AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 503 · 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.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
2. 2.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) yes (c) no
3. 3.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
4. 4.🔍 Which is the odd one out? (a) an image generator (b) a digital watch (c) a printed timetable (d) a fan regulator
5. 5.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
6. 6.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
7. 7.🧐 Fact or myth: “long answers are true”? (a) a fact (b) a myth
8. 8.🔍 Which is the odd one out? (a) an AI chatbot (b) photos grouped by face (c) a spam filter (d) a microwave timer
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
10. 10.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
11. 11.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) generating (b) predicting (c) recommending (d) recognising
12. 12.📱 What is the AI doing here: a camera app naming the flower you point at? (a) generating (b) recommending (c) predicting (d) recognising
13. 13.🔍 Which is the odd one out? (a) a microwave timer (b) a light switch (c) an app translating signs (d) a calculator
14. 14.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI can make up facts (c) AI learns from data (d) AI has real feelings
15. 15.True or false: “very few examples” is good for training a model. (a) False (b) True
16. 16.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
17. 17.True or false: “a summary of chapter 3” asks for text. (a) False (b) True
18. 18.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
19. 19.💬 What do we call the request you type to a generative AI? (a) a label (b) a prompt (c) a password (d) a battery
20. 20.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) check it on paper (c) copy it straight away (d) ask it to hurry
21. 21.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) music or sound (b) an image (c) text
22. 22.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
23. 23.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
24. 24.True or false: converting metres into centimetres needs AI that learns from examples. (a) False (b) True
25. 25.True or false: “naming a new leaf” is a prediction. (a) True (b) False
26. 26.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) bias from data (d) a strong battery
27. 27.🏠 AI or not AI: face unlock on a phone? (a) uses AI (b) not AI
28. 28.Which of these is a prediction? (a) flagging a new email (b) old emails marked spam (c) the trained program (d) 500 labelled leaf photos
29. 29.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) music or sound (b) an image (c) text
30. 30.Which of these is generative AI (it makes something new)? (a) spotting spam (b) turning speech to text (c) making up a story (d) reading number plates
31. 31.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) few child voices in data (d) children speak too fast
32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) balance the data (c) add varied examples (d) use one group only
34. 34.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) labels added at random (d) many varied examples
35. 35.True or false: “examples of every type” is good for training a model. (a) True (b) False
36. 36.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
37. 37.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) examples of every type (d) clear, sharp examples
38. 38.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) ask different people (d) ignore complaints
39. 39.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
40. 40.Which of these is not AI? (a) a spam filter (b) an app translating signs (c) face unlock on a phone (d) a kitchen weighing scale

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