AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 493 · 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.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) balance the data (d) test on one group only
3. 3.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a strong battery (c) bias from data (d) a broken screen
5. 5.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
6. 6.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
7. 7.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
8. 8.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
9. 9.True or false: “check who is missing” adds to bias. (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) add varied examples (d) add more of the same
11. 11.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
12. 12.Which of these adds to bias? (a) fix wrong labels (b) skip testing (c) balance the data (d) test on many groups
13. 13.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) fix wrong labels
14. 14.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) ask different people (d) use one group only
15. 15.True or false: “balance the data” adds to bias. (a) True (b) False
16. 16.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
17. 17.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
18. 18.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) add varied examples (d) balance the data
19. 19.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) the phone was new (d) children speak too fast
20. 20.True or false: “test on many groups” adds to bias. (a) True (b) False
21. 21.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
22. 22.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: “balance the data” helps reduce bias. (a) False (b) True
24. 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
25. 25.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
26. 26.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
28. 28.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
29. 29.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
30. 30.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
31. 31.True or false: “use one group only” helps reduce bias. (a) True (b) False
32. 32.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) copy old unfair choices (d) use one group only
33. 33.True or false: “check who is missing” helps reduce bias. (a) True (b) False
34. 34.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
35. 35.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
36. 36.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) test on many groups (d) skip testing
38. 38.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
39. 39.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
40. 40.🔍 Which is the odd one out? (a) ask different people (b) fix wrong labels (c) copy old unfair choices (d) balance the data

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