AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 584 · 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 colour (b) the weather (c) its screen size (d) its training data
2. 2.Which of these helps reduce bias? (a) test on one group only (b) add more of the same (c) ignore complaints (d) test on many groups
3. 3.Which of these adds to bias? (a) add varied examples (b) ask different people (c) fix wrong labels (d) test on one group only
4. 4.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
5. 5.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) balance the data (d) skip testing
6. 6.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
7. 7.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
8. 8.🗣️ 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) few child voices in data (d) children speak too fast
9. 9.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) use one group only (d) fix wrong labels
10. 10.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.True or false: “add varied examples” adds to bias. (a) True (b) False
12. 12.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
13. 13.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
14. 14.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
16. 16.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
17. 17.True or false: “use one group only” adds to bias. (a) False (b) True
18. 18.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) add more of the same (d) balance the data
19. 19.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
20. 20.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) fix wrong labels (d) test on one group only
21. 21.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) copy old unfair choices (d) add varied examples
22. 22.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) use one group only (d) ask different people
23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
24. 24.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
26. 26.True or false: “fix wrong labels” adds to bias. (a) False (b) True
27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
28. 28.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
29. 29.True or false: “add more of the same” helps reduce bias. (a) True (b) False
30. 30.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
31. 31.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
32. 32.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
33. 33.Which of these adds to bias? (a) fix wrong labels (b) copy old unfair choices (c) test on many groups (d) balance the data
34. 34.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
35. 35.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
36. 36.True or false: “test on many groups” helps reduce bias. (a) True (b) False
37. 37.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
38. 38.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
39. 39.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
40. 40.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) skip testing (d) fix wrong labels

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