Responsible AI Use for Students: Use It or Lose It

I am so embarrassed.

I am horrified to say that I have lost the ability to do a very basic skill.

I was at a friend's house playing Flip 7, a card game where you add up your points at the end of each round and the first person to reach 200 wins. I volunteered to be the scribe and keep track of everyone's scores, which I very quickly regretted.

I found myself staring at a page of very simple addition and my brain was frozen.

Everyone was waiting for me, I was getting hot and flustered, and the monkey clapping the cymbals in my head was nowhere to be found.

This was especially horrifying because I was actually very good at maths. I did Specialist Maths, the highest level of maths in Year 12. I was good at it.

But for more than a decade, I've had calculators, spreadsheets and my phone doing that work for me.

And because I haven't practised the skill, I've lost a huge amount of it.

Sorry Mrs Condo if you're reading this.

It made me think about AI.

What happens when we stop practising a skill?

My embarrassing card game experience made me think about something I believe we need to talk about more when we talk about AI and education.

What happens when we regularly outsource parts of our thinking and work to technology?

My basic maths skills didn't disappear overnight. I simply stopped using them.

When a calculator is always available, there isn't much reason to practise doing calculations in your head. When a spreadsheet can handle the numbers, you don't need to work them out yourself.

That is incredibly useful.

But there is a trade-off.

If you stop practising a skill, you can become less confident and less capable at using it.

The same principle matters when we think about responsible AI use for students.

AI can help students, but it can also remove practice

AI can make us faster and more efficient.

There are plenty of tasks where that is genuinely useful.

But students are in a different position from adults who are using technology to make an existing skill more efficient.

Students are still developing many of the skills they will need throughout their lives.

Writing.

Researching.

Forming an argument.

Solving problems.

Analysing information.

Working through something difficult.

Sitting with confusion and trying to work something out for yourself.

These are skills that need to be built and then continually practised.

If AI does the hard part before a student has properly developed the skill, the student may miss an important opportunity to learn.

The problem with outsourcing the thinking

Imagine a student is learning how to write an argument.

They could use AI to generate the entire structure, provide the arguments, find the evidence and write the final response.

The finished piece might be excellent.

But what did the student actually practise?

They may have practised reading the AI's response.

They may have edited a few sentences.

But they haven't necessarily practised forming their own argument.

The same thing can happen with research.

Or problem-solving.

Or analysing information.

Or writing.

Or studying.

This is why AI literacy needs to be more than teaching students how to use AI tools.

Students need to understand what happens when they hand a task over to AI.

Responsible AI use means knowing what not to outsource

A useful question for students is:

What skill am I supposed to be practising here?

Before using AI, students can think about the purpose of the task.

If the purpose is to practise writing, having AI write the first draft may remove much of the practice.

If the purpose is to understand a difficult concept, asking AI to explain it in a different way could be genuinely helpful.

If the purpose is to practise solving problems, getting AI to provide every answer might defeat the purpose.

The same technology can therefore be helpful in one situation and unhelpful in another.

That is an important part of responsible AI use for students.

AI literacy needs to include the value of effort

We often talk about AI as a way to make work faster and easier.

But faster and easier aren't always the goals.

Sometimes the effort is the point.

Students need opportunities to struggle with a difficult problem.

They need to write things themselves.

They need to practise remembering information.

They need to make mistakes.

They need to work out why something doesn't make sense.

They need to sit with confusion instead of immediately asking a tool to solve it for them.

That doesn't mean students should never use AI.

It means they need to understand when the more effortful route is actually the more valuable one.

What should schools teach students about AI and learning?

Schools don't necessarily need to tell students that AI is bad or that they should never use it.

Instead, students need a more nuanced understanding of how AI can affect their learning.

A useful AI literacy conversation could include questions such as:

What am I trying to learn?

Students need to understand the purpose of a task before deciding whether AI will help.

What part of this task is the practice?

Sometimes the process matters more than the final product.

If the task is designed to build a particular skill, students need to recognise which part of the process they need to do themselves.

Am I using AI to support my thinking or replace it?

There is a significant difference between asking AI for another explanation and asking it to do all the thinking.

Will I still be able to do this without AI?

This is the question I keep coming back to.

If students increasingly rely on AI for writing, research, problem-solving and analysis, they need to think about whether they are still developing those abilities themselves.

It really is a case of use it or lose it

My Flip 7 experience was a fairly harmless reminder of what happens when you stop practising something.

I can reach for a calculator.

I can use a spreadsheet.

I can ask my phone to do the maths.

And now, increasingly, I can ask AI to do many other things for me too.

The convenience is fantastic.

But there are some skills I still want to be able to do myself.

That is the conversation I think we need to have with students.

AI can make us faster and more efficient, and there are plenty of tasks that make sense to outsource.

But every time we hand something over to AI, we should also ask whether we're giving up an opportunity to practise a skill we still want to have.

For students, that question is particularly important.

Responsible AI use isn't about avoiding AI altogether. It's about understanding when AI supports learning and when it gets in the way of it.

Sometimes, choosing the harder route is actually the smarter choice.

And sometimes, you really do need to use it before you lose it.