AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 533 · 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) adds to bias (b) reduces bias
2. 2.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
3. 3.True or false: “check who is missing” helps reduce bias. (a) True (b) False
4. 4.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
5. 5.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
6. 6.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
7. 7.🗣️ 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) few child voices in data (d) children speak too fast
8. 8.🔍 Which is the odd one out? (a) fix wrong labels (b) test on one group only (c) add varied examples (d) balance the data
9. 9.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) a fair model (d) bias from data
11. 11.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) more varied data (c) one group only (d) fewer tests
12. 12.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
13. 13.Which of these helps reduce bias? (a) use one group only (b) balance the data (c) add more of the same (d) ignore complaints
14. 14.True or false: “check who is missing” adds to bias. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) ask different people (d) check who is missing
16. 16.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
17. 17.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
19. 19.True or false: “ask different people” adds to bias. (a) False (b) True
20. 20.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
21. 21.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) test on many groups (d) copy old unfair choices
22. 22.Which of these helps reduce bias? (a) add varied examples (b) ignore complaints (c) use one group only (d) skip testing
23. 23.True or false: “skip testing” adds to bias. (a) True (b) False
24. 24.True or false: “use one group only” helps reduce bias. (a) True (b) False
25. 25.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
26. 26.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
27. 27.Which of these adds to bias? (a) check who is missing (b) ask different people (c) fix wrong labels (d) use one group only
28. 28.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
29. 29.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
30. 30.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) add varied examples (d) use one group only
31. 31.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) skip testing (d) fix wrong labels
33. 33.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) test on one group only (d) test on many groups
34. 34.Which of these adds to bias? (a) test on many groups (b) skip testing (c) ask different people (d) add varied examples
35. 35.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
36. 36.Which of these helps reduce bias? (a) copy old unfair choices (b) check who is missing (c) skip testing (d) test on one group only
37. 37.True or false: “add varied examples” helps reduce bias. (a) True (b) False
38. 38.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) balance the data (d) add varied examples
39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) copy old unfair choices (b) add more of the same (c) check who is missing (d) ignore complaints

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