AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 427 · 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.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ask different people (d) copy old unfair choices
2. 2.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) test on many groups (d) use one group only
3. 3.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
4. 4.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
5. 5.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
6. 6.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
7. 7.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
8. 8.True or false: “ask different people” adds to bias. (a) True (b) False
9. 9.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
10. 10.Which of these helps reduce bias? (a) ignore complaints (b) copy old unfair choices (c) test on one group only (d) add varied examples
11. 11.True or false: “add varied examples” adds to bias. (a) True (b) False
12. 12.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
13. 13.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
14. 14.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
16. 16.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
17. 17.Which of these helps reduce bias? (a) balance the data (b) test on one group only (c) skip testing (d) ignore complaints
18. 18.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
19. 19.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) test on many groups (d) copy old unfair choices
20. 20.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
22. 22.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
23. 23.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
24. 24.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
25. 25.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
26. 26.True or false: “use one group only” helps reduce bias. (a) True (b) False
27. 27.🗣️ 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) children speak too fast (d) few child voices in data
28. 28.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) test on one group only (d) use one group only
29. 29.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) use one group only (d) copy old unfair choices
30. 30.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
31. 31.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
32. 32.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.True or false: “skip testing” helps reduce bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) copy old unfair choices (b) fix wrong labels (c) test on one group only (d) add more of the same
35. 35.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
36. 36.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) check who is missing (d) test on one group only
37. 37.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
38. 38.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) copy old unfair choices (d) test on one group only
39. 39.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
40. 40.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data

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