AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 89 · 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) ask different people (b) copy old unfair choices (c) test on many groups (d) fix wrong labels
2. 2.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
3. 3.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
5. 5.True or false: “fix wrong labels” adds to bias. (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) skip testing (d) balance the data
7. 7.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
8. 8.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
9. 9.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
10. 10.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
11. 11.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
12. 12.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
13. 13.🗣️ 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) it was a rainy day (d) the phone was new
14. 14.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
16. 16.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
17. 17.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
18. 18.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
20. 20.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
21. 21.True or false: “skip testing” adds to bias. (a) True (b) False
22. 22.True or false: “ignore complaints” adds to bias. (a) True (b) False
23. 23.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) test on one group only (d) copy old unfair choices
24. 24.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) use one group only (d) balance the data
25. 25.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
26. 26.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
27. 27.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) check who is missing (d) fix wrong labels
28. 28.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
29. 29.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
30. 30.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
31. 31.Which of these adds to bias? (a) ask different people (b) test on many groups (c) add varied examples (d) use one group only
32. 32.Which of these helps reduce bias? (a) skip testing (b) add varied examples (c) add more of the same (d) use one group only
33. 33.Which of these adds to bias? (a) check who is missing (b) ask different people (c) ignore complaints (d) test on many groups
34. 34.🔍 Which is the odd one out? (a) add varied examples (b) add more of the same (c) test on one group only (d) use one group only
35. 35.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
36. 36.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided 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) copy old unfair choices (b) use one group only (c) test on many groups (d) skip testing
39. 39.🔍 Which is the odd one out? (a) test on one group only (b) add varied examples (c) ask different people (d) test on many groups
40. 40.Which of these adds to bias? (a) ask different people (b) add more of the same (c) add varied examples (d) balance the data

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