AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 86 · 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: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
2. 2.True or false: “test on one group only” helps reduce bias. (a) False (b) True
3. 3.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) add varied examples
4. 4.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
5. 5.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) ask different people (d) use one group only
6. 6.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) use one group only (d) copy old unfair choices
7. 7.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
9. 9.🗣️ 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
10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
11. 11.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
12. 12.Which of these adds to bias? (a) ignore complaints (b) check who is missing (c) add varied examples (d) test on many groups
13. 13.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) fewer tests (d) one group only
14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
15. 15.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) its screen size (d) the weather
16. 16.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
17. 17.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
18. 18.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ignore complaints (d) add varied examples
20. 20.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
21. 21.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) test on many groups (d) skip testing
22. 22.True or false: “add more of the same” adds to bias. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) add varied examples (b) add more of the same (c) test on many groups (d) check who is missing
24. 24.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) ask different people (d) ignore complaints
25. 25.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
26. 26.Which of these adds to bias? (a) add varied examples (b) add more of the same (c) ask different people (d) balance the data
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.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
29. 29.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
30. 30.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
31. 31.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
32. 32.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.True or false: “fix wrong labels” adds to bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) test on one group only (b) add more of the same (c) use one group only (d) fix wrong labels
35. 35.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
36. 36.True or false: “ask different people” helps reduce bias. (a) False (b) True
37. 37.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
38. 38.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
39. 39.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
40. 40.True or false: “check who is missing” adds to bias. (a) False (b) True

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