AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 640 · 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) test on one group only (b) skip testing (c) check who is missing (d) use one group only
2. 2.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
3. 3.🔍 Which is the odd one out? (a) ask different people (b) balance the data (c) add varied examples (d) test on one group only
4. 4.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
5. 5.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
6. 6.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
8. 8.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
9. 9.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) test on one group only (d) fix wrong labels
10. 10.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
11. 11.Which of these helps reduce bias? (a) ignore complaints (b) fix wrong labels (c) add more of the same (d) skip testing
12. 12.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
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.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
15. 15.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
16. 16.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) ignore complaints (d) add varied examples
17. 17.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
18. 18.Which of these adds to bias? (a) balance the data (b) add more of the same (c) test on many groups (d) fix wrong labels
19. 19.Which of these helps reduce bias? (a) add more of the same (b) ask different people (c) ignore complaints (d) copy old unfair choices
20. 20.True or false: “test on many groups” adds to bias. (a) False (b) True
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
22. 22.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) balance the data (d) use one group only
23. 23.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
24. 24.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
25. 25.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
26. 26.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
27. 27.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.True or false: “add more of the same” adds to bias. (a) False (b) True
29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
30. 30.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
31. 31.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
32. 32.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
33. 33.True or false: “add more of the same” helps reduce bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) add more of the same (d) skip testing
35. 35.Which of these helps reduce bias? (a) add varied examples (b) copy old unfair choices (c) use one group only (d) test on one group only
36. 36.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) balance the data (d) ask different people
38. 38.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) copy old unfair choices (d) ignore complaints
39. 39.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) add varied examples (d) ask different people
40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data

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