AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 601 · 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: check who is missing? (a) reduces bias (b) adds to bias
2. 2.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
3. 3.Which of these adds to bias? (a) ask different people (b) test on many groups (c) check who is missing (d) use one group only
4. 4.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) few child voices in data (c) the phone was new (d) it was a rainy day
6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
7. 7.True or false: “test on one group only” adds to bias. (a) True (b) False
8. 8.True or false: “add more of the same” adds to bias. (a) False (b) True
9. 9.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
10. 10.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
11. 11.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) one group only (c) fewer tests (d) more varied data
12. 12.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
13. 13.🔍 Which is the odd one out? (a) ask different people (b) test on many groups (c) check who is missing (d) skip testing
14. 14.🔍 Which is the odd one out? (a) balance the data (b) use one group only (c) check who is missing (d) add varied examples
15. 15.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) add more of the same (d) balance the data
16. 16.🔍 Which is the odd one out? (a) ask different people (b) check who is missing (c) fix wrong labels (d) test on one group only
17. 17.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
18. 18.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
19. 19.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
20. 20.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) fix wrong labels (d) test on one group only
21. 21.True or false: “fix wrong labels” adds to bias. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) copy old unfair choices (d) add more of the same
23. 23.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
24. 24.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
25. 25.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
26. 26.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) use one group only (d) add more of the same
27. 27.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
28. 28.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
29. 29.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) copy old unfair choices (d) add varied examples
30. 30.Which of these adds to bias? (a) ignore complaints (b) test on many groups (c) ask different people (d) balance the data
31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) ask different people (d) add varied examples
32. 32.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
33. 33.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
34. 34.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
35. 35.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
36. 36.True or false: “balance the data” adds to bias. (a) False (b) True
37. 37.True or false: “add varied examples” helps reduce bias. (a) True (b) False
38. 38.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
39. 39.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) test on many groups (d) test on one group only
40. 40.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students