AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 989 · 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.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
2. 2.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
3. 3.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) fix wrong labels (d) skip testing
4. 4.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) it was a rainy day (d) children speak too fast
6. 6.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
7. 7.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) a broken screen (d) bias from data
9. 9.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
10. 10.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) check who is missing (d) ask different people
11. 11.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
12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) copy old unfair choices (c) test on many groups (d) ask different people
13. 13.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
15. 15.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) balance the data (d) add varied examples
16. 16.True or false: “use one group only” helps reduce bias. (a) True (b) False
17. 17.True or false: “skip testing” helps reduce bias. (a) False (b) True
18. 18.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
21. 21.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
22. 22.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
23. 23.True or false: “ask different people” helps reduce bias. (a) False (b) True
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 of these adds to bias? (a) check who is missing (b) add varied examples (c) ignore complaints (d) ask different people
26. 26.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
27. 27.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) check who is missing (d) test on one group only
29. 29.Which of these helps reduce bias? (a) balance the data (b) test on one group only (c) copy old unfair choices (d) ignore complaints
30. 30.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
31. 31.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
32. 32.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) test on one group only (d) skip testing
33. 33.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) test on one group only (d) test on many groups
34. 34.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) add more of the same (d) test on many groups
35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) add varied examples (d) balance the data
36. 36.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
37. 37.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
38. 38.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
39. 39.True or false: “check who is missing” helps reduce bias. (a) False (b) True
40. 40.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True

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