AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 509 · 40 questions

AI tip (Fair data, fairer AI): Bias usually comes from the training data: if a group is missing or shown in only one way, the model copies that. One-sided data: one age group, only ripe mangoes, only adult voices, only neat handwriting. Balanced data: many ages, colours, voices, regions and styles. Reduce bias: add varied examples, check who is missing, test on many groups, fix wrong labels and listen to complaints.

1. 1.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
2. 2.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
3. 3.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) add varied examples (d) add more of the same
5. 5.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) add varied examples (d) ignore complaints
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) fix wrong labels (d) test on many groups
8. 8.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
9. 9.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
10. 10.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
11. 11.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.True or false: “add more of the same” helps reduce bias. (a) False (b) True
13. 13.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) add more of the same (d) add varied examples
14. 14.True or false: “balance the data” adds to bias. (a) True (b) False
15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
16. 16.True or false: “ask different people” helps reduce bias. (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) ask different people (d) fix wrong labels
18. 18.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
20. 20.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
22. 22.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
23. 23.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
24. 24.True or false: “test on many groups” adds to bias. (a) True (b) False
25. 25.True or false: “add more of the same” adds to bias. (a) False (b) True
26. 26.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
27. 27.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
28. 28.Which of these adds to bias? (a) test on one group only (b) balance the data (c) add varied examples (d) check who is missing
29. 29.Which of these helps reduce bias? (a) test on many groups (b) use one group only (c) ignore complaints (d) skip testing
30. 30.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
31. 31.True or false: “ignore complaints” adds to bias. (a) False (b) True
32. 32.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) fix wrong labels (d) use one group only
33. 33.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) use one group only (d) add more of the same
34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
35. 35.True or false: “check who is missing” adds to bias. (a) True (b) False
36. 36.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) ask different people (d) copy old unfair choices
37. 37.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
39. 39.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) skip testing (d) add more of the same
40. 40.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) copy old unfair choices (d) add more of the same

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