AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 97 · 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.True or false: “add more of the same” adds to bias. (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) ignore complaints (b) use one group only (c) ask different people (d) add more of the same
3. 3.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
4. 4.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) test on many groups (d) copy old unfair choices
5. 5.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
6. 6.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
7. 7.🖼️ 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
8. 8.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
9. 9.True or false: “use one group only” helps reduce bias. (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) fix wrong labels (d) use one group only
11. 11.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
13. 13.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
14. 14.Which of these helps reduce bias? (a) add more of the same (b) use one group only (c) add varied examples (d) skip testing
15. 15.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
16. 16.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
17. 17.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) balance the data (d) add varied examples
18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
19. 19.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
20. 20.True or false: “test on many groups” adds to bias. (a) False (b) True
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.Which of these adds to bias? (a) test on one group only (b) add varied examples (c) fix wrong labels (d) ask different people
23. 23.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
24. 24.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
25. 25.True or false: “balance the data” adds to bias. (a) False (b) True
26. 26.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
27. 27.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) balance the data (d) check who is missing
28. 28.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
29. 29.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
30. 30.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
31. 31.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) balance the data (d) use one group only
32. 32.Which of these adds to bias? (a) check who is missing (b) balance the data (c) test on many groups (d) copy old unfair choices
33. 33.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) ignore complaints (d) check who is missing
34. 34.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) it was a rainy day (d) children speak too fast
35. 35.Which of these helps reduce bias? (a) ask different people (b) skip testing (c) test on one group only (d) ignore complaints
36. 36.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
37. 37.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.🔍 Which is the odd one out? (a) balance the data (b) test on one group only (c) test on many groups (d) add varied examples
39. 39.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
40. 40.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) skip testing (d) fix wrong labels

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