Teaching & Learning
- The university also states that each assessment should provide its own guidance
- Undeclared AI-generated or AI-improved work submitted for marks is treated as false authorship
- For assessed work, AI use is controlled through a university color-coded system and can range from prohibited to assistive or integral depending on the specific assessment guidance
The University has introduced a colour coded categorisation system intended to help students understand how to use Gen AI in a particular assessment, by how much they may use it and at what stage of the assessment:
RED: Gen AI Tools are NOT permitted
AMBER: Gen AI Tools can be used in an assistive role
GREEN: Gen AI Tools have an integral role
Each assessment has specific guidance and the placement module is no different.
AM 2.3.1 False Authorship is a form of plagiarism where the student has deliberately engaged with a third party and/or software tool to complete an assessment, either in part or whole. This engagement can be direct or through an intermediary. This may include work produced by another individual, an essay mill, a commercial service, or through the use of Artificial Intelligence software. As it is the authorship of work that is contested, there is no requirement to prove that the work has been purchased. The submission of undeclared work which is either generated and/or improved by language model software for the purposes of gaining marks will be regarded as False Authorship and interpreted as an attempt to gain an intentional unfair academic advantage.
- Assessment rules vary by the university's red-amber-green categorization and by the guidance attached to each assessment
- The university encourages assessment design that includes in-person written assessments such as exams as a form that is harder for generative AI to do well, but the clearest formal rule provided is that AI permission depends on the assessment-specific guidance
The University has introduced a colour coded categorisation system intended to help students understand how to use Gen AI in a particular assessment, by how much they may use it and at what stage of the assessment:
RED: Gen AI Tools are NOT permitted
AMBER: Gen AI Tools can be used in an assistive role
GREEN: Gen AI Tools have an integral role
Each assessment has specific guidance and the placement module is no different.
There is no such thing as a Gen AI-proof assignment, but it's possible to design tasks that are harder for Gen AI to do well. Examples include:
* Presentations: either live in person, or recorded via video and or audio.
* Process-based assignments such as keeping a reflective journal, or a scaffolded assignment
* In-person written assessments, such as exams.
- The university also warns against over-reliance on AI so students still develop their own skills
- AI is permitted for learning support when used to help rather than replace learning, and the university encourages students to use it critically
- In the social work placement guidance, staff may permit AI for learning outside the formal module assessment, but students must still comply with assessment guidance and seek advice if unsure
Show students how to use AI to enhance their learning rather than undermine it.
Students can use AI to bypass their learning activities by automating certain tasks such as researching and writing their assignments. But they can also use AI to do better, deeper research and to develop their written work by providing feedback on their plans and drafts and suggesting improvements.
Remember that students must comply with the assessment guidance issued for the placement module. Where you do permit students to use Gen AI for learning outside of the formal module assessment (and portfolio they submit) a simple three stage process may help you to get started:
Students must be absolutely clear where they may and may not use Gen AI during their placement: if they have any questions they must seek advice before using Gen AI.
The take away message here is that you may encourage a student to use Gen AI to help with some tasks but they must not over rely on it nor use technology which may deter developing their own essential social work skills and abilities.
- No separate university-wide programming-specific student rule was identified beyond these general provisions
- Within the SAIL platform, text and code generation are in scope for approved use by staff, students, and authorized users
- For assessed work more broadly, any code or other work produced with AI would still fall under the university's assessment rules and false authorship provisions if undeclared and used for gaining marks
The Safe AI at Lancaster (SAIL) hub provides staff, students, and authorised users with secure access to approved Generative AI tools for teaching, research, operational, and professional development purposes.
This policy applies to:
* All users of the SAIL platform, whether Bailrigg staff, students, or authorised users.
* All forms of interaction with generative AI services accessed through SAIL, including text and code generation.
AM 2.3.1 False Authorship is a form of plagiarism where the student has deliberately engaged with a third party and/or software tool to complete an assessment, either in part or whole.
The submission of undeclared work which is either generated and/or improved by language model software for the purposes of gaining marks will be regarded as False Authorship and interpreted as an attempt to gain an intentional unfair academic advantage.
Research
- No more specific research-data-analysis rule was explicitly defined in the provided sources
- Users are strongly advised not to include personal or sensitive data in SAIL, and the university's teaching guidance says personal, confidential, or restricted data must not be entered into AI tools
- Lancaster states that AI can support research and provides a university-managed environment for that use through SAIL, but it also places data-protection restrictions on what may be entered into AI systems
Throughout the Proof of Value phase, participants helped us understand how AI can support learning, teaching, research, and professional services while maintaining appropriate safeguards and university oversight.
The Safe AI at Lancaster (SAIL) hub provides staff, students, and authorised users with secure access to approved Generative AI tools for teaching, research, operational, and professional development purposes.
SAIL does not request personal or sensitive data. Users are strongly advised not to include special category data or information they would not normally share in a professional or academic setting.
Whatever tool you or your students may be using, always be aware that any data you enter will be transmitted outside the institution and will often be used to train the AI model. Do not enter any personal, confidential or restricted data into an AI tool.
- The research misconduct policy provided does not explicitly mention AI
- In the provided sources, it does not set explicit AI-specific rules for grant proposals, ethics applications, or research integrity declarations
- Lancaster states at an institutional level that AI should be responsibly governed and that research use should occur with safeguards and university oversight
At Lancaster University, we believe that artificial intelligence should be accessible, secure, and responsibly governed.
Throughout the Proof of Value phase, participants helped us understand how AI can support learning, teaching, research, and professional services while maintaining appropriate safeguards and university oversight.
Academic Integrity
- Disclosure of permitted AI use is required
- More generally, undeclared AI-generated or AI-improved work submitted for marks is treated as false authorship
- In the social work guidance, the university states that where students are permitted to use AI tools, they must acknowledge that use, and any output used in placement work must include a clear declaration of AI application
The university rule is that where students are permitted to use AI tools, they must
Therefore, regardless of whether or not Gen AI has been permitted within the placement setting, the output/work/product must demonstrably be the student's own work and include a clear declaration of any application of AI.
student to use the recommended software but they must acknowledge the use of AI in their work.
The submission of undeclared work which is either generated and/or improved by language model software for the purposes of gaining marks will be regarded as False Authorship and interpreted as an attempt to gain an intentional unfair academic advantage.
- Lancaster enforces undisclosed AI use in assessed work through its academic integrity rules by treating it as false authorship and an attempt to gain unfair academic advantage
- The university also restricts use of external AI-detection or malpractice-detection platforms: students must not upload assessment work to them unless they have express permission in advance
AM 2.3.1 False Authorship is a form of plagiarism where the student has deliberately engaged with a third party and/or software tool to complete an assessment, either in part or whole.
The submission of undeclared work which is either generated and/or improved by language model software for the purposes of gaining marks will be regarded as False Authorship and interpreted as an attempt to gain an intentional unfair academic advantage.
AM 2.9 ACADEMIC MALPRACTICE & ARTIFICIAL INTELLIGENCE DETECTION SOFTWARE
AM 2.9.1 Unless express permission is received in advance, students must not submit or upload assessment submissions to any external detection software or platforms designed to inspect for academic malpractice or artificial intelligence usage. Doing so can create a false positive with individual work being lodged in assignment comparator repositories
Institutional & Administrative
- Staff and students were also given access to SAIL for teaching, research, operational, and professional-development purposes
- Lancaster provides guidance for staff and expects instructors to set clear boundaries for students about permitted AI use in courses
- No explicit rule was found in the provided sources about staff use of AI for grading, recommendation letters, or feedback automation specifically
Be clear from the outset about what uses of Gen AI are permitted on your course and at University more generally. Point students to the University guidance on the use of generative AI in their learning and assessment.
At Lancaster University, we believe that artificial intelligence should be accessible, secure, and responsibly governed. SAIL (Safe AI at Lancaster) was developed to explore how students and staff could access AI tools within a university-managed environment that prioritises privacy, security, and responsible use.
The Safe AI at Lancaster (SAIL) hub provides staff, students, and authorised users with secure access to approved Generative AI tools for teaching, research, operational, and professional development purposes.
- Lancaster directs users toward university-managed or approved AI environments and imposes clear data-protection limits
- SAIL is described as a secure university-managed environment with approved generative AI tools, and its privacy notice says users should not include special-category or other sensitive data
- The university's broader guidance also says personal, confidential, or restricted data must not be entered into AI tools, and LUCA states that prompts and outputs are not used to train external AI models
SAIL (Safe AI at Lancaster) was developed to explore how students and staff could access AI tools within a university-managed environment that prioritises privacy, security, and responsible use.
The Safe AI at Lancaster (SAIL) hub provides staff, students, and authorised users with secure access to approved Generative AI tools for teaching, research, operational, and professional development purposes.
SAIL does not request personal or sensitive data. Users are strongly advised not to include special category data or information they would not normally share in a professional or academic setting.
Whatever tool you or your students may be using, always be aware that any data you enter will be transmitted outside the institution and will often be used to train the AI model. Do not enter any personal, confidential or restricted data into an AI tool.
LUCA has a privacy-first design. Your data is encrypted, kept for a short retention period, and never used to train external AI models.
Prompts and outputs are not used to train or improve external AI models.
- Lancaster has an institutional governance stance that AI should be accessible, secure, and responsibly governed
- This indicates an evolving university-wide governance and adoption approach rather than a single static policy document in the provided sources
- Its strategy includes university guidance for staff and students, a red-amber-green framework for AI in assessment, and the SAIL initiative as a secure university-governed AI environment whose pilot outcomes are being reviewed to inform future decisions
At Lancaster University, we believe that artificial intelligence should be accessible, secure, and responsibly governed.
Throughout the Proof of Value phase, participants helped us understand how AI can support learning, teaching, research, and professional services while maintaining appropriate safeguards and university oversight.
The outcomes of the pilot are currently being reviewed and evaluated. Future decisions regarding the service will be informed by the evidence, feedback, and lessons learned during the Proof of Value phase.
Learn more about the University position on AI, including information about the Red-Amber-Green statuses for AI in assessment, for staff and students.
DocuMark: Responsible AI Use for Academic Integrity
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Common Questions About Lancaster University's AI Policies
Lancaster University has defined AI policies in 11 of 12 categories, with an overall coverage score of 92%.
Disclosure of permitted AI use is required. In the social work guidance, the university states that where students are permitted to use AI tools, they must acknowledge that use, and any output used in placement work must include a clear declaration of AI application. More generally, undeclared AI-generated or AI-improved work submitted for marks is treated as false authorship.
Lancaster enforces undisclosed AI use in assessed work through its academic integrity rules by treating it as false authorship and an attempt to gain unfair academic advantage. The university also restricts use of external AI-detection or malpractice-detection platforms: students must not upload assessment work to them unless they have express permission in advance.
Lancaster directs users toward university-managed or approved AI environments and imposes clear data-protection limits. SAIL is described as a secure university-managed environment with approved generative AI tools, and its privacy notice says users should not include special-category or other sensitive data. The university's broader guidance also says personal, confidential, or restricted data must not be entered into AI tools, and LUCA states that prompts and outputs are not used to train external AI models.