AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 791 · 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 of these is generative AI (it makes something new)? (a) unlocking with a face (b) spotting a sick leaf (c) spotting spam (d) making up a story
2. 2.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
3. 3.True or false: recognising a friend’s face in photos needs AI that learns from examples. (a) True (b) False
4. 4.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) a password (d) training data
6. 6.Which of these is not AI? (a) face unlock on a phone (b) a doorbell (c) an image generator (d) a map predicting traffic
7. 7.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it may get it wrong (d) it will be perfect
8. 8.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) predicting (c) drawing (d) sleeping
9. 9.True or false: “flagging a new email” is a prediction. (a) True (b) False
10. 10.Which of these helps reduce bias? (a) test on one group only (b) balance the data (c) skip testing (d) use one group only
11. 11.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) many varied examples (d) checking labels twice
12. 12.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
13. 13.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
14. 14.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
15. 15.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
16. 16.Which of these adds to bias? (a) ask different people (b) fix wrong labels (c) balance the data (d) skip testing
17. 17.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
18. 18.Which of these describes how AI works? (a) does exactly as coded (b) never learns from data (c) uses rules people wrote (d) spots patterns in data
19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) bias from data (d) a strong battery
20. 20.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
21. 21.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
22. 22.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
23. 23.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new
24. 24.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can make up facts (c) AI learns from data (d) AI has real feelings
25. 25.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
26. 26.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
27. 27.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) music or sound (b) text (c) an image
28. 28.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
29. 29.✨ Generative or not: creating a cartoon? (a) makes something new (b) sorts or predicts
30. 30.🔍 Which is the odd one out? (a) drafting a letter (b) unlocking with a face (c) writing a new poem (d) writing quiz questions
31. 31.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
32. 32.🛠️ Which does this job need: converting metres into centimetres? (a) needs AI (learning) (b) a simple rule is enough
33. 33.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
34. 34.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) only one kind of example (d) correct labels
35. 35.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
36. 36.True or false: “AI is never wrong” is a fact about AI. (a) False (b) True
37. 37.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
38. 38.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) generating (b) predicting (c) recommending (d) recognising
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam

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