Topic 6: Automated and Emerging Technologies — Part 3

01 What is artificial intelligence?

Artificial intelligence (AI) is the simulation of intelligent behaviours by computers — making machines appear to think, reason, and solve problems in ways that mimic human intelligence.

Key characteristics of AI systems include:

• Data and rules — use stored information and logical rules to reach conclusions.
• Reasoning — apply logic to process information and draw inferences.
• Learn and adapt — improve performance over time, especially in machine learning systems.

02 Expert systems

An expert system is a type of AI that mimics the decision-making of a human expert in a specific domain. It has four main components:

Knowledge base

Stores facts and domain-specific information (e.g. symptoms, diseases, and treatments in medicine).

Rule base

Contains if-then rules that link conditions to conclusions (e.g. "IF fever AND rash THEN consider measles").

Inference engine

Applies the rules to the knowledge base to draw conclusions and suggest diagnoses or solutions.

User interface

Allows the user to input questions and receive explanations or recommendations.

Example: A medical diagnosis expert system helps doctors by suggesting possible conditions based on patient symptoms entered through the interface.

03 Machine learning

Machine learning (ML) is a branch of AI where systems automatically improve their performance by learning from data, rather than relying only on fixed, hand-written rules.

• ML systems adapt as they receive more data — their behaviour is not limited to a fixed set of if-then rules.
• Image recognition — identifying objects, faces, or handwriting in photos.
• Recommendation systems — services like Netflix suggesting films based on viewing history.
• Translation — automatically converting text or speech between languages.