All Student Vote (Autumn 2026)
Warwick SU to lobby the university for an ethical stance on AI #2
This motion proposes that Warwick SU should lobby the University to adopt an ethical position on the use of AI and large language models by limiting their promotion and use across teaching, assessment, governance, and marketing. Warwick SU should lobby for opt-in policies and declarations of AI use, strengthening academic integrity frameworks, accounting for environmental impacts in sustainability policy, and ensuring staff and student representation in all AI-related decision-making.
This Union notes:
1. That the popularity of Artificial Intelligence (AI)/Large Language Models (LLMs) has risen in the past 3 years prompting its rapid integration into institutional systems and individual workflows. At the same time, regulation of AI/LLMs development and use has lagged.
2. That this rapid, uncontrolled integration is impacting the livelihoods of students and Postgraduate staff, contributing to the ecological crisis, disturbing long-standing social and academic norms and conventions.
3. Turnitin is looking to use student assessment in the training of their AI models, exploiting the intellectual property of students. (Times Higher Education, 2026).
4. That there is a growing number of students (Warwick Student Survey) who are ethically opposed to the use of AI in academic work and should not be excluded from assessment on ethical grounds.
Evidence
1. That ChatGPT queries use ten times the amount of energy as Google searches, with more complex queries using even greater amounts (EPRI, 2024).
2. That the number of data centres needed to support increased use of AI/LLMs in the UK is set to increase by almost a fifth, including one in Herefordshire which will be built on a greenbelt (Kleinman & Shveda, 2025).
3. That AI/LLMs emit the equivalent of more than 8% of the annual global emission of aviation and consume the equivalent of the entire energy consumption of New York City (Dodds, 2025).
4. That AI/LLMs are increasingly used to replace the work of humans within managerial and academic spaces, in the name of efficiency and productivity. Yet, reviews of AI/LLMs integration suggests that AI/LLMs doing so does not actually reduce the burden of work on workers, especially if integration is followed by layoffs. (Niederhoffer et al. 2025; Walther, 2025; Rogelberg, 2026)
5. That AI/LLMs work still needs to be checked, verified, and augmented by humans. This means that workers could end up with more work, because not only do they have to do their own work, but now they have to check the work of AI to ensure accuracy and reliability. In one case, such work has been outsourced to prisoners, with extremely low-pay and non-existent workers protection (Meaker, 2023).
6. That higher-powered AI/LLMs are often paywalled behind a costly subscription, reinforcing existing socio-economic inequalities putting students from low affluent backgrounds at a greater disadvantage.
7. That continuous and uncritical use of AI/LLMs have been found to be linked with cognitive decline (Gerlich, 2025).
8. That AI/LLMs are trained on extremely large data sets which are partly sourced from illegal and extralegal means. Literature and visual arts have been scraped off the internet by AI/LLM developers, often without permission from or compensation to the authors. This is worse for small-scale artists, which often do not have the resources to lodge a copyright infringement against multi-billion dollar developers. (The Authors Guild, 2023; Grynbaum & Mac, 2023; Reisner, 2025)
This Union believes:
1. That the University, which aims to be sustainable, should not use and promote tools that increase carbon emissions and promote greenbelt developments.
2. That the University, as an academic institution, should not endorse nor engage in business practices that devalue the work of artists, authors, and academics through the scraping off, replication, and imitation of their work by AI/LLMs.
3. That the University, as an academic institution, should seek to protect the process of critical thinking and other essential academic skills (such as referencing and note-taking), and so they should not promote short-cut measures such as AI/LLM tools.
4. That AI/LLMs, as currently designed and operated, are profiting from the stolen work and labour of artists, authors, and academics.
This Union resolves:
Management
1. For the resolutions of this stance be under the remit primarily of the VP Education Officer, VP Postgraduate Officer and VP Democracy and Development Officer as well as in committees where AI is discussed.
2. To lobby the University to require a declaration of AI use, when and where AI is used in a non-exhaustive list of assessments, modules, assignments, lectures and feedback.
3. To lobby the University to provide a guarantee that student work will not be graded by generative AI or LLMs.
4. To lobby the University to ensure that all departments publicise clear guides for how and where students may use AI/LLMs in assignments.
5. To lobby for a stronger framework for assessing academic misconduct regarding the use of AI in assignments and Exams.
6. To lobby the University to not renew its contract with software or companies which exploit student’s academic work in the training of AI, such as turnitin plagiarism detector.
7. To lobby the university to ensure students are able to complete their modules, assessments, and courses without the required use of AI (where applicable).
8. To lobby the University to not use AI/LLMs tools to generate images, videos, or music for marketing and promotion purposes, or otherwise to use AI/LLMsgenerated images, videos, or music for marketing and promotion purposes.
9. To lobby the University to not accept sponsorships or business partnerships with AI/LLM companies.
10.To lobby the University to not use AI/LLMs tools in the creation or amendment, in part or in full, of governance documents, including byelaws and regulations.
11.To lobby the University to put in place an ‘opt-in’ policy for AI/LLMs tools, where staff must opt-in to the use of any AI tools for their work.
12.To lobby the University to incorporate in future sustainability policy assessment of AI/LLMs impacts on its Scope 2 and 3 emissions and how they mitigate the
environmental impacts of AI/LLMs.
13.To lobby the University to include students in the ongoing policy-development and consultations on AI in educational spaces
14.To lobby the University to not use AI/LLMs tools based on or that replicates, imitates, or uses the personality or likelihood of any person.
15.To lobby the University to require a declaration of AI/LLMs use as part of teaching and learning in the module approval form for staff, including where and how the AI/LLM tools are to be used.
Sources:
Dodds, Io (2025)
https://www.independent.co.uk/tech/ai-data-center-emissions-environmentb2887454.html
EPRI (2024).
https://www.epri.com/research/products/3002028905
Grynbaum, M. & Mac, R. (2023).
https://www.nytimes.com/2023/12/27/business/media/new-york-times-open-aimicrosoft-lawsuit.html
Kleinman, Z & Shveda, K, (2025).
https://www.bbc.co.uk/news/articles/clyr9nx0jrzo
Meaker, M. (2023)
https://www.wired.com/story/prisoners-training-ai-finland/
Niederhoffer G Kellerman, A Lee, A Liebscher, K Rapuano and J T.
https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity
Reisner, A. (2025). https://www.theatlantic.com/technology/archive/2025/03/libgenmeta-openai/682093/
Rogelberg, S. (2026).
https://fortune.com/article/does-ai-increase-workplace-productivity-experimentsoftware-developers-task-took-longer/
The Authors Guild (2023). https://authorsguild.org/news/ag-and-authors-file-classaction-suit-against-openai/
Times Higher Education (2026).
https://www.timeshighereducation.com/news/southampton-dumps-turnitin-over-usestudents-work-train-ai
Walther, C. (2025)
https://knowledge.wharton.upenn.edu/article/the-ai-efficiency-trap-when-productivityto