AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 139 · 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.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
2. 2.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) add varied examples (d) skip testing
4. 4.🔍 Which is the odd one out? (a) balance the data (b) ignore complaints (c) add varied examples (d) check who is missing
5. 5.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
6. 6.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
7. 7.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
8. 8.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
10. 10.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) False (b) True
11. 11.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
12. 12.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
13. 13.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
14. 14.🔍 Which is the odd one out? (a) copy old unfair choices (b) ignore complaints (c) ask different people (d) test on one group only
15. 15.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
16. 16.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
17. 17.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
19. 19.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) use one group only (d) copy old unfair choices
20. 20.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
21. 21.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) add varied examples (d) test on one group only
22. 22.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
23. 23.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
24. 24.Which of these adds to bias? (a) test on many groups (b) balance the data (c) ask different people (d) skip testing
25. 25.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
26. 26.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) ask different people (d) skip testing
27. 27.True or false: “ask different people” helps reduce bias. (a) False (b) True
28. 28.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
29. 29.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
30. 30.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
31. 31.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
32. 32.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) copy old unfair choices (d) check who is missing
33. 33.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) add more of the same (d) test on many groups
35. 35.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
36. 36.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
37. 37.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
38. 38.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
39. 39.True or false: “test on many groups” adds to bias. (a) False (b) True
40. 40.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False

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