AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 607 · 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: skip testing? (a) reduces bias (b) adds to bias
2. 2.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
5. 5.🔍 Which is the odd one out? (a) test on one group only (b) ask different people (c) add more of the same (d) copy old unfair choices
6. 6.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) ignore complaints (d) fix wrong labels
7. 7.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
9. 9.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
10. 10.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
11. 11.True or false: “add varied examples” adds to bias. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) fix wrong labels (d) use one group only
13. 13.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
14. 14.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
15. 15.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
16. 16.Which of these helps reduce bias? (a) use one group only (b) ask different people (c) copy old unfair choices (d) ignore complaints
17. 17.Which of these adds to bias? (a) test on many groups (b) fix wrong labels (c) copy old unfair choices (d) balance the data
18. 18.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
19. 19.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
20. 20.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) fewer tests (d) one group only
21. 21.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its screen size (d) its colour
22. 22.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) balance the data (b) add more of the same (c) copy old unfair choices (d) ignore complaints
24. 24.True or false: “add varied examples” helps reduce bias. (a) True (b) False
25. 25.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) add more of the same (d) test on many groups
26. 26.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a broken screen (c) a strong battery (d) a fair model
27. 27.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) ask different people (d) add more of the same
28. 28.🔍 Which is the odd one out? (a) balance the data (b) skip testing (c) test on many groups (d) add varied examples
29. 29.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) add varied examples (d) ask different people
31. 31.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
32. 32.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
33. 33.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
34. 34.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
35. 35.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
36. 36.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
37. 37.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
38. 38.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
39. 39.Which of these adds to bias? (a) test on many groups (b) ignore complaints (c) add varied examples (d) fix wrong labels
40. 40.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True

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