AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 662 · 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: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) check who is missing (d) add more of the same
3. 3.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) copy old unfair choices (d) ask different people
4. 4.Which of these helps reduce bias? (a) skip testing (b) balance the data (c) use one group only (d) ignore complaints
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
6. 6.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
7. 7.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
8. 8.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) fix wrong labels (d) test on many groups
9. 9.Which of these adds to bias? (a) test on one group only (b) fix wrong labels (c) ask different people (d) balance the data
10. 10.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) ignore complaints (d) ask different people
11. 11.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
12. 12.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) add varied examples (d) test on many groups
13. 13.True or false: “test on many groups” helps reduce bias. (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) copy old unfair choices (d) test on one group only
15. 15.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
16. 16.Which of these helps reduce bias? (a) add more of the same (b) test on one group only (c) use one group only (d) test on many groups
17. 17.True or false: “test on many groups” adds to bias. (a) True (b) False
18. 18.🖼️ 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
19. 19.True or false: “add varied examples” helps reduce bias. (a) True (b) False
20. 20.True or false: “check who is missing” helps reduce bias. (a) True (b) False
21. 21.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
22. 22.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
23. 23.Which of these adds to bias? (a) balance the data (b) test on many groups (c) ask different people (d) copy old unfair choices
24. 24.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
25. 25.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
26. 26.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
27. 27.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) add varied examples (d) ignore complaints
28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
29. 29.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
30. 30.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) skip testing (d) fix wrong labels
31. 31.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
32. 32.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
33. 33.Which of these adds to bias? (a) test on many groups (b) skip testing (c) fix wrong labels (d) balance the data
34. 34.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) test on one group only (d) balance the data
35. 35.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
36. 36.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
37. 37.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) fix wrong labels (d) skip testing
39. 39.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
40. 40.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True

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