AI literacy · Digital citizenship
AI literacy includes the rules
AI literacy is usually described as understanding what AI systems can do, how they work and how to use them critically. This page argues for the missing quarter: understanding the rules that govern them — and shows how to teach it.
AI literacy is the ability to understand how AI systems work, where they are used and how they are governed — and that includes knowing the basic logic of the EU AI Act. This page explains why regulation literacy is part of AI literacy and digital citizenship, and how scenario-based learning helps. It states plainly what the serious game can and cannot teach.
01What AI literacy means
Frameworks from bodies such as UNESCO and the OECD converge on a few competences: a basic grasp of how AI systems work, the ability to use them effectively, and the judgment to question their outputs and effects.
In practice: knowing that a model predicts rather than knows; recognising where automated systems shape your options; and asking who benefits, who is affected and who is accountable.
02Why regulation literacy belongs in AI literacy
A citizen who understands embeddings but not their rights in front of an automated rejection is only half-literate. The EU AI Act encodes society's current answers to the hard questions — which uses are unacceptable, which demand safeguards, when people must be informed.
Regulation literacy does not mean memorising articles. It means knowing that a risk-based framework exists, roughly how it sorts systems, and which questions it entitles you to ask.
03The digital citizenship connection
Rights and responsibilities around automated systems are civic matter: contestability of decisions, transparency about machine interaction, accountability of institutions that deploy AI. That is the territory of digital citizenship and AI regulation.
04Why scenario-based learning works here
Rules stick when they are needed, not when they are listed. Scenario-based learning puts the learner inside a situation — an opaque hiring filter, a scored neighbourhood — where the regulation's concepts become tools rather than trivia. The full argument is in serious games for AI regulation.
NO AI ACT applies this: in the game you classify 13 systems from evidence, and every concept — deployer, oversight, transparency — earns its place by being used.
05What a game can and cannot teach
- Can: the risk-based logic, the habit of evidence-grounded classification, the vocabulary in context, the sense that context of use changes everything.
- Cannot: the actual legal text, jurisprudence, compliance procedure, or anything requiring professional judgment. A simulation motivates and structures; it does not replace study — see the guide and glossary for the next layer.