Introduction to AI and Everyday Examples

AI lets machines do tasks that need thinking, like recognising and predicting, by learning from data. Automation only repeats a fixed rule.

Key ideas

• Artificial Intelligence (AI) is the ability of machines to do tasks that usually need human thinking.
• AI learns from data and can improve; automation follows the same fixed rule every time and does not learn.
• Supervised learning learns from examples with the right answers (labels), such as photos marked “cat” or “dog”.
• Unsupervised learning finds groups in data that has no labels; reinforcement learning learns by trial and error with rewards.
• Machines are better at fast, repetitive work; people are better at feelings, common sense and imagination.
• AI can make mistakes, so we test it on new examples and check its answers.

Remember

Watch out

• Calling every machine AI: an automatic door with a fixed rule is only automation.
• Dividing by the number wrong instead of the number tested when finding accuracy.
• Mixing up supervised (labels given) and unsupervised (no labels) learning.

Worked example