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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 639 · 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.🔍 Which is the odd one out? (a) long answers are true (b) AI always checks facts (c) AI has real feelings (d) AI answers need checking
  2. 2.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
  3. 3.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
  4. 4.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
  5. 5.✨ Generative or not: turning speech to text? (a) makes something new (b) sorts or predicts
  6. 6.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
  7. 7.True or false: “a drum beat for a dance” asks for music or sound. (a) True (b) False
  8. 8.True or false: “redo the maths yourself” is a real way to check an AI answer. (a) False (b) True
  9. 9.🔍 Which is the odd one out? (a) a spam filter (b) a printed timetable (c) a stopwatch (d) a doorbell
  10. 10.Which of these helps reduce bias? (a) copy old unfair choices (b) ignore complaints (c) fix wrong labels (d) use one group only
  11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
  12. 12.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recommending (b) generating (c) recognising (d) predicting
  13. 13.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) examples of every type (d) testing on training data
  14. 14.🔍 Which is the odd one out? (a) a digital watch (b) voice typing (c) a kitchen weighing scale (d) a microwave timer
  15. 15.True or false: “a cheerful tune for Sports Day” asks for text. (a) True (b) False
  16. 16.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) copy old unfair choices (d) ignore complaints
  17. 17.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.🔍 Which is the odd one out? (a) wrong labels (b) examples of every type (c) photos in many lights (d) checking labels twice
  19. 19.🛠️ Which does this job need: finding 10% of a price? (a) a simple rule is enough (b) needs AI (learning)
  20. 20.🔦 Is a torch with an on/off switch AI? (a) yes (b) no (c) only if it is bright
  21. 21.Which of these adds to bias? (a) test on many groups (b) balance the data (c) fix wrong labels (d) ignore complaints
  22. 22.Which of these is training data? (a) tomorrow’s rain guess (b) 500 labelled leaf photos (c) the trained program (d) what training builds
  23. 23.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
  24. 24.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) balance the data (d) copy old unfair choices
  25. 25.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
  26. 26.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
  27. 27.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
  28. 28.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  29. 29.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) turning speech to text (c) spotting spam (d) making up a story
  30. 30.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
  32. 32.True or false: “never learns from data” describes how a normal program works. (a) True (b) False
  33. 33.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  34. 34.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
  35. 35.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
  36. 36.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  37. 37.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI learns from data (c) AI has real feelings (d) AI can be wrong
  38. 38.Which of these describes how AI works? (a) spots patterns in data (b) does exactly as coded (c) same steps every time (d) follows fixed rules
  39. 39.True or false: “a cartoon of a dancing elephant” asks for an image. (a) False (b) True
  40. 40.📺 A video app suggests what to watch next. What is the AI doing? (a) charging (b) cooking (c) recommending (d) printing

Answer key

  1. AI answers need checking
  2. good for training
  3. False
  4. AI
  5. sorts or predicts
  6. a myth
  7. True
  8. True
  9. a spam filter
  10. fix wrong labels
  11. spam
  12. predicting
  13. examples of every type
  14. voice typing
  15. False
  16. fix wrong labels
  17. False
  18. wrong labels
  19. a simple rule is enough
  20. no
  21. ignore complaints
  22. 500 labelled leaf photos
  23. AI
  24. balance the data
  25. sorts or predicts
  26. learn from data
  27. to see if it works
  28. a normal program
  29. making up a story
  30. balanced data
  31. good for training
  32. True
  33. adds to bias
  34. bad for training
  35. True
  36. AI
  37. AI has real feelings
  38. spots patterns in data
  39. True
  40. recommending

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