AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 602 · 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 of these adds to bias? (a) fix wrong labels (b) add varied examples (c) add more of the same (d) check who is missing
2. 2.Which of these adds to bias? (a) test on many groups (b) ask different people (c) check who is missing (d) copy old unfair choices
3. 3.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
5. 5.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
6. 6.True or false: “test on one group only” adds to bias. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) ask different people (d) balance the data
8. 8.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
9. 9.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) ask different people (d) ignore complaints
10. 10.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) skip testing (d) add more of the same
11. 11.🔍 Which is the odd one out? (a) ignore complaints (b) test on one group only (c) add more of the same (d) ask different people
12. 12.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) test on many groups (d) use one group only
13. 13.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) test on many groups (d) ask different people
14. 14.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
15. 15.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
16. 16.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
17. 17.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
18. 18.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
19. 19.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
21. 21.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
22. 22.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
25. 25.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) fix wrong labels (d) copy old unfair choices
26. 26.True or false: “use one group only” helps reduce bias. (a) True (b) False
27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
28. 28.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
29. 29.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
30. 30.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
31. 31.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
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.True or false: “check who is missing” helps reduce bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) skip testing (b) add more of the same (c) use one group only (d) balance the data
35. 35.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
36. 36.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) add varied examples (d) test on one group only
37. 37.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) True (b) False
38. 38.Which of these adds to bias? (a) ask different people (b) skip testing (c) test on many groups (d) fix wrong labels
39. 39.Which of these adds to bias? (a) use one group only (b) fix wrong labels (c) check who is missing (d) test on many groups
40. 40.True or false: “fix wrong labels” adds to bias. (a) True (b) False

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