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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 973 · 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 of these is good for training a model? (a) wrong labels (b) only one kind of example (c) copies of one photo (d) many varied examples
  2. 2.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
  3. 3.🔍 Which is the odd one out? (a) an app translating signs (b) an image generator (c) a light switch (d) a map predicting traffic
  4. 4.🛠️ Which does this job need: spotting spam emails by their patterns? (a) needs AI (learning) (b) a simple rule is enough
  5. 5.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) predicting (c) singing (d) drawing
  6. 6.Which of these is bad for training a model? (a) examples of every type (b) labels added at random (c) many varied examples (d) clear, sharp examples
  7. 7.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) skip testing (d) test on one group only
  8. 8.🔍 Which is the odd one out? (a) confident means correct (b) AI answers need checking (c) AI has real feelings (d) AI always checks facts
  9. 9.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  10. 10.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
  11. 11.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  12. 12.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new
  13. 13.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) music or sound (b) text (c) an image
  14. 14.True or false: “checking labels twice” is good for training a model. (a) False (b) True
  15. 15.🔍 Which is the odd one out? (a) a doorbell (b) a voice assistant (c) a fan regulator (d) a microwave timer
  16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
  17. 17.🔍 Which is the odd one out? (a) a doorbell (b) a calculator (c) a microwave timer (d) a spam filter
  18. 18.True or false: “AI has real feelings” is a fact about AI. (a) False (b) True
  19. 19.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) uses magic (c) copies one website (d) asks a person
  20. 20.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI can be wrong (c) AI learns from data (d) AI knows everything
  21. 21.✨ Generative or not: suggesting a video? (a) makes something new (b) sorts or predicts
  22. 22.Which of these is a fact about AI? (a) AI can be wrong (b) AI knows everything (c) confident means correct (d) long answers are true
  23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
  24. 24.True or false: “handles unseen examples” describes how AI works. (a) True (b) False
  25. 25.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  26. 26.📱 What is the AI doing here: turning your spoken words into typed text? (a) generating (b) recognising (c) predicting (d) recommending
  27. 27.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  28. 28.🎨 This prompt asks a generative AI for: rain sound effects for a play. What kind of output is that? (a) an image (b) music or sound (c) text
  29. 29.Which of these is generative AI (it makes something new)? (a) writing a new poem (b) turning speech to text (c) predicting rain (d) sorting photos by face
  30. 30.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
  31. 31.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  32. 32.True or false: “many varied examples” is good for training a model. (a) False (b) True
  33. 33.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) creating a cartoon (c) turning speech to text (d) spotting spam
  34. 34.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  35. 35.True or false: “see if the book exists” is a real way to check an AI answer. (a) False (b) True
  36. 36.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
  37. 37.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  38. 38.Which of these adds to bias? (a) test on one group only (b) balance the data (c) add varied examples (d) test on many groups
  39. 39.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) music or sound (b) an image (c) text
  40. 40.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False

Answer key

  1. many varied examples
  2. AI
  3. a light switch
  4. needs AI (learning)
  5. predicting
  6. labels added at random
  7. add varied examples
  8. AI answers need checking
  9. adds to bias
  10. False
  11. a prediction
  12. makes something new
  13. text
  14. True
  15. a voice assistant
  16. spam
  17. a spam filter
  18. False
  19. predicts likely words
  20. AI knows everything
  21. sorts or predicts
  22. AI can be wrong
  23. not spam
  24. True
  25. adds to bias
  26. recognising
  27. to see if it works
  28. music or sound
  29. writing a new poem
  30. False
  31. needs AI (learning)
  32. True
  33. creating a cartoon
  34. training data
  35. True
  36. data, model, prediction
  37. makes something new
  38. test on one group only
  39. text
  40. False

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