AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 693 · 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.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) the Moon (d) people
2. 2.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
3. 3.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
4. 4.True or false: “a cheerful tune for Sports Day” asks for text. (a) False (b) True
5. 5.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) yes, just like us (c) no, it finds patterns (d) yes, it gets sad
6. 6.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
7. 7.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
8. 8.Which of these uses AI? (a) a microwave timer (b) a torch (c) a calculator (d) video suggestions
9. 9.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
11. 11.True or false: “check who is missing” helps reduce bias. (a) False (b) True
12. 12.Which of these is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) drawing a new picture (c) unlocking with a face (d) creating a cartoon
13. 13.🔮 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
14. 14.⏩ In machine learning, which comes first: recorded spoken words or naming a new fruit photo? (a) recorded spoken words (b) naming a new fruit photo
15. 15.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
16. 16.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
17. 17.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
18. 18.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) spotting spam (c) writing quiz questions (d) unlocking with a face
19. 19.True or false: “AI can make up facts” is a myth about AI. (a) True (b) False
20. 20.Which of these is bad for training a model? (a) testing on training data (b) photos in many lights (c) new data for testing (d) many varied examples
21. 21.Which of these is not AI? (a) an app translating signs (b) a voice assistant (c) face unlock on a phone (d) a printed timetable
22. 22.🧮 Which of these is NOT AI? (a) a spam filter (b) a basic calculator (c) face unlock (d) voice typing
23. 23.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
24. 24.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
25. 25.Which of these uses AI? (a) a fan regulator (b) photos grouped by face (c) a kitchen weighing scale (d) a digital watch
26. 26.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
27. 27.🏠 AI or not AI: photos grouped by face? (a) not AI (b) uses AI
28. 28.Which of these is not AI? (a) photos grouped by face (b) an image generator (c) face unlock on a phone (d) a microwave timer
29. 29.Which of these describes how a normal program works? (a) improves with more data (b) spots patterns in data (c) handles unseen examples (d) uses rules people wrote
30. 30.True or false: “old emails marked spam” is training data. (a) True (b) False
31. 31.Which of these is bad for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) photos in many lights (d) new data for testing
32. 32.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
33. 33.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
34. 34.✨ Is everything a generative AI makes true? (a) no, it can be wrong (b) yes, always (c) only on Mondays
35. 35.Which of these describes how AI works? (a) same steps every time (b) makes a best guess (c) one set rule per case (d) never learns from data
36. 36.🔍 Which is the odd one out? (a) correct labels (b) copies of one photo (c) new data for testing (d) many varied examples
37. 37.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
38. 38.Which of these is a prediction? (a) 500 labelled leaf photos (b) the trained program (c) old emails marked spam (d) naming a new leaf
39. 39.True or false: showing the time on a clock only needs a simple fixed rule. (a) True (b) False
40. 40.True or false: “ignore complaints” adds to bias. (a) True (b) False

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