6.3

Artificial Intelligence

Cambridge IGCSE Computer Science (0478)  · Unit 6: Automated and emerging technologies  · 9 flashcards

Artificial Intelligence is topic 6.3 in the Cambridge IGCSE Computer Science (0478) syllabus , positioned in Unit 6 — Automated and emerging technologies , alongside Automated systems and Robotics.  In one line: AI is the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction.

This topic is examined in Paper 1 (computer systems theory) and Paper 2 (algorithms, programming and logic).

The deck below contains 9 flashcards — 4 definitions, 3 key concepts and 2 application cards — covering the precise wording mark schemes reward.  Use the 4 definition cards to lock down command-word answers (define, state), then move on to the concept and application cards to handle explain, describe and compare questions.

Key definition

Artificial Intelligence (AI)

AI is the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction.

Example: a self-driving car uses AI to navigate.

What the Cambridge 0478 syllabus says

2026-2028 syllabus, in our words

What the syllabus expects you to be able to do in this topic, in plain English. Match the command word (Describe, Explain, State, etc.) in your answer to score full marks. For the exact wording, see the official syllabus (PDF).

  1. Understand Understand what the term artificial intelligence (AI) means.
  2. Describe Describe the key features of AI: it collects data and applies rules for using that data, it can reason, and it may also be able to learn and adapt.
  3. Explain Explain the basic workings and parts of AI systems that mimic intelligent behaviour, covering machine learning and expert systems (with their interface, inference engine, knowledge base and rule base).
Definition Flip

Define Artificial Intelligence (AI).

Answer Flip

AI is the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction.

Example: a self-driving car uses AI to navigate.
Key Concept Flip

Explain the concept of Machine Learning.

Answer Flip

Machine learning is a type of AI that allows systems to learn from data without being explicitly programmed.

Example: a spam filter learns to identify spam emails based on patterns in the emails it has already processed.
Definition Flip

Describe the structure and function of a neural network.

Answer Flip

A neural network is a computational model inspired by the structure of the human brain, consisting of interconnected nodes (neurons) organized in layers. It learns by adjusting the connections between these nodes.

Example: image recognition software might use a neural network.
Definition Flip

What is an expert system and how does it work?

Answer Flip

An expert system is a computer program that emulates the decision-making ability of a human expert. It uses a knowledge base and inference engine to provide advice or solutions.

Example: a medical diagnosis system.
Definition Flip

Explain the purpose of Natural Language Processing (NLP).

Answer Flip

NLP enables computers to understand, interpret, and generate human language. This allows interaction between humans and computers in a natural way.

Example: voice assistants such as Siri or Alexa use NLP.
Key Concept Flip

Describe how a chatbot uses AI.

Answer Flip

Chatbots use AI, particularly NLP and machine learning, to understand user input and provide relevant responses. They learn from previous conversations to improve their understanding. A common example is a customer service chatbot on a website.

Key Concept Flip

Give an example of a real-world application of AI in healthcare.

Answer Flip

AI is used in healthcare to analyze medical images (X-rays, MRIs) for faster and more accurate diagnoses. It can also assist in drug discovery and personalized treatment plans.

Example: AI is used to detect tumors in medical scans.
Key Concept Flip

Explain the difference between supervised and unsupervised learning.

Answer Flip

Supervised learning uses labeled data to train a model to predict outcomes. Unsupervised learning uses unlabeled data to find patterns and relationships. An example of supervised learning is classifying images, while unsupervised learning might be grouping customers based on purchasing behavior.

Key Concept Flip

Outline the potential ethical concerns related to the use of AI.

Answer Flip

Ethical concerns include job displacement due to automation, bias in algorithms leading to unfair outcomes, and privacy concerns related to data collection. It's important to consider these implications to ensure AI is used responsibly.

Review the material

Read revision notes with definitions, equations, and exam tips.

Read Notes
6.2 Robotics 7.1 Algorithm design

Key Questions: Artificial Intelligence

Define Artificial Intelligence (AI).

AI is the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction.

Example: a self-driving car uses AI to navigate.
Describe the structure and function of a neural network.

A neural network is a computational model inspired by the structure of the human brain, consisting of interconnected nodes (neurons) organized in layers. It learns by adjusting the connections between these nodes.

Example: image recognition software might use a neural network.
What is an expert system and how does it work?

An expert system is a computer program that emulates the decision-making ability of a human expert. It uses a knowledge base and inference engine to provide advice or solutions.

Example: a medical diagnosis system.
Explain the purpose of Natural Language Processing (NLP).

NLP enables computers to understand, interpret, and generate human language. This allows interaction between humans and computers in a natural way.

Example: voice assistants such as Siri or Alexa use NLP.

More topics in Unit 6 — Automated and emerging technologies

Artificial Intelligence sits alongside these Computer Science decks in the same syllabus unit. Each uses the same spaced-repetition system, so progress in one informs the next.

6.1 Automated systems

9 flashcards
6.2 Robotics

9 flashcards

Cambridge syllabus keywords to use in your answers

These are the official Cambridge 0478 terms tagged to this section. Mark schemes credit responses that use the exact term — weave them into your answers verbatim rather than paraphrasing.

artificial intelligence AI machine learning neural network expert system natural language processing chatbot

Key terms covered in this Artificial Intelligence deck

Every term below is defined in the flashcards above. Use the list as a quick recall test before your exam — if you can't define one of these in your own words, flip back to that card.

Artificial Intelligence (AI)
Describe the structure and function of a neural network
Expert system and how does it work
Explain the purpose of Natural Language Processing (NLP)

How to study this Artificial Intelligence deck

Start in Study Mode, attempt each card before flipping, then rate Hard, Okay or Easy. Cards you rate Hard come back within a day; cards you rate Easy push out to weeks. Your progress is saved in your browser, so come back daily for 5–10 minute reviews until every card reads Mastered.