AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 104 · 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.🔍 Which is the odd one out? (a) balance the data (b) check who is missing (c) add more of the same (d) add varied examples
2. 2.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
3. 3.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
6. 6.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
7. 7.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
8. 8.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) use one group only (d) ask different people
9. 9.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) balance the data (d) fix wrong labels
10. 10.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
11. 11.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
12. 12.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) copy old unfair choices (d) check who is missing
15. 15.True or false: “test on one group only” adds to bias. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) skip testing (d) use one group only
17. 17.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a broken screen (d) a strong battery
18. 18.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
20. 20.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
21. 21.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
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.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
24. 24.True or false: “use one group only” helps reduce bias. (a) True (b) False
25. 25.🔍 Which is the odd one out? (a) test on one group only (b) use one group only (c) ask different people (d) ignore complaints
26. 26.Which of these helps reduce bias? (a) skip testing (b) check who is missing (c) use one group only (d) test on one group only
27. 27.🗣️ 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
28. 28.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
29. 29.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
30. 30.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
31. 31.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
32. 32.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
33. 33.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) check who is missing (d) ask different people
34. 34.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) fix wrong labels
35. 35.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
36. 36.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) one group only (d) more varied data
37. 37.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
38. 38.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) fix wrong labels (d) skip testing
39. 39.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
40. 40.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data

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