching, learning and assessment university-wide. The principles cover promoting critical use of AI, adopting a consistent ethical approach, and building a proactive research community around AI in education.

Review: Agent reviewedConfidence85%
Last checked
May 6, 2026
Last changed
May 6, 2026

Original evidence

Evidence 1
These principles are intended to provide a starting point for approaches to using generative AI in teaching, learning and assessment at Imperial. Imperial supports the use of the principles to frame and underpin activities university-wide as we as a community explore the use of generative AI, progress and develop policy, and establish guidelines. The principles are underpinned by Imperial's core Values. ... Promoting the critical use of generative AI in teaching, learning and assessment. Adopting a consistent ethical approach to the use of generative AI. Building a proactive research community around the use of generative AI.
Source language
English (en)
Snapshot hash
8e2e65292a63189e93172810ff4ba9ff98e77d13894233c506f64f803d0bc94f
Retrieved
May 6, 2026
Evidence locator
Generative AI Principles page - introductory and principles sections

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

14 source attribution

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