AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 997 · 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.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
2. 2.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) add more of the same (d) copy old unfair choices
3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
4. 4.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
5. 5.🔍 Which is the odd one out? (a) test on many groups (b) balance the data (c) ignore complaints (d) add varied examples
6. 6.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) test on many groups (d) copy old unfair choices
7. 7.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
8. 8.Which of these adds to bias? (a) check who is missing (b) copy old unfair choices (c) balance the data (d) test on many groups
9. 9.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
10. 10.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
11. 11.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) ignore complaints (d) copy old unfair choices
12. 12.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
13. 13.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
14. 14.True or false: “use one group only” adds to bias. (a) True (b) False
15. 15.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
16. 16.True or false: “use one group only” helps reduce bias. (a) True (b) False
17. 17.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
18. 18.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
20. 20.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) test on one group only (d) balance the data
21. 21.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
22. 22.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
23. 23.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
24. 24.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
25. 25.True or false: “test on one group only” helps reduce bias. (a) False (b) True
26. 26.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
27. 27.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
28. 28.True or false: “add more of the same” adds to bias. (a) True (b) False
29. 29.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) test on one group only (d) ask different people
30. 30.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
31. 31.🖼️ 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
32. 32.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
34. 34.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
35. 35.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
36. 36.Which of these helps reduce bias? (a) fix wrong labels (b) use one group only (c) ignore complaints (d) skip testing
37. 37.True or false: “balance the data” adds to bias. (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
39. 39.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
40. 40.Which of these adds to bias? (a) balance the data (b) ask different people (c) add varied examples (d) ignore complaints

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