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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 970 · 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.🧐 Fact or myth: “AI answers need checking”? (a) a myth (b) a fact
  2. 2.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) use one group only (d) fix wrong labels
  3. 3.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) turning speech to text (c) drafting a letter (d) drawing a new picture
  4. 4.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
  5. 5.🔍 Which is the odd one out? (a) unlocking with a face (b) drafting a letter (c) writing a new poem (d) creating a cartoon
  6. 6.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
  7. 7.🗣️ 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
  8. 8.True or false: “AI can be wrong” is a myth about AI. (a) False (b) True
  9. 9.True or false: “asking the same AI again” is a real way to check an AI answer. (a) False (b) True
  10. 10.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) reduces bias (b) adds to bias
  11. 11.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  12. 12.🔍 Which is the odd one out? (a) correct labels (b) wrong labels (c) very few examples (d) labels added at random
  13. 13.🔍 Which is the odd one out? (a) a stopwatch (b) a digital watch (c) a torch (d) a voice assistant
  14. 14.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) predicting (b) recommending (c) generating (d) recognising
  15. 15.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  16. 16.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) ask it to hurry (c) check it on paper (d) copy it straight away
  17. 17.Which of these is AI that sorts, spots or predicts (not generative)? (a) suggesting a video (b) making up a story (c) composing a new tune (d) writing a new poem
  18. 18.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on one group only (c) use one group only (d) balance the data
  19. 19.🔍 Which is the odd one out? (a) AI learns from data (b) AI can be wrong (c) AI can make up facts (d) AI has real feelings
  20. 20.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) drafting a letter (b) unlocking with a face (c) sorting photos by face (d) suggesting a video
  22. 22.📱 What is the AI doing here: turning your spoken words into typed text? (a) predicting (b) generating (c) recognising (d) recommending
  23. 23.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  24. 24.🔍 Which is the odd one out? (a) unlocking with a face (b) composing a new tune (c) predicting rain (d) spotting spam
  25. 25.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  26. 26.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
  27. 27.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a backup (c) a summary (d) a hallucination
  28. 28.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) printing (c) cooking (d) charging
  29. 29.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) copies of one photo (d) labels added at random
  30. 30.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
  31. 31.🧮 Is a basic calculator an AI system? (a) yes, it is smart (b) only at night (c) yes, it can think (d) no, it follows rules
  32. 32.True or false: “a thank-you note to the bus driver” asks for an image. (a) False (b) True
  33. 33.📱 What is the AI doing here: a camera app naming the flower you point at? (a) predicting (b) recommending (c) recognising (d) generating
  34. 34.🔍 Which is the odd one out? (a) a digital watch (b) a map predicting traffic (c) an AI chatbot (d) video suggestions
  35. 35.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) very few examples (d) correct labels
  36. 36.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  37. 37.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  38. 38.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  39. 39.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  40. 40.Which of these is a myth about AI? (a) AI learns from data (b) AI can be wrong (c) AI has real feelings (d) AI can mix up numbers

Answer key

  1. a fact
  2. use one group only
  3. turning speech to text
  4. no, it can be wrong
  5. unlocking with a face
  6. a real check
  7. few child voices in data
  8. False
  9. False
  10. adds to bias
  11. reduces bias
  12. correct labels
  13. a voice assistant
  14. predicting
  15. True
  16. check it on paper
  17. suggesting a video
  18. balance the data
  19. AI has real feelings
  20. False
  21. drafting a letter
  22. recognising
  23. good for training
  24. composing a new tune
  25. a fact
  26. makes something new
  27. a hallucination
  28. recommending
  29. photos in many lights
  30. True
  31. no, it follows rules
  32. False
  33. recognising
  34. a digital watch
  35. correct labels
  36. reduces bias
  37. True
  38. True
  39. False
  40. AI has real feelings

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