AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 249 · 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: test on one group only? (a) adds to bias (b) reduces bias
2. 2.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
3. 3.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
4. 4.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
5. 5.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
6. 6.True or false: “add varied examples” helps reduce bias. (a) True (b) False
7. 7.🗣️ 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) children speak too fast (d) the phone was new
8. 8.🔍 Which is the odd one out? (a) check who is missing (b) test on many groups (c) fix wrong labels (d) copy old unfair choices
9. 9.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) use one group only (d) fix wrong labels
10. 10.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
11. 11.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) use one group only (d) add more of the same
12. 12.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
13. 13.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) test on one group only (d) add more of the same
14. 14.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on many groups (d) add more of the same
15. 15.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) test on many groups (d) ignore complaints
16. 16.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
17. 17.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
19. 19.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
20. 20.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
21. 21.Which of these adds to bias? (a) skip testing (b) test on many groups (c) add varied examples (d) balance the data
22. 22.True or false: “ignore complaints” adds to bias. (a) True (b) False
23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
24. 24.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
25. 25.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
26. 26.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
27. 27.True or false: “add varied examples” adds to bias. (a) True (b) False
28. 28.Which of these adds to bias? (a) add varied examples (b) use one group only (c) ask different people (d) fix wrong labels
29. 29.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
30. 30.True or false: “fix wrong labels” adds to bias. (a) False (b) True
31. 31.True or false: “balance the data” helps reduce bias. (a) True (b) False
32. 32.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
33. 33.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
34. 34.Which of these helps reduce bias? (a) add varied examples (b) use one group only (c) skip testing (d) add more of the same
35. 35.🔍 Which is the odd one out? (a) skip testing (b) ask different people (c) test on one group only (d) ignore complaints
36. 36.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
37. 37.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
38. 38.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) add more of the same (d) use one group only
39. 39.Which of these adds to bias? (a) add more of the same (b) check who is missing (c) add varied examples (d) ask different people
40. 40.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data

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