AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 379 · 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) test on many groups (b) add varied examples (c) fix wrong labels (d) add more of the same
2. 2.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
3. 3.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) test on one group only (d) add more of the same
4. 4.True or false: “add varied examples” adds to bias. (a) True (b) False
5. 5.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
6. 6.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) ask different people (d) use one group only
7. 7.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
8. 8.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) add varied examples (d) test on one group only
9. 9.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
10. 10.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
11. 11.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) check who is missing (d) skip testing
13. 13.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) bias from data (d) a strong battery
14. 14.🛠️ What helps make an AI system fairer? (a) more varied data (b) fewer tests (c) ignoring mistakes (d) one group only
15. 15.Which of these helps reduce bias? (a) balance the data (b) ignore complaints (c) skip testing (d) copy old unfair choices
16. 16.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
17. 17.True or false: “test on many groups” helps reduce bias. (a) True (b) False
18. 18.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
19. 19.Which of these adds to bias? (a) balance the data (b) add varied examples (c) test on many groups (d) ignore complaints
20. 20.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) balance the data (d) add more of the same
21. 21.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: “test on many groups” adds to bias. (a) False (b) True
24. 24.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
25. 25.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
26. 26.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
27. 27.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
28. 28.🗣️ 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
29. 29.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
30. 30.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) add more of the same (d) test on one group only
31. 31.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
32. 32.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) skip testing (d) use one group only
33. 33.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
34. 34.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) check who is missing (d) add varied examples
35. 35.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
36. 36.🔍 Which is the odd one out? (a) balance the data (b) fix wrong labels (c) copy old unfair choices (d) test on many groups
37. 37.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
38. 38.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) check who is missing (d) fix wrong labels
39. 39.Which of these helps reduce bias? (a) test on one group only (b) fix wrong labels (c) add more of the same (d) copy old unfair choices
40. 40.True or false: “check who is missing” adds to bias. (a) True (b) False

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