GenAI is often presented to academics as a tool for acceleration. Marking can be automated, lecture slides summarised in seconds and drafts polished at speed. The message is clear: do the same work, only faster. Yet, this framing risks reinforcing an already unsustainable level of efficiency.
What if, instead of speeding up, GenAI could help us slow down? Used thoughtfully, these tools can encourage reflection, deepen dialogue and make space for richer connections between research and teaching. Slowness here is not inefficiency. Instead, it is the deliberate act of reclaiming attention for what matters most: curiosity, questioning and collaboration.
Why slowing down matters
In higher education, the pressure to produce more with less is unrelenting. Staff are encouraged to juggle research, teaching and administration, while students navigate overloaded curricula and the constant churn of assessment. Against this backdrop, it’s unsurprising that time-saving features are marketed as GenAI’s greatest value.
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But acceleration has a cost. When we prize efficiency above all else, we risk flattening inquiry into delivery. We leave little space for students to inhabit research as a process, and little time for staff to reflect on how their own scholarship and teaching intersect.
Slowing down with GenAI can counterbalance this culture. It doesn’t reject efficiency but reframes it. Time “saved” is not the end goal. Instead, that time is reinvested into dialogue, exploration and meaningful connections between research and teaching.
Slow AI in practice
The teaching-research nexus is often spoken of in abstract terms, but it becomes tangible when we involve students in scholarly habits of questioning and reflection. AI can support this, provided we resist the temptation to use it only for shortcuts.
For example, in my own teaching, I’ve used AI to generate alternative perspectives on scientific concepts. Rather than asking for a quick summary of a paper, I invite the tool to propose counter-questions that a critical reader might raise. Students can then discuss these prompts in small groups, identifying which they find most compelling and why. This simple exercise doesn’t speed up the class but it does deepen the conversation.
Similarly, when mentoring early career researchers, I’ve encouraged them to use AI not to streamline their writing but to surface hidden assumptions. By pasting a draft paragraph into an AI tool and asking it to highlight biases or unstated perspectives, they slow down to consider the choices they’re making as writers. This process shifts from editing for speed to reflecting on voice and stance.
Three prompt recipes to try
Here are three specific exercises that you can adapt for your own teaching or research practice. They’re designed not to make things quicker but to cultivate slowness, attention and dialogue.
1. The ‘second look’ prompt
- Paste a short section of your own writing, such as a lecture explanation or a research abstract.
- Ask: What is one subtle assumption or bias in this text that I might not have noticed?
- Share the output with colleagues or students and reflect together.
Why it helps: We all carry blind spots into our work. This prompt slows us down by encouraging critical reflection on how we frame knowledge, and it opens opportunities for collaborative revision.
2. The ‘counter-question’ prompt
- After presenting a concept in class, paste your notes into the tool.
- Ask: If a thoughtful student wanted to challenge this idea, what counter-question might they ask?
- Bring these counter-questions back into discussion or use them as starting points for seminar debate.
Why it helps: Instead of speeding through slides, this prompt invites students into the role of co-inquirers. It slows the pace of teaching to focus on dialogue, strengthening the link between research and teaching by modelling how scholars manage critique.
3. The ‘slow summary’ prompt
- Paste the abstract of an article you’re assigning for reading.
- Ask: Summarise this article in 100 words but frame it as an open research question that students could explore further.
- Use the result to design seminar discussions or assignments.
Why it helps: Summarisation becomes a tool, not for faster reading, but for sparking inquiry. It helps students see research not as a finished product but as an ongoing conversation they can join.
Building a culture of slowness
These prompts aren’t time-intensive. Each takes only a few minutes to try. What matters is the shift in mindset they encourage: away from AI as an accelerator of tasks, towards AI as a collaborator in reflective practice.
This is not only useful for classroom teaching. It also offers a model for bridging scholarship and practice more broadly. By building slowness into our engagement with AI, we’re better placed to integrate research into learning in ways that are authentic, critical and collaborative.
If you want to experiment with Slow AI in your own work, start small. Choose one prompt recipe and test it in your next seminar or supervision meeting. Notice what shifts when the focus is not speed, but reflection.
You can also find weekly creative prompts and community reflections at Slow AI, a newsletter dedicated to exploring how these tools can help us pause, notice and engage more deeply.
Slowing down with AI may feel counterintuitive in a sector obsessed with speed but it’s exactly this change of pace that lets us reclaim curiosity, questioning and collaboration as the heart of higher education.
Sam Illingworth is professor of creative pedagogies at Edinburgh Napier University and author of Bridging Scholarship and Practice in Higher Education. His work focuses on using AI and poetry to help explore staff and student belonging. GenAI was used in the writing of this article, to optimise some of the prompts and sense check the argument of the piece.
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