AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 967 · 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: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
2. 2.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) ask different people (d) use one group only
3. 3.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) ignore complaints (d) use one group only
4. 4.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) it was a rainy day (c) the phone was new (d) children speak too fast
6. 6.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) fix wrong labels (d) balance the data
7. 7.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
8. 8.Which of these helps reduce bias? (a) use one group only (b) fix wrong labels (c) test on one group only (d) copy old unfair choices
9. 9.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
10. 10.Which of these adds to bias? (a) test on many groups (b) ask different people (c) copy old unfair choices (d) balance the data
11. 11.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
12. 12.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) skip testing (d) add varied examples
14. 14.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
15. 15.🔍 Which is the odd one out? (a) balance the data (b) copy old unfair choices (c) check who is missing (d) add varied examples
16. 16.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its colour (d) its training data
17. 17.🛠️ What helps make an AI system fairer? (a) more varied data (b) ignoring mistakes (c) one group only (d) fewer tests
18. 18.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
19. 19.Which of these adds to bias? (a) add varied examples (b) fix wrong labels (c) ask different people (d) test on one group only
20. 20.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
21. 21.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
22. 22.True or false: “add varied examples” adds to bias. (a) False (b) True
23. 23.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
24. 24.Which of these adds to bias? (a) ask different people (b) add varied examples (c) check who is missing (d) ignore complaints
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: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
27. 27.Which of these helps reduce bias? (a) ask different people (b) use one group only (c) test on one group only (d) copy old unfair choices
28. 28.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) add varied examples (d) fix wrong labels
29. 29.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
30. 30.True or false: “balance the data” adds to bias. (a) True (b) False
31. 31.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
32. 32.True or false: “check who is missing” adds to bias. (a) True (b) False
33. 33.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a broken screen (d) a fair model
34. 34.Which of these helps reduce bias? (a) skip testing (b) add more of the same (c) check who is missing (d) use one group only
35. 35.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
36. 36.True or false: “use one group only” adds to bias. (a) False (b) True
37. 37.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
39. 39.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
40. 40.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True

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