AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 170 · 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.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
2. 2.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
3. 3.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a fair model (d) a strong battery
4. 4.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
5. 5.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add more of the same (d) add varied examples
6. 6.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
7. 7.Which of these helps reduce bias? (a) add more of the same (b) fix wrong labels (c) ignore complaints (d) use one group only
8. 8.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) use one group only (d) add more of the same
9. 9.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) test on one group only
10. 10.🔍 Which is the odd one out? (a) skip testing (b) test on one group only (c) copy old unfair choices (d) check who is missing
11. 11.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
12. 12.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
13. 13.True or false: “ignore complaints” adds to bias. (a) True (b) False
14. 14.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
15. 15.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) skip testing (d) test on one group only
16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
17. 17.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
18. 18.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) use one group only (d) check who is missing
20. 20.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
21. 21.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
22. 22.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
23. 23.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
24. 24.True or false: “check who is missing” adds to bias. (a) True (b) False
25. 25.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
26. 26.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
27. 27.Which of these helps reduce bias? (a) check who is missing (b) ignore complaints (c) add more of the same (d) copy old unfair choices
28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
29. 29.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
30. 30.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) ignore complaints (d) ask different people
31. 31.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
32. 32.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
33. 33.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
34. 34.Which of these adds to bias? (a) balance the data (b) check who is missing (c) skip testing (d) fix wrong labels
35. 35.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
36. 36.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
37. 37.True or false: “skip testing” helps reduce bias. (a) True (b) False
38. 38.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) add varied examples (d) skip testing
40. 40.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False

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