AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 428 · 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 helps reduce bias? (a) use one group only (b) test on one group only (c) skip testing (d) add varied examples
2. 2.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) test on many groups (d) add more of the same
3. 3.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
5. 5.Which of these helps reduce bias? (a) ask different people (b) ignore complaints (c) skip testing (d) copy old unfair choices
6. 6.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) add varied examples (d) use one group only
7. 7.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
8. 8.Which of these adds to bias? (a) add varied examples (b) use one group only (c) fix wrong labels (d) check who is missing
9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
10. 10.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
12. 12.True or false: “check who is missing” adds to bias. (a) False (b) True
13. 13.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) ignore complaints (d) balance the data
14. 14.🖼️ 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
15. 15.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) use one group only (d) ask different people
16. 16.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) ignore complaints (d) balance the data
17. 17.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
18. 18.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
19. 19.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
20. 20.True or false: “add more of the same” adds to bias. (a) False (b) True
21. 21.Which of these helps reduce bias? (a) fix wrong labels (b) use one group only (c) test on one group only (d) copy old unfair choices
22. 22.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
24. 24.🔍 Which is the odd one out? (a) use one group only (b) test on many groups (c) copy old unfair choices (d) test on one group only
25. 25.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
26. 26.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
27. 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
29. 29.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
30. 30.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
31. 31.🗣️ 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) children speak too fast (d) few child voices in data
32. 32.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
33. 33.True or false: “ask different people” adds to bias. (a) False (b) True
34. 34.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
35. 35.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
37. 37.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) balance the data (d) ignore complaints
38. 38.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) check who is missing (d) add more of the same
39. 39.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
40. 40.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True

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