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AI Ethics & Society

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AI makes guesses. People choose how it learns. This track is about those choices.

This track's nine ideas, in order.

Need a quick recap?

  • An AI learns from examples. Examples from one place teach it about that place.
  • Accuracy is a count of right guesses out of all guesses.
  • What you post and what an app records are different.

What this track covers

  • Measuring who it gets wrong — score each group.
  • What it can work out — what an app records and works out.
  • When seeing is not believing — go back to where a message began.
  • The work inside a job — tasks shrink, stay or appear.
  • Somebody chose this — examples, goal and who answers.
  • The list that knows you — how a suggestion list is built.
  • Navigating, not fearing — a plain habit for each situation.
  • Who can use AI? — price, internet and who is left out.
  • Four rules for AI in health care — bioethics, judging health care choices.

Nothing here asks about you. Every example is made up.

This track also covers AI access. That means who can use AI at all. It covers bioethics too, a way to judge choices in health care. Both have a lesson at the end of this track.

Jump to lesson

This track

  1. 0 Start here
  2. 1 Measuring who it gets wrong
  3. 2 What it can work out
  4. 3 When seeing is not believing
  5. 4 The work inside a job
  6. 5 Somebody chose this
  7. 6 The list that knows you
  8. 7 Navigating, not fearing
  9. 8 Who can use AI?
  10. 9 Four rules for AI in health care
  11. 10 Checkpoint: choices, lists, habits, access and health care
  12. 12 The big picture
  13. 11 Track quiz

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