AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 389 · 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.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
2. 2.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) no, check it anyway (c) yes, if it is long
3. 3.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
4. 4.True or false: “AI can be wrong” is a fact about AI. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) photos in many lights (b) labels added at random (c) correct labels (d) examples of every type
6. 6.Which of these is generative AI (it makes something new)? (a) composing a new tune (b) reading number plates (c) unlocking with a face (d) sorting photos by face
7. 7.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) inventing a recipe (b) drawing a new picture (c) drafting a letter (d) predicting rain
9. 9.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) drawing (c) sleeping (d) predicting
10. 10.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
11. 11.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it uses electricity (c) it learns from examples (d) it has a screen
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
13. 13.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
14. 14.Which of these is AI that sorts, spots or predicts (not generative)? (a) drafting a letter (b) composing a new tune (c) inventing a recipe (d) suggesting a video
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
16. 16.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its screen size (c) its training data (d) the weather
17. 17.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
18. 18.True or false: “a logo idea for the eco club” asks for an image. (a) False (b) True
19. 19.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
20. 20.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) False (b) True
21. 21.🧐 Fact or myth: “AI can mix up numbers”? (a) a fact (b) a myth
22. 22.✅ Is this a real check of an AI answer: it sounds very sure? (a) a real check (b) not a real check
23. 23.Which of these is AI that sorts, spots or predicts (not generative)? (a) creating a cartoon (b) inventing a recipe (c) drafting a letter (d) predicting rain
24. 24.True or false: a music app suggesting a song you may like is AI predicting something. (a) False (b) True
25. 25.🧮 Which of these is NOT AI? (a) a spam filter (b) face unlock (c) voice typing (d) a basic calculator
26. 26.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
27. 27.Which of these is a myth about AI? (a) AI learns from data (b) AI can make up facts (c) AI can be wrong (d) AI always checks facts
28. 28.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) very few examples (d) many varied examples
29. 29.Which of these is a myth about AI? (a) long answers are true (b) AI can make up facts (c) AI can mix up numbers (d) AI answers need checking
30. 30.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
31. 31.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) wrong labels (d) blurry, unclear photos
32. 32.🔍 Which is the odd one out? (a) AI knows everything (b) AI can make up facts (c) AI always checks facts (d) AI is never wrong
33. 33.Which of these is a myth about AI? (a) AI answers need checking (b) AI copies data patterns (c) AI can be wrong (d) confident means correct
34. 34.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) never do maths (c) check it on paper (d) ask it to hurry
35. 35.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) check who is missing (d) test on one group only
36. 36.True or false: “AI can make up facts” is a myth about AI. (a) False (b) True
37. 37.Which of these describes how AI works? (a) follows fixed rules (b) learns from examples (c) same steps every time (d) never learns from data
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
39. 39.Which of these is a fact about AI? (a) AI has real feelings (b) long answers are true (c) AI can make up facts (d) AI always checks facts
40. 40.Which of these describes how AI works? (a) same steps every time (b) one set rule per case (c) uses rules people wrote (d) handles unseen examples

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