AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 163 · 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.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
2. 2.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) balance the data (d) use one group only
3. 3.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
6. 6.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) copy old unfair choices (d) test on one group only
7. 7.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) few child voices in data (d) the phone was new
8. 8.Which of these adds to bias? (a) check who is missing (b) add more of the same (c) test on many groups (d) ask different people
9. 9.🖼️ 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
10. 10.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) the weather (d) its colour
11. 11.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
12. 12.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) use one group only (b) add varied examples (c) copy old unfair choices (d) test on one group only
14. 14.True or false: “balance the data” adds to bias. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) ask different people (d) use one group only
16. 16.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
17. 17.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
18. 18.True or false: “add more of the same” adds to bias. (a) True (b) False
19. 19.True or false: “ask different people” adds to bias. (a) True (b) False
20. 20.Which of these helps reduce bias? (a) fix wrong labels (b) ignore complaints (c) add more of the same (d) test on one group only
21. 21.🔍 Which is the odd one out? (a) ask different people (b) skip testing (c) use one group only (d) add more of the same
22. 22.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
23. 23.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) ask different people (d) check who is missing
25. 25.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) check who is missing (d) add varied examples
26. 26.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
27. 27.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
28. 28.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
29. 29.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
30. 30.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
31. 31.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
32. 32.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) fix wrong labels (d) ignore complaints
34. 34.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) ignore complaints (d) balance the data
35. 35.True or false: “add varied examples” adds to bias. (a) False (b) True
36. 36.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) add more of the same (d) copy old unfair choices
37. 37.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) skip testing (d) test on one group only
38. 38.True or false: “add varied examples” helps reduce bias. (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) test on many groups (b) skip testing (c) fix wrong labels (d) balance the data
40. 40.Which of these helps reduce bias? (a) test on one group only (b) test on many groups (c) ignore complaints (d) add more of the same

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