AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 916 · 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 of these helps reduce bias? (a) test on many groups (b) skip testing (c) use one group only (d) test on one group only
2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
3. 3.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
4. 4.True or false: “check who is missing” helps reduce bias. (a) False (b) True
5. 5.True or false: “ignore complaints” adds to bias. (a) False (b) True
6. 6.Which of these adds to bias? (a) add more of the same (b) fix wrong labels (c) add varied examples (d) balance the data
7. 7.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
8. 8.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add more of the same (d) add varied examples
9. 9.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) balance the data (d) copy old unfair choices
10. 10.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
11. 11.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
13. 13.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
14. 14.Which of these adds to bias? (a) copy old unfair choices (b) balance the data (c) ask different people (d) test on many groups
15. 15.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) skip testing (d) ask different people
16. 16.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
18. 18.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
20. 20.True or false: “test on many groups” adds to bias. (a) True (b) False
21. 21.True or false: “ask different people” adds to bias. (a) True (b) False
22. 22.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
24. 24.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) add more of the same (d) use one group only
25. 25.🖼️ 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
26. 26.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) test on many groups (d) ignore complaints
27. 27.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
28. 28.Which of these adds to bias? (a) add varied examples (b) skip testing (c) test on many groups (d) ask different people
29. 29.True or false: “use one group only” adds to bias. (a) False (b) True
30. 30.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
31. 31.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) skip testing (d) copy old unfair choices
32. 32.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
33. 33.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
35. 35.Which of these adds to bias? (a) fix wrong labels (b) ignore complaints (c) test on many groups (d) ask different people
36. 36.Which of these helps reduce bias? (a) balance the data (b) use one group only (c) skip testing (d) copy old unfair choices
37. 37.Which of these helps reduce bias? (a) add varied examples (b) add more of the same (c) copy old unfair choices (d) use one group only
38. 38.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
39. 39.True or false: “test on one group only” adds to bias. (a) True (b) False
40. 40.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data

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