AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 225 · 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.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
2. 2.Which of these adds to bias? (a) test on many groups (b) ignore complaints (c) fix wrong labels (d) add varied examples
3. 3.True or false: “uses rules people wrote” describes how a normal program works. (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) a digital watch (b) a fan regulator (c) a stopwatch (d) a voice assistant
5. 5.🛠️ Which does this job need: finding 10% of a price? (a) a simple rule is enough (b) needs AI (learning)
6. 6.Which of these helps reduce bias? (a) ignore complaints (b) check who is missing (c) skip testing (d) use one group only
7. 7.🔍 Which is the odd one out? (a) confident means correct (b) AI can make up facts (c) AI has real feelings (d) AI is never wrong
8. 8.🤖 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
9. 9.True or false: “it has a neat layout” is a real way to check an AI answer. (a) True (b) False
10. 10.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
11. 11.True or false: “never learns from data” describes how AI works. (a) True (b) False
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) many varied examples (d) only one kind of example
13. 13.✨ Generative or not: suggesting a video? (a) makes something new (b) sorts or predicts
14. 14.True or false: “ask your teacher” is NOT a real way to check an AI answer. (a) False (b) True
15. 15.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) checking labels twice (d) very few examples
16. 16.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
17. 17.🧮 Which of these is NOT AI? (a) a spam filter (b) face unlock (c) voice typing (d) a basic calculator
18. 18.True or false: “see if the book exists” is a real way to check an AI answer. (a) False (b) True
19. 19.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
20. 20.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) the weather (d) its screen size
21. 21.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) gives a likely answer (d) does exactly as coded
22. 22.True or false: “it sounds very sure” is a real way to check an AI answer. (a) False (b) True
23. 23.Which of these describes how AI works? (a) makes a best guess (b) uses rules people wrote (c) same steps every time (d) one set rule per case
24. 24.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
25. 25.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
26. 26.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) writing quiz questions (c) unlocking with a face (d) turning speech to text
27. 27.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
29. 29.🥭 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 will be perfect (d) it may get it wrong
30. 30.🔍 Which is the odd one out? (a) AI knows everything (b) AI can be wrong (c) AI has real feelings (d) AI always checks facts
31. 31.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
32. 32.Which of these is good for training a model? (a) examples of every type (b) only one kind of example (c) copies of one photo (d) testing on training data
33. 33.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
34. 34.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
35. 35.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
36. 36.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it learns from examples (c) it is always right (d) it uses electricity
37. 37.Which of these is the model? (a) recorded spoken words (b) what training builds (c) tomorrow’s rain guess (d) flagging a new email
38. 38.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to change its name (d) to make it slower
39. 39.🤖 AI or a normal program: which one “same steps every time”? (a) a normal program (b) AI
40. 40.✅ Is this a real check of an AI answer: it sounds very sure? (a) not a real check (b) a real check

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