AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 431 · 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: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
2. 2.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
3. 3.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
4. 4.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
5. 5.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) fix wrong labels (d) check who is missing
6. 6.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
7. 7.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a fair model (d) a strong battery
8. 8.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
9. 9.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) ignore complaints (d) balance the data
10. 10.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
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) test on many groups (b) test on one group only (c) add more of the same (d) skip testing
14. 14.True or false: “test on many groups” adds to bias. (a) False (b) True
15. 15.True or false: “test on many groups” helps reduce bias. (a) False (b) True
16. 16.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
17. 17.True or false: “use one group only” adds to bias. (a) False (b) True
18. 18.True or false: “add varied examples” helps reduce bias. (a) False (b) True
19. 19.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
20. 20.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
22. 22.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
23. 23.🔍 Which is the odd one out? (a) balance the data (b) test on many groups (c) add varied examples (d) ignore complaints
24. 24.Which of these adds to bias? (a) skip testing (b) test on many groups (c) balance the data (d) ask different people
25. 25.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
26. 26.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
27. 27.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
29. 29.🔍 Which is the odd one out? (a) fix wrong labels (b) use one group only (c) copy old unfair choices (d) skip testing
30. 30.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
31. 31.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
32. 32.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) fix wrong labels (d) copy old unfair choices
33. 33.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
34. 34.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) test on one group only (d) add varied examples
35. 35.True or false: “fix wrong labels” adds to bias. (a) False (b) True
36. 36.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
37. 37.True or false: “use one group only” helps reduce bias. (a) True (b) False
38. 38.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) add varied examples (d) fix wrong labels
39. 39.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
40. 40.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) skip testing (d) ignore complaints

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