AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 422 · 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 of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) use one group only (d) skip testing
2. 2.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
3. 3.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) check who is missing (d) skip testing
4. 4.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
5. 5.True or false: “add more of the same” adds to bias. (a) True (b) False
6. 6.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
7. 7.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) fix wrong labels (d) test on many groups
8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
9. 9.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) test on one group only (d) ignore complaints
10. 10.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) add more of the same (d) check who is missing
11. 11.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
12. 12.True or false: “skip testing” helps reduce bias. (a) True (b) False
13. 13.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
15. 15.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
16. 16.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
17. 17.True or false: “test on one group only” adds to bias. (a) True (b) False
18. 18.True or false: “test on many groups” adds to bias. (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) use one group only (d) ask different people
20. 20.True or false: “test on one group only” helps reduce bias. (a) False (b) True
21. 21.True or false: “test on many groups” helps reduce bias. (a) False (b) True
22. 22.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
23. 23.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
24. 24.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
25. 25.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
26. 26.Which of these adds to bias? (a) balance the data (b) test on one group only (c) check who is missing (d) fix wrong labels
27. 27.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) add varied examples (d) balance the data
29. 29.True or false: “ignore complaints” adds to bias. (a) False (b) True
30. 30.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
31. 31.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) balance the data (d) use one group only
32. 32.🗣️ 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) few child voices in data (d) children speak too fast
33. 33.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
34. 34.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) test on many groups (d) copy old unfair choices
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.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
37. 37.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
38. 38.True or false: “add more of the same” helps reduce bias. (a) False (b) True
39. 39.Which of these adds to bias? (a) check who is missing (b) add more of the same (c) add varied examples (d) ask different people
40. 40.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

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