AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 181 · 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: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
2. 2.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
4. 4.Which of these helps reduce bias? (a) fix wrong labels (b) test on one group only (c) ignore complaints (d) copy old unfair choices
5. 5.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) skip testing (d) add more of the same
6. 6.True or false: “skip testing” adds to bias. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) skip testing (d) use one group only
8. 8.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
9. 9.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) ignore complaints (d) balance the data
10. 10.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
11. 11.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
12. 12.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
13. 13.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
14. 14.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
16. 16.Which of these adds to bias? (a) fix wrong labels (b) check who is missing (c) add more of the same (d) test on many groups
17. 17.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
18. 18.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) fix wrong labels (b) add more of the same (c) add varied examples (d) check who is missing
20. 20.Which of these adds to bias? (a) use one group only (b) test on many groups (c) ask different people (d) check who is missing
21. 21.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) skip testing (d) ask different people
22. 22.🖼️ 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
23. 23.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
26. 26.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) test on many groups (d) add more of the same
27. 27.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
28. 28.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
29. 29.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
30. 30.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
31. 31.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
32. 32.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
33. 33.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
35. 35.True or false: “add varied examples” helps reduce bias. (a) False (b) True
36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
37. 37.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
38. 38.Which of these adds to bias? (a) ask different people (b) add varied examples (c) ignore complaints (d) check who is missing
39. 39.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) fix wrong labels (d) test on many groups
40. 40.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias

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