AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 973 · 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: check who is missing? (a) reduces bias (b) adds to bias
2. 2.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
4. 4.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) copy old unfair choices
5. 5.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
6. 6.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
7. 7.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) check who is missing
8. 8.True or false: “check who is missing” adds to bias. (a) False (b) True
9. 9.Which of these adds to bias? (a) ask different people (b) test on many groups (c) use one group only (d) fix wrong labels
10. 10.True or false: “add varied examples” helps reduce bias. (a) False (b) True
11. 11.True or false: “add varied examples” adds to bias. (a) True (b) False
12. 12.True or false: “skip testing” helps reduce bias. (a) True (b) False
13. 13.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) add more of the same (d) copy old unfair choices
15. 15.🔍 Which is the odd one out? (a) ignore complaints (b) copy old unfair choices (c) use one group only (d) balance the data
16. 16.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) use one group only
18. 18.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) use one group only (d) add more of the same
19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
20. 20.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
21. 21.True or false: “use one group only” helps reduce bias. (a) True (b) False
22. 22.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
23. 23.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
25. 25.🔍 Which is the odd one out? (a) ask different people (b) ignore complaints (c) copy old unfair choices (d) test on one group only
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” helps reduce bias. (a) False (b) True
28. 28.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
29. 29.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
30. 30.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
31. 31.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
32. 32.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
33. 33.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
34. 34.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) test on one group only (d) test on many groups
35. 35.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
36. 36.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) fix wrong labels (d) add more of the same
37. 37.True or false: “test on one group only” helps reduce bias. (a) True (b) False
38. 38.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
39. 39.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
40. 40.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias

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