Automated and Emerging Technologies · 4 question types
Past paper frequency (2018 to 2024)
This topic accounts for approximately 4% of your exam marks.
AI applications and machine learning concepts are growing in exam prominence.
Artificial intelligence (AI) is the area of computer science focused on building machines whose behaviour mimics human intelligence.
An AI system is one that can do three things:
| Capability | What it means |
|---|---|
| Learn | Take in new information and update its behaviour based on what it has seen |
| Decide | Analyse a situation and choose between alternative actions |
| Act autonomously | Carry out chosen actions without needing a human to step in for each one |
A system that does all three (gathers information, makes its own decisions, and acts on them) qualifies as AI. A pocket calculator does not qualify: it cannot learn, and every "decision" follows a fixed rule the user typed in. A modern chess engine does qualify: it analyses positions, weighs alternatives, learns from training games, and plays its own moves.
Mark-scheme phrasing: the three CIE-approved verbs are learn, decide and act autonomously. Use those exact words for full marks; vague phrases like "AI is a clever computer" do not score.
AI is usually split into two big categories:
| Narrow AI (also called weak AI) | General AI (also called strong AI or AGI) | |
|---|---|---|
| Scope | Built to handle a single defined task (or a tight group of related tasks) | Built to perform any intellectual task a human can do |
| Does it exist today? | Yes, in many products | No; it remains a research goal |
| Examples | Chess engines, voice assistants, image recognisers, recommendation systems, self-driving cars | Hypothetical: a machine with full human-level intelligence across every domain |
Every AI system you can interact with today is narrow. Even very impressive systems (chat assistants, image generators, AlphaGo) are highly specialised, just on a wider task than older AIs.