AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 993 · 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.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
2. 2.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) add more of the same (d) copy old unfair choices
3. 3.True or false: “add varied examples” adds to bias. (a) True (b) False
4. 4.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
6. 6.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) ignore complaints (d) ask different people
7. 7.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) test on one group only (d) fix wrong labels
8. 8.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
9. 9.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) copy old unfair choices (b) check who is missing (c) fix wrong labels (d) add varied examples
11. 11.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) use one group only (d) copy old unfair choices
12. 12.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) balance the data (d) ask different people
13. 13.True or false: “add varied examples” helps reduce bias. (a) False (b) True
14. 14.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
15. 15.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
16. 16.Which of these adds to bias? (a) test on many groups (b) balance the data (c) test on one group only (d) ask different people
17. 17.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) fewer tests (d) ignoring mistakes
18. 18.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) balance the data (d) copy old unfair choices
20. 20.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
21. 21.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) test on many groups (d) test on one group only
23. 23.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) use one group only (d) fix wrong labels
24. 24.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
25. 25.True or false: “balance the data” adds to bias. (a) False (b) True
26. 26.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
27. 27.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
28. 28.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
29. 29.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
30. 30.🔍 Which is the odd one out? (a) skip testing (b) check who is missing (c) test on one group only (d) add more of the same
31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
32. 32.Which of these helps reduce bias? (a) test on many groups (b) test on one group only (c) use one group only (d) skip testing
33. 33.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
34. 34.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) add more of the same (d) balance the data
35. 35.🖼️ 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
36. 36.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
37. 37.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
38. 38.True or false: “skip testing” helps reduce bias. (a) True (b) False
39. 39.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias

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