AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 266 · 40 questions

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

1. 1.🔍 Which is the odd one out? (a) correct labels (b) checking labels twice (c) blurry, unclear photos (d) clear, sharp examples
2. 2.🔍 Which is the odd one out? (a) long answers are true (b) AI knows everything (c) AI always checks facts (d) AI answers need checking
3. 3.🗣️ 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) it was a rainy day (d) the phone was new
4. 4.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
5. 5.True or false: an AI tool making a brand-new tune is AI generating something new. (a) False (b) True
6. 6.Which of these describes how AI works? (a) uses rules people wrote (b) follows fixed rules (c) learns from examples (d) does exactly as coded
7. 7.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a prediction (d) a label error
8. 8.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
9. 9.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
10. 10.🏠 AI or not AI: a printed timetable? (a) uses AI (b) not AI
11. 11.Which of these uses AI? (a) a light switch (b) a doorbell (c) voice typing (d) a kitchen weighing scale
12. 12.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
13. 13.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
14. 14.True or false: a music app suggesting a song you may like is AI predicting something. (a) False (b) True
15. 15.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
16. 16.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
17. 17.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
18. 18.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
19. 19.True or false: “AI answers need checking” is a myth about AI. (a) True (b) False
20. 20.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
21. 21.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
22. 22.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it is always right (c) it has a screen (d) it learns from examples
23. 23.True or false: turning your spoken words into typed text is AI generating something new. (a) True (b) False
24. 24.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
25. 25.🎨 An image generator makes a picture from… (a) a text description (b) your password (c) a phone number (d) the weather
26. 26.✍️ How does an AI chatbot write its replies? (a) asks a person (b) copies one website (c) uses magic (d) predicts likely words
27. 27.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
28. 28.True or false: spotting spam emails by their patterns only needs a simple fixed rule. (a) True (b) False
29. 29.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
30. 30.True or false: “very few examples” is bad for training a model. (a) False (b) True
31. 31.True or false: a phone unlocking when it sees your face is AI recognising something. (a) False (b) True
32. 32.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) drawing a new picture (c) reading number plates (d) unlocking with a face
33. 33.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
34. 34.🔍 Which is the odd one out? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) add varied examples
35. 35.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) wrong labels (d) new data for testing
36. 36.Which of these is training data? (a) what training builds (b) the trained program (c) old emails marked spam (d) flagging a new email
37. 37.True or false: translating a sentence into Hindi only needs a simple fixed rule. (a) False (b) True
38. 38.Which of these is a fact about AI? (a) AI has real feelings (b) AI knows everything (c) AI answers need checking (d) AI is never wrong
39. 39.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) False (b) True
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam

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