AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 577 · 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.🗣️ 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
2. 2.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) check who is missing (d) test on many groups
4. 4.True or false: “test on many groups” helps reduce bias. (a) True (b) False
5. 5.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
6. 6.Which of these helps reduce bias? (a) add more of the same (b) add varied examples (c) test on one group only (d) ignore complaints
7. 7.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) test on many groups (d) add more of the same
8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
9. 9.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
10. 10.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) add varied examples (d) skip testing
11. 11.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
12. 12.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
13. 13.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
14. 14.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
15. 15.🛠️ What helps make an AI system fairer? (a) fewer tests (b) ignoring mistakes (c) more varied data (d) one group only
16. 16.🔍 Which is the odd one out? (a) use one group only (b) add more of the same (c) test on many groups (d) skip testing
17. 17.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
19. 19.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
20. 20.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) copy old unfair choices (d) test on many groups
21. 21.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
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: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
25. 25.True or false: “ask different people” adds to bias. (a) False (b) True
26. 26.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) add more of the same (d) test on many groups
27. 27.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
28. 28.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
29. 29.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) balance the data (d) test on one group only
30. 30.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
31. 31.True or false: “add varied examples” adds to bias. (a) False (b) True
32. 32.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on one group only (d) check who is missing
33. 33.True or false: “fix wrong labels” adds to bias. (a) True (b) False
34. 34.True or false: “add more of the same” helps reduce bias. (a) True (b) False
35. 35.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
36. 36.True or false: “test on one group only” helps reduce bias. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) test on one group only (d) skip testing
38. 38.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
39. 39.True or false: “ignore complaints” adds to bias. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) skip testing (d) add more of the same

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