AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 837 · 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: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
2. 2.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
3. 3.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
4. 4.True or false: “use one group only” helps reduce bias. (a) True (b) False
5. 5.True or false: “check who is missing” adds to bias. (a) False (b) True
6. 6.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) ignore complaints (d) balance the data
7. 7.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
8. 8.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
9. 9.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
10. 10.Which of these adds to bias? (a) ask different people (b) use one group only (c) test on many groups (d) fix wrong labels
11. 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a broken screen (d) a fair model
12. 12.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) test on one group only (d) test on many groups
13. 13.True or false: “balance the data” helps reduce bias. (a) True (b) False
14. 14.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
15. 15.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
16. 16.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
18. 18.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
19. 19.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
20. 20.🔍 Which is the odd one out? (a) fix wrong labels (b) skip testing (c) add varied examples (d) test on many groups
21. 21.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) fix wrong labels (d) balance the data
22. 22.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) ignore complaints (d) add more of the same
23. 23.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) ask different people (d) ignore complaints
24. 24.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) balance the data (d) use one group only
25. 25.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
26. 26.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) copy old unfair choices (d) use one group only
27. 27.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
28. 28.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) add varied examples (d) test on one group only
29. 29.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
30. 30.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
31. 31.True or false: “add varied examples” adds to bias. (a) False (b) True
32. 32.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
34. 34.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
35. 35.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
36. 36.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
37. 37.Which of these adds to bias? (a) test on many groups (b) skip testing (c) check who is missing (d) ask different people
38. 38.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ignore complaints (d) copy old unfair choices
39. 39.Which of these helps reduce bias? (a) fix wrong labels (b) use one group only (c) copy old unfair choices (d) ignore complaints
40. 40.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) balance the data (d) check who is missing

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