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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 837 · 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 adds to bias? (a) fix wrong labels (b) copy old unfair choices (c) balance the data (d) ask different people
  2. 2.🤖 AI or a normal program: which one “handles unseen examples”? (a) AI (b) a normal program
  3. 3.True or false: adding up the marks on a report card needs AI that learns from examples. (a) True (b) False
  4. 4.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  5. 5.✅ Is this a real check of an AI answer: redo the maths yourself? (a) a real check (b) not a real check
  6. 6.True or false: “follows fixed rules” describes how AI works. (a) True (b) False
  7. 7.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  8. 8.Which of these is good for training a model? (a) clear, sharp examples (b) blurry, unclear photos (c) only one kind of example (d) testing on training data
  9. 9.📱 What is the AI doing here: an AI tool making a brand-new tune? (a) recommending (b) predicting (c) recognising (d) generating
  10. 10.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  11. 11.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  12. 12.🛠️ Which does this job need: translating a sentence into Hindi? (a) a simple rule is enough (b) needs AI (learning)
  13. 13.🔦 Is a torch with an on/off switch AI? (a) no (b) yes (c) only if it is bright
  14. 14.True or false: “ask your teacher” is a real way to check an AI answer. (a) True (b) False
  15. 15.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it uses electricity (c) it is always right (d) it has a screen
  16. 16.True or false: “AI learns from data” is a myth about AI. (a) False (b) True
  17. 17.Which of these describes how AI works? (a) uses rules people wrote (b) makes a best guess (c) follows fixed rules (d) does exactly as coded
  18. 18.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  19. 19.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  20. 20.🔍 Which is the odd one out? (a) ignore complaints (b) test on many groups (c) add more of the same (d) use one group only
  21. 21.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) uses rules people wrote (d) learns from examples
  22. 22.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) music or sound (b) text (c) an image
  23. 23.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
  24. 24.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) composing a new tune (c) unlocking with a face (d) creating a cartoon
  26. 26.🏠 AI or not AI: a map predicting traffic? (a) not AI (b) uses AI
  27. 27.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  28. 28.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
  29. 29.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
  30. 30.🔍 Which is the odd one out? (a) ask different people (b) use one group only (c) add more of the same (d) skip testing
  31. 31.🏠 AI or not AI: voice typing? (a) not AI (b) uses AI
  32. 32.✅ Is this a real check of an AI answer: it sounds very sure? (a) not a real check (b) a real check
  33. 33.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) no, check it anyway (c) yes, if it is long
  34. 34.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
  35. 35.🏠 AI or not AI: a kitchen weighing scale? (a) not AI (b) uses AI
  36. 36.Which of these is a fact about AI? (a) long answers are true (b) AI can make up facts (c) AI has real feelings (d) confident means correct
  37. 37.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  38. 38.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
  39. 39.True or false: “balance the data” helps reduce bias. (a) True (b) False
  40. 40.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) correct labels (d) labels added at random

Answer key

  1. copy old unfair choices
  2. AI
  3. False
  4. training data
  5. a real check
  6. False
  7. AI
  8. clear, sharp examples
  9. generating
  10. a prediction
  11. training data
  12. needs AI (learning)
  13. no
  14. True
  15. it learns from examples
  16. False
  17. makes a best guess
  18. a normal program
  19. False
  20. test on many groups
  21. uses rules people wrote
  22. text
  23. adds to bias
  24. True
  25. unlocking with a face
  26. uses AI
  27. the trained program
  28. a real check
  29. many labelled photos
  30. ask different people
  31. uses AI
  32. not a real check
  33. no, check it anyway
  34. bias from data
  35. not AI
  36. AI can make up facts
  37. a fact
  38. True
  39. True
  40. labels added at random

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