AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 536 · 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: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
2. 2.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
3. 3.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) test on one group only (d) check who is missing
4. 4.Which of these adds to bias? (a) use one group only (b) add varied examples (c) ask different people (d) test on many groups
5. 5.True or false: “test on one group only” helps reduce bias. (a) True (b) False
6. 6.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) test on many groups (d) add more of the same
7. 7.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) balance the data (d) ignore complaints
8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
9. 9.True or false: “skip testing” adds to bias. (a) False (b) True
10. 10.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
11. 11.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
13. 13.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
14. 14.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
15. 15.True or false: “skip testing” helps reduce bias. (a) True (b) False
16. 16.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
17. 17.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
18. 18.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a strong battery (d) a fair model
19. 19.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) add more of the same (d) test on many groups
20. 20.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
21. 21.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
22. 22.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
23. 23.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) test on one group only (d) check who is missing
24. 24.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
26. 26.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) check who is missing (d) add varied examples
27. 27.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) test on many groups (d) test on one group only
28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
30. 30.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) ignore complaints (d) add varied examples
31. 31.Which of these helps reduce bias? (a) add varied examples (b) use one group only (c) skip testing (d) test on one group only
32. 32.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
33. 33.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
34. 34.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
35. 35.True or false: “ask different people” helps reduce bias. (a) False (b) True
36. 36.True or false: “balance the data” adds to bias. (a) True (b) False
37. 37.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
38. 38.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
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.True or false: “ignore complaints” helps reduce bias. (a) True (b) False

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