| By Mike Bindon |
The year has begun with multiple international news stories about politicians, government officials, and public figures being “caught” using artificial intelligence.
I find that language fascinating.Not because AI use is surprising, it isn’t, but because of what the phrase “caught using” actually implies. It suggests wrongdoing without context, collapses very different actions into a single moral judgement, and feeds a narrative of suspicion rather than clarity. It also mirrors, almost perfectly, the tension many teachers are currently navigating in classrooms.
Across schools, unclear or inconsistent AI policies have muddied an essential distinction: there is a significant difference between using AI and using AI inappropriately, unethically, or without transparency. When that distinction is lost, the messaging becomes damaging.
Assessment pressure and the quiet rise of policing
For many arts teachers, this is not an abstract concern. Assessment systems, external moderation, and leadership expectations mean that teachers are increasingly being asked to act as gatekeepers of academic integrity, often without clear policies or shared understanding of what appropriate AI use actually looks like. In some contexts, this has quietly turned arts educators into de facto AI police, responsible for detecting misuse in disciplines where learning is embodied, process-based, and collaborative. This pressure is real, and it is deeply misaligned with how artistic learning is best observed, assessed, and supported.
In the arts, integrity is not best protected through forensic analysis of outputs, but through task design, visible process, and professional judgement. These are areas where arts educators already have deep expertise.
When assessment systems move slowly
At the same time, it is important to acknowledge the wider system in which teachers are working. Assessment bodies, by necessity, are often the slowest to adapt. Large curriculum and assessment frameworks take years to review, revise, consult on, and publish. School leaders, understandably, often wait for clear signalling from these bodies before making decisive changes to policy.
In the meantime, it is classroom teachers, particularly in the arts, who are caught between two realities. On one side sit fixed assessment structures and policies that were never designed with AI in mind. On the other is a world in which students see AI being used openly, efficiently, and effectively to get things done, in higher education, in creative industries, and by adults around them, including their own teachers. When policy lags behind practice, students are penalised not for acting unethically, but for navigating a system that has not yet caught up with itself.
Where AI does belong in arts education
This does not mean that anything goes.
AI can be completely acceptable, and genuinely valuable, when used appropriately. In arts education, AI can support ideation, offering starting points, provocations, and alternative possibilities to explore. It can assist with visualisation, particularly in theatre, film, and design contexts where students may struggle to communicate ideas through drawing or notation. It can widen access through translation and multimodal support, and it can provide material to critique, challenge, or reject as part of the creative process.
What AI must not do is replace interpretation, judgement, performance, or meaning-making. These remain human responsibilities.
The real solution: clarity, not surveillance
The solution, then, is not to wait passively for systems to catch up, and it is not to double down on surveillance.
The solution is clarity.
Clear distinctions between acceptable and unacceptable use. Clear expectations around transparency, attribution, and process. Clear task design that values decision-making, iteration, and embodied learning over polish alone. And clear professional trust in teachers’ judgement, particularly in the arts, where learning is visible, collaborative, and deeply human.
Arts educators do not need to abandon integrity in order to engage with AI. Nor do they need to pretend that AI does not exist until assessment frameworks evolve. What they need is permission — and support — to lead responsibly in the present, while larger systems adapt more slowly around them.
If we can shift the conversation from “caught using AI” to “using AI appropriately, ethically, and transparently in service of learning”, we create space for honesty rather than fear, and for education rather than enforcement.
That shift will not come from technology alone.
It will come from professional judgement, thoughtful pedagogy, and leadership that understands how learning actually happens in the arts.
