AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 820 · 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 is the odd one out? (a) balance the data (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
2. 2.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
3. 3.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
5. 5.🔍 Which is the odd one out? (a) copy old unfair choices (b) balance the data (c) use one group only (d) skip testing
6. 6.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
7. 7.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
8. 8.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
9. 9.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
10. 10.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) skip testing (d) add varied examples
11. 11.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
12. 12.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) ask different people (d) use one group only
14. 14.True or false: “balance the data” helps reduce bias. (a) True (b) False
15. 15.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
16. 16.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
17. 17.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
18. 18.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) use one group only (d) add varied examples
19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
20. 20.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) use one group only (d) check who is missing
21. 21.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
22. 22.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
23. 23.Which of these helps reduce bias? (a) test on many groups (b) use one group only (c) copy old unfair choices (d) ignore complaints
24. 24.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
25. 25.🔍 Which is the odd one out? (a) check who is missing (b) balance the data (c) add varied examples (d) add more of the same
26. 26.Which of these adds to bias? (a) test on many groups (b) balance the data (c) fix wrong labels (d) copy old unfair choices
27. 27.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
28. 28.Which of these adds to bias? (a) test on many groups (b) test on one group only (c) add varied examples (d) balance the data
29. 29.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
30. 30.True or false: “add varied examples” helps reduce bias. (a) True (b) False
31. 31.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
32. 32.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
33. 33.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) copy old unfair choices (d) skip testing
34. 34.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) test on one group only (d) skip testing
36. 36.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) use one group only (d) add more of the same
38. 38.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) test on many groups (d) ignore complaints
39. 39.True or false: “add more of the same” helps reduce bias. (a) True (b) False
40. 40.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

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