AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 966 · 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.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
2. 2.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
3. 3.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) use one group only (d) balance the data
5. 5.True or false: “skip testing” adds to bias. (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) fix wrong labels (b) test on many groups (c) check who is missing (d) ignore complaints
7. 7.🖼️ 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
8. 8.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
9. 9.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) the phone was new (c) children speak too fast (d) it was a rainy day
10. 10.Which of these helps reduce bias? (a) ignore complaints (b) test on many groups (c) test on one group only (d) skip testing
11. 11.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
12. 12.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) add more of the same (b) check who is missing (c) use one group only (d) skip testing
14. 14.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) False (b) True
15. 15.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
16. 16.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
17. 17.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
19. 19.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
20. 20.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
21. 21.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
22. 22.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) test on one group only (d) balance the data
23. 23.Which of these adds to bias? (a) copy old unfair choices (b) add varied examples (c) ask different people (d) balance the data
24. 24.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
25. 25.True or false: “balance the data” adds to bias. (a) True (b) False
26. 26.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
27. 27.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
28. 28.Which of these adds to bias? (a) balance the data (b) add varied examples (c) test on many groups (d) add more of the same
29. 29.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
30. 30.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
31. 31.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
32. 32.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
33. 33.Which of these helps reduce bias? (a) copy old unfair choices (b) fix wrong labels (c) test on one group only (d) skip testing
34. 34.True or false: “test on many groups” adds to bias. (a) False (b) True
35. 35.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) skip testing (d) fix wrong labels
36. 36.🔍 Which is the odd one out? (a) test on one group only (b) fix wrong labels (c) check who is missing (d) add varied examples
37. 37.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
38. 38.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
39. 39.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
40. 40.True or false: “ignore complaints” adds to bias. (a) True (b) False

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