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