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AI Ethics & Bias

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When an AI helps to decide, it should treat people fairly. How can we tell when it does not?

This track's four ideas, in order.

This is AI Ethics & Bias. It uses what you know about how an AI learns from examples.

Ethics means moral rules for choosing what is right and fair.

If an AI result seems unfair, tell a grown-up you trust.

What you will learn

  • Unfair picks. What bias is and where it starts.
  • Five kinds. Data, historical, measurement, algorithmic and human.
  • Three reported mistakes. What happened and what each one taught.
  • A person in charge. Who checks a big decision.

Need a quick recap?

  • Training — a program learns a rule from labelled examples. A label is the right answer.
  • What it learned from — the examples it was shown.
  • Tracing a mistake — follow a wrong answer to its cause.

Jump to lesson

This track

  1. 0 Start here
  2. 1 When a choice is unfair
  3. 2 Five kinds of bias
  4. 3 Three mistakes that were reported
  5. 4 Keep a person in charge
  6. 5 The big picture
  7. 6 Track quiz

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