AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 818 · 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: stories with doctors of every gender? (a) balanced data (b) one-sided data
2. 2.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
3. 3.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
4. 4.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) use one group only
5. 5.🔍 Which is the odd one out? (a) add more of the same (b) balance the data (c) skip testing (d) use one group only
6. 6.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) add more of the same (d) fix wrong labels
7. 7.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
8. 8.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) use one group only (d) ignore complaints
9. 9.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
10. 10.Which of these adds to bias? (a) ask different people (b) check who is missing (c) balance the data (d) skip testing
11. 11.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) ask different people (d) balance the data
12. 12.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
15. 15.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
16. 16.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
17. 17.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
18. 18.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
19. 19.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) copy old unfair choices (d) test on one group only
20. 20.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) use one group only (d) check who is missing
21. 21.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
22. 22.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add varied examples (d) use one group only
23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
24. 24.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
25. 25.True or false: “test on one group only” helps reduce bias. (a) False (b) True
26. 26.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
27. 27.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) test on one group only (d) balance the data
28. 28.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
29. 29.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) check who is missing (d) test on many groups
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
31. 31.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
32. 32.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
33. 33.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
34. 34.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
35. 35.True or false: “ask different people” helps reduce bias. (a) False (b) True
36. 36.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
37. 37.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
38. 38.True or false: “use one group only” adds to bias. (a) False (b) True
39. 39.True or false: “skip testing” adds to bias. (a) False (b) True
40. 40.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False

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