AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 626 · 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) video suggestions (b) a doorbell (c) a digital watch (d) a stopwatch
2. 2.Which of these uses AI? (a) photos grouped by face (b) a digital watch (c) a calculator (d) a fan regulator
3. 3.True or false: a car camera reading a speed sign is AI recognising something. (a) True (b) False
4. 4.Which of these is AI that sorts, spots or predicts (not generative)? (a) reading number plates (b) composing a new tune (c) writing quiz questions (d) drawing a new picture
5. 5.📦 What happens during training? (a) it prints labels (b) it charges up (c) it takes photos (d) it learns patterns
6. 6.🤖 What does AI stand for? (a) automatic internet (b) actual information (c) app installer (d) artificial intelligence
7. 7.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) wrong labels (d) correct labels
8. 8.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
9. 9.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False
10. 10.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
11. 11.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
12. 12.Which of these is AI that sorts, spots or predicts (not generative)? (a) turning speech to text (b) making up a story (c) composing a new tune (d) writing a new poem
13. 13.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
15. 15.🧮 Is a basic calculator an AI system? (a) no, it follows rules (b) yes, it can think (c) only at night (d) yes, it is smart
16. 16.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
17. 17.True or false: “AI is never wrong” is a fact about AI. (a) True (b) False
18. 18.💬 What do we call the request you type to a generative AI? (a) a label (b) a password (c) a battery (d) a prompt
19. 19.Which of these is training data? (a) recorded spoken words (b) naming a new fruit photo (c) tomorrow’s rain guess (d) typing a new spoken word
20. 20.🔍 Which is the odd one out? (a) a calculator (b) voice typing (c) video suggestions (d) an AI chatbot
21. 21.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
22. 22.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
23. 23.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
24. 24.True or false: spotting spam emails by their patterns only needs a simple fixed rule. (a) False (b) True
25. 25.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) printing (c) cooking (d) charging
26. 26.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
27. 27.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the textbook (b) share it online (c) stop studying (d) trust the AI
28. 28.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) ask it to hurry (c) never do maths (d) check it on paper
29. 29.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) AI can make up facts (b) AI answers need checking (c) AI learns from data (d) AI always checks facts
31. 31.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) checking labels twice (d) labels added at random
32. 32.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
33. 33.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
34. 34.True or false: “ask different people” adds to bias. (a) True (b) False
35. 35.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) checking labels twice (d) copies of one photo
37. 37.🔍 Which is the odd one out? (a) AI is never wrong (b) AI can mix up numbers (c) AI knows everything (d) confident means correct
38. 38.True or false: “improves with more data” describes how AI works. (a) False (b) True
39. 39.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
40. 40.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) the trained program (d) typing a new spoken word

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