AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 614 · 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: “ask different people” adds to bias. (a) False (b) True
2. 2.🗣️ 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) children speak too fast (d) it was a rainy day
3. 3.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
4. 4.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
5. 5.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
6. 6.True or false: “ignore complaints” adds to bias. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) add varied examples (d) use one group only
8. 8.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
9. 9.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
10. 10.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) check who is missing (d) test on one group only
11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
12. 12.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
13. 13.True or false: “test on many groups” helps reduce bias. (a) False (b) True
14. 14.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
16. 16.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
17. 17.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
18. 18.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.Which of these adds to bias? (a) fix wrong labels (b) balance the data (c) ask different people (d) add more of the same
20. 20.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) test on many groups (d) add varied examples
21. 21.Which of these adds to bias? (a) check who is missing (b) skip testing (c) test on many groups (d) add varied examples
22. 22.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) fix wrong labels (d) use one group only
23. 23.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
24. 24.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
25. 25.True or false: “skip testing” helps reduce bias. (a) False (b) True
26. 26.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
27. 27.True or false: “test on many groups” adds to bias. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) use one group only (d) check who is missing
29. 29.🔍 Which is the odd one out? (a) copy old unfair choices (b) ask different people (c) add varied examples (d) check who is missing
30. 30.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
31. 31.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
32. 32.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) more varied data (d) fewer tests
33. 33.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
34. 34.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
35. 35.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
36. 36.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
37. 37.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
38. 38.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
39. 39.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
40. 40.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False

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