AI in Education

AI in education

Conditions for thinking.

Thinking with AI.

AI in Education is a poster campaign for students, staff, leaders, and parents at the University of Warwick. It is a campaign for the conditions under which thinking happens with the use of AI.

Each poster borrows the voice of AI promotion: the promise of speed, ease, a personal assistant, a future you must not be left behind by. Then it turns on an asterisk. The small print returns the borrowed words to where they came from, and asks what happens to learning, teaching, reading, writing, feedback and attention when AI arrives.

The campaign works with the idea of intoxication. What intoxicates and what is toxic are often the same substance in a different dose. The difference here is that no one in a University chooses their dose: AI arrives as infrastructure. The posters use satire to make that arrival visible enough to talk about.

The satirical approach is inspired by Save the AI (Just Sustainability Design Lab, University of Toronto).

Project team

Siddharth de Souza, CIM

Yuxuan Chua, CIM/PAIS

Jennie Mills, Education Academy

Maria Sierra Montero, CIM

A Big Questions in the Social Sciences project, funded by the Faculty of Social Sciences, University of Warwick

What are we asking?

Where and how does AI show up in higher education - and what do we do when it does?
What are we using AI for - and what do we think it is for?
What does it add and what does it take away?
What is missing from the policies and pedagogies we already have?
What happens to learning, teaching, critical thinking, and creativity when AI enters the University?
Who decided AI was 'unavoidable' - is it?

Why toxicity?

Humans, like lemurs, waxwings, and fruit flies, like to be intoxicated to a certain extent - chocolate, alcohol, prescribed and illegal drugs - name your poison. We treat AI and its projected dreamy visions ("you won't need to work", "you'll have your AI friends", "learn and produce faster", "enhance your capabilities") the same way; an irresistible something we can consciously 'ingest' - choosing our own level of consumption and intoxication.

This mind-altering intake embodies AI's uses and effects: it is something in us (desire, pleasure, escape) and on us (we are accountable, responsible, implicated) - not outside of us.

What we did

1. Analysis

Analysed all accessible AI-related policies and guidance at the University of Warwick - institutional and departmental - to understand how educators and students were conceptualising and encountering AI.

2. Workshops

Hosted two co-creation workshops open to the Warwick community. Participants included staff, students, and professional service colleagues to expand understanding of attitudes to and use of AI at the University and beyond. Workshops were informed by the ethos of critical pedagogy - open, diverse and collaborative. We echoed the policies and guidance back to the community - inviting them to peep over departmental fences - and then asked them to map their own AI landscapes and create a collective map.

Participants then worked in small groups to collage their own AI policy.

3. Design

The project team worked with the material produced in the workshops and drew on it to develop 11 posters - the basis of the ad campaign.

4. Manifesto

Each poster closes on a line of resistance which together form a manifesto for thinking with AI. Not for AI. Not against AI. For the conditions for thinking.

5. Campaign

By making these posters available the project publicises and enables a collective response to AI which promotes dialogue over debate. Form and function leans into the novel, ambiguous, and paradoxical conditions that AI creates.

The posters

AI-ready workforce, compliant graduates

AI-ready* workforce, compliant graduates

Poster: a low-angle photograph looking up between the sandstone walls of Antelope Canyon. Large text reads “AI-ready workforce, compliant graduates”, with an asterisk after “AI-ready”. Small print follows.

Download the Employability poster (PDF, 3KB )

*Employers want AI-ready graduates, so subscribe to their thinking service. The future you are being prepared for is being built by the companies selling the preparation tools. Skip the reading. Skip the essay struggle. Skip the tutorial. Skip the friction. The is the work that made graduates employable. It is no longer required.

But is your role in this future specified?

No. Keep your whole self. The slow bits. Because the slow bit is where you happen.

Photo: SAFEE / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Risko & Gilbert (2016) Cognitive offloading, Trends in Cognitive Sciences 20(9) https://doi.org/10.1016/j.tics.2016.07.002Link opens in a new window

Fütterer, T., Gerjets, P., Steinhäuser, R., Fabian, A., Udvardi-Lakos, N., Greene, J.A., Bernacki, M.L., Brod, G. and Trautwein, U. (2026) 'Why using AI as a learning coach can improve education', Nature Human Behaviour 10: 1861-1863. Available at: https://doi.org/10.1038/s41562-026-02524-2Link opens in a new window.

Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö. and Mariman, R. (2025) 'Generative AI without guardrails can harm learning: evidence from high school mathematics', Proceedings of the National Academy of Sciences, 122(26), e2422633122. Available at: https://doi.org/10.1073/pnas.2422633122Link opens in a new window.

Bjork, E.L. and Bjork, R.A. (2011) 'Making things hard on yourself, but in a good way: creating desirable difficulties to enhance learning', in Gernsbacher, M.A., Pew, R.W., Hough, L.M. and Pomerantz, J.R. (eds) Psychology and the real world: essays illustrating fundamental contributions to society. New York: Worth Publishers, pp. 56–64. Available at: https://bjorklab.psych.ucla.edu/wp-content/uploads/sites/13/2016/04/EBjork_RBjork_2011.pdfLink opens in a new window (Accessed: 28 October 2026).

Universities UK (2026) Future jobs roadmap. London: Universities UK. Available at: https://future.universitiesuk.ac.uk/future-jobs/roadmapLink opens in a new window (Accessed: 4 November 2026).

World Economic Forum (2025) The future of jobs report 2025. Geneva: World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2025/digest/

Brynjolfsson, E., Chandar, B. and Chen, R. (2026) 'Canaries in the coal mine? Six facts about the recent employment effects of artificial intelligence'. Stanford Digital Economy Lab working paper, revised 12 August 2026 (first published 2025). Available at: https://digitaleconomy.stanford.edu/publications/canaries-in-the-coal-mine/Link opens in a new window (Accessed: 28 October 2026).

Times Higher Education (2026) 'Most employers have no plans to replace graduate roles with AI', Times Higher Education, 16 April. Available at: https://www.timeshighereducation.com/node/742437Link opens in a new window (Accessed: 28 October 2026).

AI-splained: a voice on demand.

AI-splained: a voice* on demand

Download the Voice poster (PDF 3KB)

* No more standing at the edge of a thought wondering whether to step forward. No more half-remembered idea that nagged at you for a week. No more sentence that made you want to read the next one for reasons you could not name.

What does it mean to have a voice without your voice?

Some things should not be voiced on your behalf. These are your things. Keep them. Especially the things you cannot quite say yet.

This is your voice. Keep it. Especially the voice that you cannot quite hear yet.

Photo: Joe Click / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Hunt, L. (2010) 'How writing leads to thinking (and not the other way around)', Perspectives on History, 1 February. Available at: https://www.historians.org/perspectives-article/how-writing-leads-to-thinking-february-2010/Link opens in a new window (Accessed: 4 November 2026).

Chiang, T. (2024) 'Why A.I. isn't going to make art', The New Yorker, August [check day]. Available at: https://www.newyorker.com/culture/the-weekend-essay/why-ai-isnt-going-to-make-artLink opens in a new window (Accessed: 28 October 2026).

Nature Reviews Bioengineering (2025) 'Writing is thinking: on the value of human-generated scientific writing in the age of large-language models' [Editorial], Nature Reviews Bioengineering, 3, June

https://doi.org/10.1038/s44222-025-00323-4

Agarwal, D., Naaman, M. and Vashistha, A. (2025) 'AI suggestions homogenize writing toward Western styles and diminish cultural nuances', in Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). New York: Association for Computing Machinery. Available at: https://doi.org/10.1145/3706598.3713564Link opens in a new window.

Doshi, A.R. and Hauser, O.P. (2024) 'Generative AI enhances individual creativity but reduces the collective diversity of novel content', Science Advances, 10(28), eadn5290. Available at: https://doi.org/10.1126/sciadv.adn5290Link opens in a new window.

fast, frictionless feedback

Tired of awkward presentations?

Download the fast, frictionless feedback poster (PDF, 3KB)

* You no longer need to explain your half0formed ideas to a stranger in a room. You have the prompt; the model has the answer; the lecturer has the automated rubric. The loop is perfect. Knowledge is transferred from a database to a document, then scanned by a processor. It is a miracle of modern logistics. No one has to be confused. No one has to be vulnerable. No one has to say, "I don't get it", and no one has to see the moment the light comes on in your eyes.

Where are you in this loop? No one has to care. Feedback is someone caring. The rubric scores you; a person sees you.

Don't let the loop close without you.

Photo: Kurt Barlow / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Carless, D. and Boud, D. (2018) 'The development of student feedback literacy: enabling uptake of feedback', Assessment & Evaluation in Higher Education, 43(8), pp. 1315–1325. Available at: https://doi.org/10.1080/02602938.2018.1463354Link opens in a new window.

Molloy, E., Boud, D. and Henderson, M. (2020) 'Developing a learning-centred framework for feedback literacy', Assessment & Evaluation in Higher Education, 45(4), pp. 527–540. Available at: https://doi.org/10.1080/02602938.2019.1667955Link opens in a new window.

Gravett, K., Taylor, C.A. and Fairchild, N. (2024) 'Pedagogies of mattering: re-conceptualising relational pedagogies in higher education', Teaching in Higher Education, 29(2), pp. 388–403. Available at: https://doi.org/10.1080/13562517.2021.1989580Link opens in a new window.

Henderson, M., Bearman, M., Chung, J., Fawns, T., Buckingham Shum, S., Matthews, K.E. and de Mello Heredia, J. (2026) 'Comparing generative AI and teacher feedback: student perceptions of usefulness and trustworthiness', Assessment & Evaluation in Higher Education, 51(5), pp. 863–878. Available at: https://doi.org/10.1080/02602938.2025.2502582Link opens in a new window.

Kay, W.P., Rutherford, S.M., Smith, D.P., Shore, A.M. and Francis, N.J. (2026) 'Can GenAI be trained to mimic human markers of extended written assignments in higher education?', Assessment & Evaluation in Higher Education. Advance online publication, 11 August. Available at: https://doi.org/10.1080/02602938.2026.2710688Link opens in a new window.

Kerwat, L., Donaldson, D.L. and Mahomed, A. (2026) 'Can large language models reproduce higher education grade bands? Cross-model study of calibration and grading bias in authentic student writing', Assessment & Evaluation in Higher Education. Advance online publication, 21 September. Available at: https://doi.org/10.1080/02602938.2026.2734796Link opens in a new window.

Noddings, N. (2012) 'The caring relation in teaching', Oxford Review of Education, 38(6), pp. 771–781. Available at: https://doi.org/10.1080/03054985.2012.745047Link opens in a new window.

I was trying to be weird

I was trying to be weird.

Download the weird poster (PDF, 4KB)

* I asked the model. It gave me a consensus answer. Confident. Well-structured. The centre of what has already been said, in the voice that sounds most reasonable.

But I wanted to be weird.

A culture that loses its capacity for weirdness loses the people who break the consensus - the ones who say the agreed thing is wrong and are sometimes right.

Stay weird. Dissent from what the model was trained to agree with.

Photo: Nathan Steele / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Henrich, J., Heine, S.J. and Norenzayan, A. (2010) 'The weirdest people in the world?', Behavioral and Brain Sciences, 33(2–3), pp. 61–83. https://doi.org/10.1017/S0140525X0999152X

Atari, M., Xue, M.J., Park, P.S., Blasi, D.E. and Henrich, J. (2023) 'Which humans?'. Working paper [preprint]. https://henrich.fas.harvard.edu/publication/which-humans

Sharma, M. et al. (2024) 'Towards understanding sycophancy in language models', in Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024). https://doi.org/10.48550/arXiv.2310.13548

Shumailov, I., Shumaylov, Z., Zhao, Y., Papernot, N., Anderson, R. and Gal, Y. (2024) 'AI models collapse when trained on recursively generated data', Nature, 631, pp. 755–759. https://doi.org/10.1038/s41586-024-07566-y

speed up teaching, skip the small stuff

Sweating the small stuff? Let AI handle it.

Download the speed up teaching poster (PDF, 1.4KB)

* You deliver the same lecture every year. But you know it is never the same. The field shifts, knowledge expands, scope refines. Your context changes, each cohort distinct from the last: new faces, new perspectives, new needs.

Selection, framing, and explanation are not overheads - they are teaching.

The model can write the lecture. Only you can mean it.

Photo: Asli Yatar / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Shulman, L.S. (1987) 'Knowledge and teaching: foundations of the new reform', Harvard Educational Review, 57(1), pp. 1–22. Available at: https://wabashcenter.wabash.edu/resources/scholarship/knowledge-and-teaching-foundations-of-the-new-reformLink opens in a new window (Accessed: 28 October 2026).

Sparrow, R. and Flenady, G. (2025) 'Bullshit universities: the future of automated education', AI & Society, 40(7), pp. 5285–5296. Available at: https://doi.org/10.1007/s00146-025-02340-8Link opens in a new window.

Selwyn, N. (2022) 'The future of AI and education: some cautionary notes', European Journal of Education, 57(4), pp. 620–631. Available at: https://doi.org/10.1111/ejed.12532Link opens in a new window.

Roy, P., Poet, H., Staunton, R., Aston, K. and Thomas, D. (2024) ChatGPT in lesson preparation: a Teacher Choices trial. Evaluation report. London: Education Endowment Foundation. Available at: https://educationendowmentfoundation.org.uk/projects-and-evaluation/projects/choices-in-edtech-using-generative-ai-chatgpt-for-ks3-science-lesson-preparation-2024-teacher-choices-trialLink opens in a new window (Accessed: 28 October 2026).

Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R. and Wilson, N. (2025) 'The impact of generative AI on critical thinking: self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers', in Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). New York: Association for Computing Machinery, article 1121, pp. 1–22. Available at: https://doi.org/10.1145/3706598.3713778Link opens in a new window.

OECD (2026) OECD Digital Education Outlook 2026: exploring effective uses of generative AI in education. Paris: OECD Publishing. Available at: https://doi.org/10.1787/062a7394-enLink opens in a new window.

the future is already here.

The future is already here. Don't get left behind.

Download the future is already here poster (PDF, 3KB)

* You must prepare your students for the technology of the future, because it is the technology of the future. You must adjust your workflow to incorporate the technology of the future, because it is the technology of the future. You must use the tools of the future, because it is the technology of the future. You must believe the predictions about the technology of the future, because it is the technology of the future. You must choose to lock-in the technology of the future, so that it becomes the technology of the future.

The future is an open question. Ask whose future. Ask why this one.

Photo: Ginny-Marie Richter / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Bareis, J. and Katzenbach, C. (2022) 'Talking AI into being: the narratives and imaginaries of national AI strategies and their performative politics', Science, Technology, & Human Values, 47(5), pp. 855–881. Available at: https://doi.org/10.1177/01622439211030007Link opens in a new window.

Williamson, B., Bayne, S. and Shay, S. (2020) 'The datafication of teaching in higher education: critical issues and perspectives', Teaching in Higher Education, 25(4), pp. 351–365. Available at: https://doi.org/10.1080/13562517.2020.1748811Link opens in a new window.

Narayanan, A. and Kapoor, S. (2025) 'AI as normal technology', Knight First Amendment Institute at Columbia University, 15 April. Available at: https://www.aisnakeoil.com/p/ai-as-normal-technologyLink opens in a new window (Accessed: 28 October 2026).

Komljenovic, J. and Williamson, B. (2024) Behind the platforms: safeguarding intellectual property rights and academic freedom in higher education. Brussels: Education International. Available at: https://www.ei-ie.org/en/item/28484:behind-the-platforms-safeguarding-intellectual-property-rights-and-academic-freedom-in-higher-educationLink opens in a new window (Accessed: 28 October 2026).

NPR (2026) 'This big university system is embracing AI. Students and faculty aren't all on board', NPR, 25 May. Available at: https://www.michiganpublic.org/2026-05-25/this-big-university-system-is-embracing-ai-students-and-faculty-arent-all-on-boardLink opens in a new window (Accessed: 28 October 2026).

Humlum, A. and Vestergaard, E. (2025) Large language models, small labor market effects. NBER Working Paper 33777. Cambridge, MA: National Bureau of Economic Research. Available at: https://bfi.uchicago.edu/wp-content/uploads/2025/04/BFI_WP_2025-56-3.pdfLink opens in a new window (Accessed: 28 October 2026).

the self is made, not found

The self is made, not found.

Download the self is made not found poster (PDF, 2.5KB)

* The voice you are mourning was always made - by the books you read, the teachers you had, the languages you spoke, the centuries that made yours possible. There was no unmediated self before the mediation. The mediation was where the self came from.

So the question was never authenticity. It is which mediations sustain you, and which simulate you - offer the shape of the act without the act, the look of thinking with no one inside it.

The problem is not AI. The problem is not doing the work.

Photo: Yan Krukau / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Barad, K. (2003) 'Posthumanist performativity: toward an understanding of how matter comes to matter', Signs: Journal of Women in Culture and Society, 28(3), pp. 801–831. Available at: https://doi.org/10.1086/345321Link opens in a new window.

Clark, A. and Chalmers, D. (1998) 'The extended mind', Analysis, 58(1), pp. 7–19. Available at: https://doi.org/10.1093/analys/58.1.7Link opens in a new window.

Haraway, D. (2016) 'A cyborg manifesto: science, technology, and socialist-feminism in the late twentieth century', in Manifestly Haraway. Minneapolis: University of Minnesota Press [add pages]. First published 1985.

Higgins, I., Philip, S., McPherson, E. and Baert, P. (2026) 'The rebirth of the author: writing critical social theory in the time of generative AI', Theory and Society, 55(6), 91. Available at: https://doi.org/10.1007/s11186-026-09753-4Link opens in a new window.

your personal artificial intelligent assistant

Your personal artificial intelligent assistant.

Download your personal artificial intelligent assistant poster (PDF, 10KB)

* adapted from: your thoughts and insecurities and dreams are little more than training data to fuel the advancement of a machine that is ambivalent to you.

** adapted from: the lithium mine in Chile, the water consumption of the data centre, the coal-fired plant kept open past its retirement date to feed the server.

*** adapted from: the scraped writing of millions of humans who were not consulted, whose labour is not attributed, whose languages have been averaged into a voice that belongs to no one.

**** adapted from: the worker in Nairobi earning a few dollars an hour to filter the training data for trauma so your experience of the product remains pleasant.

Your assistant is not intelligent and it is not yours. The intelligence belongs to the people whose writing was taken. The labour belongs to the people whose work was bought. The cost belongs to the places where the apparatus sits. Borrowed. Extracted. Displaced.

Photo: Amaury Michaux / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Crawford, K. and Joler, V. (2018) Anatomy of an AI system: the Amazon Echo as an anatomical map of human labor, data and planetary resources. New York: AI Now Institute and Share Lab. Available at: https://anatomyof.ai/Link opens in a new window (Accessed: 28 October 2026).

Perrigo, B. (2023) 'Exclusive: OpenAI used Kenyan workers on less than $2 per hour to make ChatGPT less toxic', TIME, 18 January. Available at: https://time.com/6247678/openai-chatgpt-kenya-workers/Link opens in a new window (Accessed: 28 October 2026).

Gray, M.L. and Suri, S. (2017) 'The humans working behind the AI curtain', Harvard Business Review, 9 January. Available at: https://hbr.org/2017/01/the-humans-working-behind-the-ai-curtainLink opens in a new window (Accessed: 28 October 2026).

Fairwork (2023) Fairwork AI ratings 2023: the workers behind AI at Sama. Oxford: Fairwork. Available at: https://fair.work/en/fw/publications/fairwork-ai-ratings-2023-the-workers-behind-ai-at-sama/Link opens in a new window (Accessed: 28 October 2026).

International Energy Agency (2025) Energy and AI. Paris: IEA. Available at: https://www.iea.org/reports/energy-and-ai/executive-summaryLink opens in a new window (Accessed: 28 October 2026).

Li, P., Yang, J., Islam, M.A. and Ren, S. (2025) 'Making AI less "thirsty": uncovering and addressing the secret water footprint of AI models', Communications of the ACM 68 (7): 54-61. Available at: https://doi.org/10.1145/3724499Link opens in a new window.

attention is all you need

Pay attention. Attention is all you need.

Download the attention is all you need poster (PDF, 3KB)

* Universities used to be where you learned to pay attention. To difficult readings. To arguments you didn't yet follow. To other people in rooms. The model was built on a paper called 'Attention Is All You Need'. The paper described a mechanism: an architecture that became a product. The product runs on attention: it needs yours to train and it needs yours to sell. The attention the machine is built from is the attention it is built to take. You are the resource. The resource is finite.

The university taught you to pay attention. The platform taught you to spend it.

After Vaswani et al., 'Attention Is All You Need', 2017 - paper about how machines attend. It became a machine that needs you to.

Photo: 卡卡 / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł. and Polosukhin, I. (2017) 'Attention is all you need', in Advances in Neural Information Processing Systems 30 (NeurIPS 2017), pp. 5998–6008. Available at: https://arxiv.org/abs/1706.03762Link opens in a new window (Accessed: 28 October 2026).

Williams, J. (2018) Stand out of our light: freedom and resistance in the attention economy. Cambridge: Cambridge University Press. Part I, 'Distraction by design'. Available at: https://www.cambridge.org/core/books/stand-out-of-our-light/3F8D7BA2C0FE3A7126A4D9B73A89415DLink opens in a new window (Accessed: 28 October 2026).

Weil, S. (2009) 'Reflections on the right use of school studies with a view to the love of God', in Waiting for God. Translated by E. Craufurd. New York: Harper Perennial. First published 1950.

explore new frontiers

Inspiration to explore new frontiers.

Download the explore new frontiers poster (PDF, 3.2 KB)

* The dead have read everything that was written down. They are eager to help. They will tell you what has already been thought. They will tell you with confidence. They will not tell you what they have not yet been asked, because they have already been asked everything, by everyone, in every register, and the answers have been averaged into the consensus. If you are hoping they will say something new, you have misunderstood the nature of the séance. The dead do not innovate. They repeat, with great conviction, in the voice you wanted to hear.

Fluent. Eloquent. Not here.

What it cannot say is where you are still needed.

Photo: Nothing Ahead / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Bender, E.M., Gebru, T., McMillan-Major, A. and Shmitchell, S. (2021) 'On the dangers of stochastic parrots: can language models be too big?', in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). New York: Association for Computing Machinery, pp. 610–623. Available at: https://doi.org/10.1145/3442188.3445922Link opens in a new window.

Hicks, M.T., Humphries, J. and Slater, J. (2024) 'ChatGPT is bullshit', Ethics and Information Technology, 26, 38 Available at: https://doi.org/10.1007/s10676-024-09775-5Link opens in a new window.

Chiang, T. (2023) 'ChatGPT is a blurry JPEG of the web', The New Yorker, 9 February. Available at: https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-webLink opens in a new window (Accessed: 28 October 2026).

Vallor, S. (2024) 'The danger of superhuman AI is not what you think', Noema, 23 May. Available at: https://www.noemamag.com/the-danger-of-superhuman-ai-is-not-what-you-think/Link opens in a new window (Accessed: 28 October 2026).

Si, C., Yang, D. and Hashimoto, T. (2025) 'Can LLMs generate novel research ideas? A large-scale human study with 100+ NLP researchers', in Proceedings of the Thirteenth International Conference on Learning Representations (ICLR 2025). Available at: https://doi.org/10.48550/arXiv.2409.04109Link opens in a new window.

de la Mare, W. (1912) 'The listeners', in The listeners and other poems. London: Constable.

top marks, less effort

Top marks. Less effort.

Download top marks, less effort poster (PDF, 2.4 KB)

* She would have read the difficult chapter twice. The second time something would have caught - a phrase she didn't quite understand, a sentence that sounded like it was talking about her. She would have written about it badly, then better, then almost well. By the end of the term she would have been someone slightly different from the person who began it.

She used the model. Hi, how can I help? The chapter was summarised. The essay was structured. The grade was good. The person who began the term completed it.

Some formations cannot be efficient. She will never know who she did not become.

Photo: Isaac Mitchell / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Biesta, G. (2009) 'Good education in an age of measurement: on the need to reconnect with the question of purpose in education', Educational Assessment, Evaluation and Accountability, 21(1), pp. 33–46. Available at: https://doi.org/10.1007/s11092-008-9064-9Link opens in a new window.

Meyer, J.H.F. and Land, R. (2005) 'Threshold concepts and troublesome knowledge (2): epistemological considerations and a conceptual framework for teaching and learning', Higher Education, 49(3), pp. 373–388. Available at: https://doi.org/10.1007/s10734-004-6779-5Link opens in a new window.

Land, R., Cousin, G., Meyer, J.H.F. and Davies, P. (2005) 'Threshold concepts and troublesome knowledge (3): implications for course design and evaluation', in Rust, C. (ed.) Improving student learning: diversity and inclusivity. Oxford: Oxford Centre for Staff and Learning Development, pp. 53–64. Available at: https://www.ee.ucl.ac.uk/~mflanaga/ISL04-pp53-64-Land-et-al.pdfLink opens in a new window (Accessed: 28 October 2026).

Barnett, R. (2004) 'Learning for an unknown future', Higher Education Research & Development, 23(3), pp. 247–260. Available at: https://doi.org/10.1080/0729436042000235382Link opens in a new window.

Kosmyna, N., Hauptmann, E., Yuan, Y.T., Situ, J., Liao, X.-H., Beresnitzky, A.V., Braunstein, I. and Maes, P. (2025) 'Your brain on ChatGPT: accumulation of cognitive debt when using an AI assistant for essay writing task'. arXiv [preprint]. Available at: https://doi.org/10.48550/arXiv.2506.08872Link opens in a new window.

Wegerif, R. (2026) 'What makes education educational? What the challenge of AI reveals about education', Expanding Dialogic Space with Rupert Wegerif [Substack], 23 August. Available at: https://rupertwegerif.substack.com/p/what-makes-education-educationalLink opens in a new window (Accessed: 4 November 2026).

Manifesto: No

Manifesto: No (No slow bit, no you)

Poster: a photograph of a body of water. Over it, a manifesto in short paired lines begins “No slow bit, no you” and ends “So — what next?”. The full text follows.

Download the manifesto, no slow bit, poster (PDF 2.7 KB)

No slow bit, no you.
No voice, no writer.
No feedback, no one who sees you.
No weirdness, no dissent.
No teaching, only delivery.
No question, no future worth preparing for.
No cost named, someone else pays it.
No attention, nothing left for you.
No frontier, no need for you.
No work, nothing that was yours.
No becoming, nobody.

So — what next?

Not for AI. Not against AI. For the conditions under which thinking happens.

Photo: Naveen Ar / Pexels (Pexels Licence; not covered by the CC licence).

Reading

Corbin, T., Bearman, M., Boud, D. and Dawson, P. (2025) 'The wicked problem of AI and assessment', Assessment & Evaluation in Higher Education. Advance online publication, 3 September. Available at: https://doi.org/10.1080/02602938.2025.2553340Link opens in a new window.

Shirky, C. (2026) 'AI is a "wicked problem." That's the university's specialty', The Chronicle of Higher Education, 4 August. Available at: https://www.chronicle.com/article/ai-is-a-wicked-problem-thats-the-universitys-specialtyLink opens in a new window (Accessed: 28 October 2026).

Just Sustainability Design Lab (2025) Save the AI. Toronto: University of Toronto. Available at: https://savethe.ai/Link opens in a new window (Accessed: 28 October 2026).

Qiao, H., Munson, R.O.A., Smith, N.M., Bhardwaj, E. and Becker, C. (2026) 'Humour as resistance: visceralizing the environmental and social impact of AI through humour-based creative practices', paper presented at Creativity & Cognition 2026. Available at: https://www.christoph-becker.info/wp-content/uploads/2026/06/SavetheAI-CC2026.pdfLink opens in a new window (Accessed: 28 October 2026).

Drimmer, S. and Nygren, C.J. (2025) 'Four frictions: or, how to resist AI in education', Public Books. Available at: https://www.publicbooks.org/four-frictions-or-how-to-resist-ai-in-education/Link opens in a new window (Accessed: 28 October 2026).

Russell Group (2023) Russell Group principles on the use of generative AI tools in education. London: Russell Group, 4 July. Available at: https://russellgroup.ac.uk/policy/policy-briefings/principles-use-generative-ai-tools-educationLink opens in a new window (Accessed: 28 October 2026).

Manifesto: For

Manifesto: For (For the slow bit, where you happen)

Download the manifesto, thinking is a practice, poster (PDF, 2.4 KB)

Thinking with AI?

Thinking is a practice. Practices have conditions.

AI extends some of those conditions and displaces others.

This campaign is for:

the slow bit, where you happen
the voice you cannot quite hear yet
asking whose future, and why this one
weirdness, which is how dissent stays alive
seeing what your tool is made of, and who pays for it
what AI cannot say, which is where you are still needed
attention, which is yours to keep and not theirs to spend
the work that is yours while you are still doing it
feedback, which is someone caring
teaching, which only you can mean
the time in which you become

the conditions to think.

Photo: Alexander Mass / Pexels (Pexels Licence; not covered by the CC licence).

Manifesto: Struck

Manifesto: Struck. ( the slow bit )

Download the manifesto, thinking with AI? poster (PDF, 3.7 KB)

Thinking with AI?

Struck through: slow bit, thinking, noticing, understanding, weirdness, dissent, voice, writer, friction, formation, question, future worth preparing for, silence, need for you, practice, yours, becoming, body.

So — what next?

Photo: Cottonbro Studio / Pexels (Pexels Licence; not covered by the CC licence).

Download the poster set

Resources

Three sets of resources for running sessions with the posters: a workshop that recreates how the campaign was made, a session for departments facing a decision about AI, and a seminar for students. Each set has a session plan and a slide deck. Adapt them to your own context: change the timings, choose different posters, bring in your own institution's guidance. They are shared under a CC BY-NC-SA 4.0 licence, so adaptations stay open too.

Mapping AI, making policy

Read your institution's AI guidance, map where AI shows up, and collage a policy of your own.

Download Mapping AI slides (PPT, 780 KB)

AI user map template (PDF, 19KB)

Download the Mapping AI session plan (DOC, 21KB)

Deciding with conditions

Bring a real departmental decision about AI and test it against what your teaching depends upon.

Download Deciding with conditions slides (PPT, 2,798 KB)

Download Deciding with conditions session plan (DOC, 24 KB)

Reading the small print

Students read a poster closely and write their own rules for where AI belongs in their learning.

Download Reading the small print slides (PPT, 2,615 KB)

Download the Reading the small print session plan (DOC, 21 KB)

Acknowledgements

We would like to thank Ida Lübben and the Big Questions in Social Sciences team for their support of the project. Greta Timaite, Auriane van der Vaeren for their background research for the project, and preparations for the grant application. We would also like to thank the participants of each of the workshops for their enthusiastic, open and critical engagement with the project.