AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 101 · 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: mangoes both raw and ripe? (a) one-sided data (b) balanced data
2. 2.True or false: “add varied examples” adds to bias. (a) True (b) False
3. 3.Which of these adds to bias? (a) test on many groups (b) add varied examples (c) ask different people (d) use one group only
4. 4.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
6. 6.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
7. 7.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) skip testing (d) check who is missing
8. 8.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) add more of the same (d) ask different people
9. 9.🔍 Which is the odd one out? (a) use one group only (b) ask different people (c) balance the data (d) fix wrong labels
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
11. 11.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) fix wrong labels (d) skip testing
13. 13.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) copy old unfair choices (d) check who is missing
14. 14.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
16. 16.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
17. 17.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) test on one group only (d) test on many groups
18. 18.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
20. 20.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) add more of the same
21. 21.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
22. 22.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
23. 23.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
24. 24.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
26. 26.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) skip testing (d) test on one group only
27. 27.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
28. 28.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) ignore complaints (d) balance the data
29. 29.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
30. 30.True or false: “test on many groups” helps reduce bias. (a) True (b) False
31. 31.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
33. 33.True or false: “check who is missing” adds to bias. (a) False (b) True
34. 34.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add more of the same (d) ask different people
35. 35.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) add varied examples (d) test on one group only
36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
37. 37.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
38. 38.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
39. 39.🗣️ 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
40. 40.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) copy old unfair choices (d) add varied examples

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