SECAI Core · phase 1 of 15
Machine learning
A component of AI that enables a machine to develop strategies for solving a task given a labeled dataset where features have been manually identified but without further explicit instructions.
The Explain card
- Plain English
- Machine learning is the part of AI where a machine works out its own strategy for a task from a labeled dataset, with humans picking out the features but not writing the rules.
- Example
- A spam filter is fed thousands of emails marked "spam" or "not spam", with features like sender domain and link count identified by engineers. It learns the weighting itself.
- Why it matters
- If the model learns from data, then whoever controls or poisons that data shapes the model's behaviour. Data quality and data security become model security.
- Hook
- Humans label the ingredients, the machine writes the recipe.
Where it sits in the deck
Phase 1: What AI Is: Core Concepts and Paradigms
You cannot secure, govern, or attack something you cannot define — establish what AI actually is before any other concept can land.
