AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 585 · 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.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) add more of the same (d) use one group only
2. 2.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
3. 3.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) it was a rainy day (d) the phone was new
5. 5.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
6. 6.True or false: “add more of the same” adds to bias. (a) True (b) False
7. 7.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) add varied examples (d) copy old unfair choices
8. 8.True or false: “skip testing” helps reduce bias. (a) True (b) False
9. 9.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
10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
12. 12.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
13. 13.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (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.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
16. 16.True or false: “fix wrong labels” adds to bias. (a) False (b) True
17. 17.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) use one group only
18. 18.Which of these adds to bias? (a) test on many groups (b) ignore complaints (c) check who is missing (d) balance the data
19. 19.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) copy old unfair choices (d) fix wrong labels
20. 20.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
21. 21.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
23. 23.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
24. 24.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) add more of the same (d) test on one group only
25. 25.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
26. 26.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) fix wrong labels (d) add more of the same
27. 27.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
28. 28.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) check who is missing (d) fix wrong labels
29. 29.Which of these adds to bias? (a) skip testing (b) balance the data (c) add varied examples (d) check who is missing
30. 30.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
31. 31.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
32. 32.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
34. 34.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
35. 35.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) test on one group only (d) ignore complaints
36. 36.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
37. 37.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
38. 38.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
39. 39.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) fix wrong labels (d) use one group only
40. 40.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data

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