Lesson Objectives
- Define Artificial Intelligence.
- Explain the Turing Test.
- Describe machine learning.
- Compare Narrow AI and AGI.
What is Artificial Intelligence?
Artificial Intelligence (AI) refers to computer systems that perform tasks normally requiring human intelligence.
- Recognising speech
- Understanding language
- Making decisions
- Learning from data
- Solving problems
AI does not "think" like humans — it identifies patterns in data.
Alan Turing
- British mathematician (1912–1954).
- Helped break the Enigma code in WWII.
- Laid foundations of computer science.
- Proposed the Turing Test in 1950.
The Turing Test
- A judge communicates with a human and a machine via text.
- If the judge cannot reliably tell which is the machine, it passes.
- Tests imitation of intelligence — not consciousness.
Traditional Programming
Input → Rules → Output
- Programmer writes rules manually.
- Computer follows exact instructions.
- Limited adaptability.
Machine Learning
Input + Output Examples → Computer Learns Rules
- Uses training data.
- Finds patterns automatically.
- Improves with more data.
Example: Spam Detection
- Thousands of labelled emails.
- AI learns spam patterns.
- Predicts new spam emails.
Narrow AI
- Designed for one specific task.
- Cannot transfer learning.
- Exists today.
- Examples: Voice assistants, recommendation systems.
Artificial General Intelligence (AGI)
- Would perform any intellectual task a human can.
- Transfer knowledge across domains.
- Does not currently exist.
Discussion Question
Is modern AI truly intelligent — or advanced pattern recognition?
- Does imitation equal understanding?
- Is consciousness required for intelligence?