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  1. Title
  2. Introduction to the role of algorithms
  3. Student list of experiences
  4. Title
  5. Algorithms are like recipes
  6. Define algorithm
  7. Machine learning
  8. Define training data
  9. Black box problem
  10. Explain training data bias
  11. How algorithms work
  12. Explain search engine algorithms
  13. Bias in search algorithms
  14. Identifying the least biased search
  15. Title
  16. The attention economy
  17. Reorder attention economy steps
  18. Addicting and engaging content
  19. Costs of the attention economy
  20. How suggestion algorithms change you
  21. Title
  22. Celebrity clones
  23. Reducing harmful content
  24. Filter bubbles
  25. Match filter bubble and rabbit hole
  26. Reflect on feedback loops
  27. Amplifying bias
  28. Bias from training data
  29. Title
  30. Meet Gen
  31. Explain generative AI inaccuracies
  32. AI image generators
  33. Explain AI images and harmful stereotypes
  34. Future AI concerns and developments
  35. Connect AI problems to algorithmic harms
  36. Argue risks and benefits of AI
  37. Title
  38. Steps you can take
  39. List actions
  40. Make an algorithm plan
  41. Acknowledgments
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