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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 132 · 40 questions
TalentJR

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.

NameDateTime takenScore ___ / 40
  1. 1.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
  2. 2.🔍 Which is the odd one out? (a) a light switch (b) photos grouped by face (c) a torch (d) a stopwatch
  3. 3.🤖 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
  4. 4.🔍 Which is the odd one out? (a) add more of the same (b) ignore complaints (c) copy old unfair choices (d) test on many groups
  5. 5.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  6. 6.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) recommending (b) predicting (c) recognising (d) generating
  7. 7.✨ Is everything a generative AI makes true? (a) only on Mondays (b) yes, always (c) no, it can be wrong
  8. 8.Which of these describes how AI works? (a) never learns from data (b) learns from examples (c) follows fixed rules (d) uses rules people wrote
  9. 9.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
  10. 10.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  11. 11.True or false: “what training builds” is a prediction. (a) False (b) True
  12. 12.🔍 Which is the odd one out? (a) long answers are true (b) AI knows everything (c) AI has real feelings (d) AI can make up facts
  13. 13.True or false: “write a poem about the monsoon” asks for text. (a) False (b) True
  14. 14.🛠️ Which does this job need: sorting names in A to Z order? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.True or false: “a cheerful tune for Sports Day” asks for an image. (a) True (b) False
  16. 16.Which of these is a fact about AI? (a) AI has real feelings (b) confident means correct (c) AI learns from data (d) AI always checks facts
  17. 17.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
  18. 18.True or false: “makes a best guess” describes how a normal program works. (a) True (b) False
  19. 19.🔍 Which is the odd one out? (a) a digital watch (b) voice typing (c) photos grouped by face (d) an AI chatbot
  20. 20.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  21. 21.True or false: “it uses big words” is a real way to check an AI answer. (a) True (b) False
  22. 22.🛠️ What helps make an AI system fairer? (a) one group only (b) more varied data (c) fewer tests (d) ignoring mistakes
  23. 23.True or false: “does exactly as coded” describes how AI works. (a) True (b) False
  24. 24.✅ Is this a real check of an AI answer: it has a neat layout? (a) not a real check (b) a real check
  25. 25.🔢 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
  26. 26.📱 What is the AI doing here: a video app suggesting what to watch next? (a) recognising (b) generating (c) predicting (d) recommending
  27. 27.Which of these uses AI? (a) a printed timetable (b) a calculator (c) a doorbell (d) face unlock on a phone
  28. 28.True or false: “improves with more data” describes how AI works. (a) False (b) True
  29. 29.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  30. 30.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  31. 31.Which of these is a fact about AI? (a) AI is never wrong (b) AI answers need checking (c) AI knows everything (d) AI has real feelings
  32. 32.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) correct labels (d) photos in many lights
  33. 33.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) an image (b) text (c) music or sound
  34. 34.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  35. 35.🎨 An image generator makes a picture from… (a) a phone number (b) a text description (c) the weather (d) your password
  36. 36.True or false: “same steps every time” describes how AI works. (a) False (b) True
  37. 37.🐶 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
  38. 38.✨ Generative or not: creating a cartoon? (a) sorts or predicts (b) makes something new
  39. 39.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI
  40. 40.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess

Answer key

  1. spam
  2. photos grouped by face
  3. no, it finds patterns
  4. test on many groups
  5. adds to bias
  6. predicting
  7. no, it can be wrong
  8. learns from examples
  9. bad for training
  10. what training builds
  11. False
  12. AI can make up facts
  13. True
  14. a simple rule is enough
  15. False
  16. AI learns from data
  17. few child voices in data
  18. False
  19. a digital watch
  20. training data
  21. False
  22. more varied data
  23. False
  24. not a real check
  25. check it on paper
  26. recommending
  27. face unlock on a phone
  28. True
  29. reduces bias
  30. one-sided data
  31. AI answers need checking
  32. testing on training data
  33. music or sound
  34. recorded spoken words
  35. a text description
  36. False
  37. many labelled photos
  38. makes something new
  39. AI
  40. what training builds

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