AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 398 · 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: stories with doctors of every gender? (a) one-sided data (b) balanced data
2. 2.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) skip testing (d) add varied examples
3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a fair model (d) a strong battery
5. 5.Which of these adds to bias? (a) balance the data (b) check who is missing (c) test on one group only (d) ask different people
6. 6.True or false: “add varied examples” helps reduce bias. (a) True (b) False
7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
8. 8.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) add more of the same (d) check who is missing
9. 9.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) ask different people (d) ignore complaints
10. 10.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
11. 11.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
12. 12.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) add more of the same
13. 13.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
14. 14.True or false: “test on one group only” helps reduce bias. (a) True (b) False
15. 15.True or false: “skip testing” adds to bias. (a) False (b) True
16. 16.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
18. 18.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
19. 19.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
20. 20.True or false: “fix wrong labels” adds to bias. (a) True (b) False
21. 21.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
22. 22.True or false: “add more of the same” adds to bias. (a) False (b) True
23. 23.Which of these helps reduce bias? (a) copy old unfair choices (b) check who is missing (c) ignore complaints (d) use one group only
24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
25. 25.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
26. 26.Which of these helps reduce bias? (a) use one group only (b) add more of the same (c) copy old unfair choices (d) test on many groups
27. 27.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
28. 28.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) balance the data (d) add varied examples
29. 29.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
31. 31.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) add more of the same (d) add varied examples
32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) fix wrong labels (d) ignore complaints
34. 34.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) add varied examples (d) check who is missing
35. 35.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
36. 36.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
37. 37.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
38. 38.True or false: “balance the data” adds to bias. (a) True (b) False
39. 39.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) skip testing (d) ask different people
40. 40.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False

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