AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 510 · 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: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
3. 3.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
4. 4.🔍 Which is the odd one out? (a) balance the data (b) ask different people (c) check who is missing (d) test on one group only
5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
6. 6.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) skip testing (d) check who is missing
8. 8.True or false: “fix wrong labels” adds to bias. (a) False (b) True
9. 9.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
10. 10.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
11. 11.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) add varied examples (d) copy old unfair choices
12. 12.Which of these helps reduce bias? (a) test on many groups (b) use one group only (c) test on one group only (d) add more of the same
13. 13.True or false: “skip testing” adds to bias. (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) balance the data (d) ignore complaints
15. 15.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
16. 16.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
17. 17.True or false: “add more of the same” helps reduce bias. (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) fix wrong labels (d) test on one group only
19. 19.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
20. 20.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
21. 21.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
22. 22.🖼️ 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
23. 23.True or false: “test on many groups” adds to bias. (a) True (b) False
24. 24.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
25. 25.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
26. 26.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
27. 27.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
28. 28.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) check who is missing
29. 29.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) balance the data (d) use one group only
30. 30.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) check who is missing (d) add varied examples
31. 31.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
32. 32.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.🗣️ 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
34. 34.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) ignore complaints (d) ask different people
35. 35.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
37. 37.Which of these adds to bias? (a) check who is missing (b) ask different people (c) fix wrong labels (d) add more of the same
38. 38.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
39. 39.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
40. 40.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True

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