Why Citizenship is the best subject to demonstrate AI

Citizenship and Social Development values evidence-based judgement and analysis from several angles. The EDB's AI for Empowering Learning and Teaching Funding Programme asks for AI-assisted teaching in at least three subjects, and Citizenship is one of the most worthwhile to include: the contested issues it deals with often involve numbers, legislation and the sequence of events, which are exactly where generative AI most easily goes wrong, and where students most need to tell what is true.

Three steps for issue inquiry

One approach you can adopt straight away is to embed AI in a structured issue inquiry, rather than letting students ask their way to a conclusion in one go.

  • One, gather positions: on a contested issue (say municipal solid waste charging, or an opt-out default for organ donation), have students use AI to list the main arguments for and against, building a full picture of the issue quickly
  • Two, check point by point: for every argument AI puts forward, students must verify it against sources other than AI, including government statistics, news reports, official documents or academic material, and note the source
  • Three, form a position: students build their own position only after checking, and write it up as a paragraph backed by sources; any AI argument with no independent source to support it is dropped

One classroom rule: AI output cannot count as a source

The whole approach rests on one rule: content generated by AI cannot itself be cited as a source. Students may use AI to draft, to lay things out, and to find leads, but in the argument they hand in, every fact and figure has to point to an original source that can be checked. This rule hands responsibility back to the student: what AI said does not matter; whether you can verify it does.

It also settles the most common worry in Citizenship, that students take AI-generated content as established fact and copy it straight into their work. Generative AI can produce content that reads smoothly yet does not match the facts, so writing verification into the classroom rule means that every time students run an inquiry, they practise fact-checking once more.

Extending to commentary writing and debate

The same logic extends to commentary writing and classroom debate. For commentary writing, students first use AI to generate a draft commentary with a clear stance, then play the role of fact-checker, marking sentence by sentence which parts are verifiable facts, which are opinion, and which are claims with no evidence behind them, and rewrite on that basis. Students find that AI writes fluently but often makes opinion read like fact.

For debate, AI can help students prepare the arguments the other side might raise, making their preparation more thorough; but every piece of evidence cited on the day has to come from an independent source that has been checked. AI widens the view, while the responsibility for evidence still sits with the student.

Turning inquiry into evidence for the report

These lessons readily grow into the teaching demonstration examples the programme asks for, and they can also count towards student AI literacy activities. For each issue inquiry, keep a few things consistently: the issue and the learning goals, the student's verification record (AI arguments set against independent sources), the final argument or commentary piece, and a short reflection noting whether the student's view on whether AI's answers can be trusted has changed. Design the format once and use it across the whole year group; when it comes to writing the interim and final reports, the Citizenship part will have real work and finished pieces ready to submit.