Students are worried about how their peers are using AI.
Yesterday, I asked a group of Year 11–12 students in Bunbury what they thought about students using AI in education.
Their biggest concern?
That many of their friends understand almost nothing about the technology they are already using.
These weren't students who had simply heard a few things about AI. They were passionate young people who had done a lot of their own research into the technology, and they were genuinely worried about their peers.
What they told me was a good reminder that AI literacy for students needs to be much bigger than teaching them how to use a chatbot.
What are students concerned about when it comes to AI?
The students I spoke to raised several different concerns about the way their peers are using AI.
They talked about students not knowing where their data goes when they use AI.
They raised the environmental impact of generative AI.
They talked about the ethical questions around how AI models are trained.
But the thing they kept coming back to was thinking.
They are worried about young people outsourcing their thinking to AI before they have developed the critical thinking, reasoning and analysis skills to know whether what the AI is giving them is actually any good.
That concern is worth listening to.
Students are worried about outsourcing their thinking
One student articulated it so clearly:
“AI literacy has to be more than teaching students how to use AI chatbots.”
I think they're right.
A student can learn how to write a prompt in a matter of minutes.
That doesn't necessarily mean they understand what the AI is doing.
They might not know why it produces a particular answer. They might not know that it can confidently provide incorrect information. They might not know what information they are sharing with the system or what happens to that data.
And they may not have developed the skills to evaluate whether the answer they have received is actually any good.
This is where AI literacy and critical thinking need to come together.
What should AI literacy for students actually include?
If AI is sticking around, and it certainly looks like it is, teaching students how to prompt a chatbot isn't enough.
Students need a much broader understanding of the technology they are using.
How AI works
Students don't need to become computer scientists.
But they do need a basic understanding of how generative AI systems work and why they can produce answers that sound convincing without necessarily being accurate.
Understanding this helps students move away from treating AI as a source of unquestionable answers.
How to question AI outputs
Students need to know that an AI-generated answer is a starting point, not automatically a fact.
They need to ask:
Does this make sense?
Could this be wrong?
How could I check it?
What evidence supports this?
Is there another perspective?
What does the AI leave out?
These are critical thinking skills that students need whether they are using AI or not.
What happens to their data
Students are already entering information into AI systems.
They need to understand that what they type into a tool can have privacy implications.
AI literacy should include conversations about personal information, privacy and the kinds of information students should think carefully about sharing with AI.
The ethical questions around AI
The students I spoke to weren't only interested in what AI can do.
They were interested in how it is made and the questions that come with it.
How are AI models trained?
What data is used?
Whose work is included?
What biases might be reflected in the technology?
These aren't questions that students need to solve themselves.
But they are questions they should know how to ask.
The environmental impact
Generative AI also comes with environmental considerations, including the energy and resources required to develop and operate AI systems.
Students raised this themselves.
That is important because responsible AI use isn't simply about whether a tool is convenient or useful.
Students should also be able to think about the wider consequences of the technologies they use.
When should students use AI and when should they do the thinking themselves?
This might be one of the most important questions schools can help students work through.
There are situations where AI can be genuinely useful.
It can help students brainstorm, explain a difficult concept, generate ideas or provide another way of approaching a problem.
But there are also times when using AI too early can remove the learning opportunity.
If a student asks AI to analyse a text before they have attempted the analysis themselves, they may never develop the ability to do that analysis independently.
If they ask AI to solve every problem, they can miss the process of working out how to solve it.
If they automatically accept the AI's explanation, they may never learn to question it.
The question isn't simply whether students are using AI.
We need to think about how, why and when they are using it.
Young people already know this is a problem
One thing I found particularly interesting about this conversation was that the concern wasn't coming from adults telling students how they should behave.
It was coming from students themselves.
These young people were looking at what their peers were doing and saying, essentially, we need to understand this better.
They weren't necessarily calling for AI to disappear.
They recognised that AI is becoming part of education and that it is unlikely to simply go away.
What they wanted was better understanding.
They wanted their peers to know what they were actually using.
That is an important distinction for schools.
AI education in schools needs to listen to students
When we design AI education, it is easy to focus on what adults think students need to know.
Teachers might be thinking about academic integrity.
School leaders might be thinking about appropriate use policies.
Parents might be thinking about safety.
All of those things matter.
But students have a perspective too.
They are the ones using these technologies every day.
They are seeing how their friends are using them.
And some of them are already thinking deeply about the consequences.
We should listen to them.
AI literacy is about understanding, not just using
For me, good AI literacy for students means giving young people the knowledge and critical thinking skills to make informed decisions about AI.
That includes understanding how the technology works, questioning its outputs, protecting their data and considering the ethical and environmental trade-offs.
It also means helping students recognise when AI is useful and when they are better off doing the thinking themselves.
Teaching students how to prompt is one small part of that.
It shouldn't be the whole lesson.
The students who understand this technology are telling us they want their peers to understand it too.
We should listen.
If your school is looking at how to build practical AI literacy into education, my AI literacy workshops for schools help students explore how AI works, how to question its outputs and how to use it thoughtfully. Programs such as Think Before You Prompt can help schools move the conversation beyond simply teaching students how to use AI tools.
