AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 718 · 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.True or false: “test on many groups” adds to bias. (a) True (b) False
2. 2.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
3. 3.True or false: “fix wrong labels” adds to bias. (a) False (b) True
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) bias from data (d) a strong battery
5. 5.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
6. 6.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) ignore complaints (d) check who is missing
7. 7.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) ignore complaints (d) skip testing
8. 8.True or false: “check who is missing” helps reduce bias. (a) False (b) True
9. 9.True or false: “balance the data” helps reduce bias. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) check who is missing (d) test on many groups
11. 11.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) use one group only (d) test on many groups
12. 12.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) test on one group only (d) check who is missing
13. 13.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
14. 14.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) check who is missing (d) copy old unfair choices
15. 15.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
16. 16.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
17. 17.True or false: “skip testing” helps reduce bias. (a) False (b) True
18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
19. 19.🗣️ 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) children speak too fast (d) few child voices in data
20. 20.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
21. 21.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
22. 22.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
23. 23.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) ignore complaints (d) add varied examples
25. 25.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
26. 26.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
27. 27.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
28. 28.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) balance the data (d) skip testing
29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
30. 30.True or false: “ask different people” helps reduce bias. (a) True (b) False
31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
32. 32.Which of these adds to bias? (a) check who is missing (b) balance the data (c) copy old unfair choices (d) add varied examples
33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) use one group only (d) add varied examples
34. 34.Which of these adds to bias? (a) ask different people (b) test on many groups (c) add varied examples (d) add more of the same
35. 35.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
37. 37.True or false: “use one group only” adds to bias. (a) False (b) True
38. 38.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) test on one group only (d) copy old unfair choices
39. 39.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
40. 40.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data

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