AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 669 · 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) the weather (b) its colour (c) its training data (d) its screen size
2. 2.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
3. 3.True or false: “test on many groups” helps reduce bias. (a) False (b) True
4. 4.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
5. 5.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
6. 6.Which of these adds to bias? (a) balance the data (b) use one group only (c) test on many groups (d) check who is missing
7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
8. 8.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) test on one group only (d) test on many groups
9. 9.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) skip testing (d) add more of the same
10. 10.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) add more of the same (d) test on one group only
11. 11.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) ignore complaints (d) ask different people
12. 12.True or false: “add varied examples” helps reduce bias. (a) False (b) True
13. 13.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) balance the data (d) ignore complaints
14. 14.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) skip testing (d) add varied examples
15. 15.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) ask different people (d) check who is missing
16. 16.True or false: “add varied examples” adds to bias. (a) False (b) True
17. 17.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) copy old unfair choices (d) ask different people
18. 18.🖼️ 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
19. 19.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) ignoring mistakes (d) fewer tests
20. 20.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
21. 21.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
22. 22.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
23. 23.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
25. 25.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) balance the data (d) add varied examples
26. 26.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
27. 27.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) test on one group only (d) add more of the same
29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
30. 30.Which of these helps reduce bias? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) use one group only
31. 31.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
32. 32.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
33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
34. 34.Which of these adds to bias? (a) add varied examples (b) ask different people (c) check who is missing (d) copy old unfair choices
35. 35.Which of these adds to bias? (a) test on many groups (b) ask different people (c) test on one group only (d) balance the data
36. 36.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
37. 37.True or false: “skip testing” helps reduce bias. (a) False (b) True
38. 38.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
39. 39.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
40. 40.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias

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