AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 674 · 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.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
2. 2.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
3. 3.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
4. 4.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
5. 5.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
6. 6.🔍 Which is the odd one out? (a) copy old unfair choices (b) fix wrong labels (c) test on one group only (d) ignore complaints
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) test on many groups (d) add varied examples
8. 8.True or false: “add more of the same” helps reduce bias. (a) False (b) True
9. 9.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
10. 10.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
11. 11.🔍 Which is the odd one out? (a) test on many groups (b) add more of the same (c) check who is missing (d) add varied examples
12. 12.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) use one group only (d) balance the data
14. 14.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
15. 15.🔍 Which is the odd one out? (a) test on many groups (b) skip testing (c) test on one group only (d) ignore complaints
16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
17. 17.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ignore complaints (d) add more of the same
18. 18.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
20. 20.True or false: “use one group only” adds to bias. (a) True (b) False
21. 21.Which of these helps reduce bias? (a) balance the data (b) copy old unfair choices (c) ignore complaints (d) use one group only
22. 22.True or false: “ask different people” helps reduce bias. (a) False (b) True
23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
24. 24.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
25. 25.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
26. 26.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
27. 27.Which of these adds to bias? (a) ask different people (b) skip testing (c) check who is missing (d) balance the data
28. 28.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) the phone was new (d) children speak too fast
29. 29.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
30. 30.True or false: “add varied examples” adds to bias. (a) True (b) False
31. 31.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
33. 33.Which of these adds to bias? (a) add varied examples (b) ignore complaints (c) fix wrong labels (d) test on many groups
34. 34.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
35. 35.True or false: “test on one group only” helps reduce bias. (a) False (b) True
36. 36.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
37. 37.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
38. 38.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
39. 39.Which of these helps reduce bias? (a) check who is missing (b) ignore complaints (c) use one group only (d) add more of the same
40. 40.True or false: “add varied examples” helps reduce bias. (a) True (b) False

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