AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 567 · 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.True or false: “it uses big words” is NOT a real way to check an AI answer. (a) False (b) True
2. 2.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) sorting photos by face (c) writing a new poem (d) drawing a new picture
3. 3.🔍 Which is the odd one out? (a) spotting spam (b) creating a cartoon (c) writing a new poem (d) drawing a new picture
4. 4.True or false: “very few examples” is good for training a model. (a) False (b) True
5. 5.Which of these is a myth about AI? (a) AI copies data patterns (b) AI can mix up numbers (c) AI can make up facts (d) long answers are true
6. 6.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
7. 7.🔍 Which is the odd one out? (a) ignore complaints (b) skip testing (c) fix wrong labels (d) test on one group only
8. 8.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) uses magic (c) asks a person (d) copies one website
9. 9.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
10. 10.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
11. 11.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
12. 12.Which of these is a myth about AI? (a) confident means correct (b) AI copies data patterns (c) AI can make up facts (d) AI answers need checking
13. 13.Which of these adds to bias? (a) ignore complaints (b) balance the data (c) add varied examples (d) test on many groups
14. 14.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
15. 15.Which of these is a prediction? (a) typing a new spoken word (b) 500 labelled leaf photos (c) recorded spoken words (d) labelled fruit photos
16. 16.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) copies of one photo (d) checking labels twice
17. 17.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) music or sound (b) text (c) an image
18. 18.Which of these is a fact about AI? (a) AI has real feelings (b) AI can be wrong (c) AI is never wrong (d) AI always checks facts
19. 19.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recognising (b) predicting (c) recommending (d) generating
20. 20.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) testing on training data (d) checking labels twice
21. 21.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
22. 22.Which of these describes how a normal program works? (a) same steps every time (b) makes a best guess (c) improves with more data (d) learns from examples
23. 23.True or false: “what training builds” is the model. (a) False (b) True
24. 24.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recognising (b) recommending (c) generating (d) predicting
25. 25.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) its colour (d) the weather
26. 26.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
27. 27.Which of these is not AI? (a) a microwave timer (b) face unlock on a phone (c) photos grouped by face (d) an app translating signs
28. 28.True or false: “long answers are true” is a fact about AI. (a) False (b) True
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
30. 30.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) an image (b) text (c) music or sound
31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
32. 32.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) drawing a new picture (c) composing a new tune (d) suggesting a video
33. 33.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) balance the data (d) add varied examples
34. 34.Which of these is the model? (a) old emails marked spam (b) labelled fruit photos (c) the learned patterns (d) flagging a new email
35. 35.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
36. 36.True or false: “never learns from data” describes how a normal program works. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) face unlock on a phone (b) photos grouped by face (c) a digital watch (d) an AI chatbot
38. 38.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
40. 40.Which of these is generative AI (it makes something new)? (a) turning speech to text (b) writing a new poem (c) predicting rain (d) reading number plates

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