AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 806 · 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: “test on many groups” helps reduce bias. (a) False (b) True
2. 2.🖼️ 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
3. 3.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
4. 4.Which of these helps reduce bias? (a) test on one group only (b) ignore complaints (c) use one group only (d) ask different people
5. 5.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) skip testing (c) balance the data (d) add varied examples
8. 8.True or false: “use one group only” helps reduce bias. (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) balance the data (d) add more of the same
10. 10.True or false: “test on one group only” adds to bias. (a) False (b) True
11. 11.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
12. 12.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) add varied examples (d) ignore complaints
14. 14.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
15. 15.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
16. 16.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) use one group only
17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
18. 18.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
19. 19.🗣️ 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
20. 20.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
21. 21.True or false: “test on one group only” helps reduce bias. (a) False (b) True
22. 22.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
23. 23.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
25. 25.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
26. 26.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
27. 27.True or false: “ignore complaints” adds to bias. (a) False (b) True
28. 28.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
29. 29.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) copy old unfair choices (b) fix wrong labels (c) add varied examples (d) balance the 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) True (b) False
32. 32.Which of these adds to bias? (a) test on one group only (b) check who is missing (c) balance the data (d) test on many groups
33. 33.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) use one group only (d) add more of the same
34. 34.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
35. 35.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
36. 36.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
37. 37.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
38. 38.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
39. 39.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
40. 40.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) check who is missing (d) fix wrong labels

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