AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 822 · 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.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
2. 2.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) test on many groups (b) skip testing (c) fix wrong labels (d) ask different people
4. 4.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
5. 5.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) balance the data (d) add more of the same
6. 6.True or false: “test on many groups” helps reduce bias. (a) False (b) True
7. 7.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) skip testing (d) balance the data
8. 8.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
9. 9.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) use one group only (d) test on many groups
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) a broken screen (d) bias from data
11. 11.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) ignore complaints (d) ask different people
12. 12.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its colour (d) its screen size
13. 13.Which of these adds to bias? (a) check who is missing (b) ask different people (c) test on one group only (d) fix wrong labels
14. 14.True or false: “add varied examples” helps reduce bias. (a) False (b) True
15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
16. 16.Which of these adds to bias? (a) use one group only (b) balance the data (c) check who is missing (d) add varied examples
17. 17.🛠️ What helps make an AI system fairer? (a) more varied data (b) one group only (c) ignoring mistakes (d) fewer tests
18. 18.True or false: “test on many groups” adds to bias. (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) test on many groups (d) ignore complaints
20. 20.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
21. 21.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
22. 22.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: “add varied examples” adds to bias. (a) True (b) False
24. 24.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
25. 25.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
26. 26.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
27. 27.True or false: “add more of the same” helps reduce bias. (a) True (b) False
28. 28.Which of these adds to bias? (a) skip testing (b) fix wrong labels (c) ask different people (d) add varied examples
29. 29.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) the phone was new (d) it was a rainy day
30. 30.Which of these helps reduce bias? (a) skip testing (b) check who is missing (c) ignore complaints (d) copy old unfair choices
31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
32. 32.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
33. 33.True or false: “use one group only” adds to bias. (a) False (b) True
34. 34.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
35. 35.Which of these adds to bias? (a) test on many groups (b) add more of the same (c) check who is missing (d) balance the data
36. 36.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) fix wrong labels (d) copy old unfair choices
38. 38.True or false: “skip testing” helps reduce bias. (a) False (b) True
39. 39.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) False (b) True
40. 40.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) add more of the same (d) add varied examples

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