AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 487 · 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.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
2. 2.Which of these helps reduce bias? (a) use one group only (b) ask different people (c) ignore complaints (d) add more of the same
3. 3.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
4. 4.🔍 Which is the odd one out? (a) test on many groups (b) use one group only (c) ignore complaints (d) skip testing
5. 5.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
6. 6.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
7. 7.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
8. 8.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
9. 9.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
10. 10.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
12. 12.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
13. 13.True or false: “skip testing” helps reduce bias. (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
15. 15.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
16. 16.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
17. 17.True or false: “add more of the same” adds to bias. (a) False (b) True
18. 18.Which of these adds to bias? (a) use one group only (b) balance the data (c) check who is missing (d) add varied examples
19. 19.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
20. 20.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
21. 21.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) ignore complaints (d) add varied examples
22. 22.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) add more of the same (d) check who is missing
23. 23.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
25. 25.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) copy old unfair choices (d) balance the data
26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
27. 27.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
28. 28.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
29. 29.Which of these adds to bias? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) add more of the same
30. 30.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
31. 31.True or false: “ignore complaints” adds to bias. (a) True (b) False
32. 32.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
33. 33.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
34. 34.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) fix wrong labels (d) use one group only
35. 35.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
36. 36.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) add more of the same (d) use one group only
37. 37.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
38. 38.Which of these adds to bias? (a) check who is missing (b) balance the data (c) test on many groups (d) ignore complaints
39. 39.True or false: “test on many groups” adds to bias. (a) False (b) True
40. 40.True or false: “use one group only” adds to bias. (a) False (b) True

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