AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 666 · 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.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
2. 2.🗣️ 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) children speak too fast (d) few child voices in data
3. 3.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
4. 4.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
5. 5.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
6. 6.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) test on one group only (d) add more of the same
7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
8. 8.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
9. 9.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) fix wrong labels (d) ask different people
10. 10.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
11. 11.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) skip testing
12. 12.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
13. 13.True or false: “test on one group only” helps reduce bias. (a) True (b) False
14. 14.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) skip testing (d) fix wrong labels
15. 15.True or false: “add more of the same” adds to bias. (a) False (b) True
16. 16.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
17. 17.True or false: “ask different people” adds to bias. (a) True (b) False
18. 18.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) test on many groups (d) test on one group only
19. 19.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) add more of the same (d) skip testing
20. 20.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) test on many groups (d) ask different people
21. 21.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
22. 22.Which of these helps reduce bias? (a) ask different people (b) copy old unfair choices (c) use one group only (d) add more of the same
23. 23.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
24. 24.True or false: “ignore complaints” adds to bias. (a) True (b) False
25. 25.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
26. 26.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
28. 28.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) fix wrong labels (d) balance the data
29. 29.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
30. 30.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
31. 31.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
32. 32.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) skip testing (d) ignore complaints
33. 33.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.True or false: “fix wrong labels” adds to bias. (a) True (b) False
35. 35.True or false: photos of people of many ages and skin tones 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 one-sided data (likely to make a biased model). (a) True (b) False
37. 37.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
38. 38.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) ask different people (d) test on many groups
40. 40.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data

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