AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 486 · 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: copy old unfair choices? (a) reduces bias (b) adds to bias
2. 2.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
3. 3.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
4. 4.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
5. 5.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
6. 6.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
7. 7.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) skip testing
8. 8.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
9. 9.Which of these helps reduce bias? (a) test on one group only (b) fix wrong labels (c) skip testing (d) copy old unfair choices
10. 10.Which of these adds to bias? (a) use one group only (b) fix wrong labels (c) balance the data (d) add varied examples
11. 11.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
12. 12.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
13. 13.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
15. 15.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
16. 16.🗣️ 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) the phone was new (d) children speak too fast
17. 17.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) add more of the same (d) balance the data
18. 18.🔍 Which is the odd one out? (a) test on many groups (b) ignore complaints (c) check who is missing (d) ask different people
19. 19.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
20. 20.True or false: “balance the data” helps reduce bias. (a) False (b) True
21. 21.True or false: “skip testing” helps reduce bias. (a) True (b) False
22. 22.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on many groups (d) add more of the same
23. 23.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
24. 24.True or false: “check who is missing” adds to bias. (a) True (b) False
25. 25.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
26. 26.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
27. 27.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
28. 28.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
29. 29.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ignore complaints (d) fix wrong labels
30. 30.True or false: “ask different people” adds to bias. (a) False (b) True
31. 31.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
32. 32.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
33. 33.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
34. 34.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
35. 35.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
36. 36.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) test on one group only (d) balance the data
37. 37.🔍 Which is the odd one out? (a) use one group only (b) copy old unfair choices (c) check who is missing (d) add more of the same
38. 38.True or false: “ignore complaints” adds to bias. (a) True (b) False
39. 39.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add varied examples (d) add more of the same

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