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