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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 122 · 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.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
  2. 2.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  3. 3.Which of these adds to bias? (a) test on one group only (b) ask different people (c) balance the data (d) add varied examples
  4. 4.✍️ How does an AI chatbot write its replies? (a) asks a person (b) uses magic (c) predicts likely words (d) copies one website
  5. 5.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
  6. 6.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
  7. 7.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new
  8. 8.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  9. 9.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) photos in many lights (d) only one kind of example
  10. 10.🔍 Which is the odd one out? (a) spotting spam (b) spotting a sick leaf (c) sorting photos by face (d) making up a story
  11. 11.True or false: “AI always checks facts” is a fact about AI. (a) True (b) False
  12. 12.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  13. 13.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
  14. 14.True or false: “learns from examples” describes how a normal program works. (a) False (b) True
  15. 15.🔍 Which is the odd one out? (a) a kitchen weighing scale (b) a microwave timer (c) a map predicting traffic (d) a digital watch
  16. 16.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) its training data (c) its screen size (d) the weather
  17. 17.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  18. 18.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  19. 19.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
  20. 20.Which of these describes how a normal program works? (a) uses rules people wrote (b) handles unseen examples (c) gives a likely answer (d) spots patterns in data
  21. 21.Which of these uses AI? (a) a torch (b) voice typing (c) a fan regulator (d) a microwave timer
  22. 22.🧐 Fact or myth: “AI can mix up numbers”? (a) a fact (b) a myth
  23. 23.💬 What do we call the request you type to a generative AI? (a) a battery (b) a label (c) a password (d) a prompt
  24. 24.📱 What is the AI doing here: a video app suggesting what to watch next? (a) predicting (b) recognising (c) recommending (d) generating
  25. 25.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
  26. 26.Which of these uses AI? (a) a calculator (b) a fan regulator (c) a kitchen weighing scale (d) photos grouped by face
  27. 27.🔍 Which is the odd one out? (a) AI can make up facts (b) AI can mix up numbers (c) AI always checks facts (d) AI can be wrong
  28. 28.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, always (c) yes, if it is long
  29. 29.🎨 This prompt asks a generative AI for: a drawing of a cat on the Moon. What kind of output is that? (a) an image (b) text (c) music or sound
  30. 30.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  31. 31.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  32. 32.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) new data for testing (d) wrong labels
  33. 33.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  34. 34.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
  35. 35.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) predicting (c) drawing (d) sleeping
  36. 36.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) no (c) yes
  37. 37.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) False (b) True
  38. 38.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  39. 39.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) confident means correct (b) AI answers need checking (c) AI learns from data (d) AI can make up facts

Answer key

  1. many labelled photos
  2. balanced data
  3. test on one group only
  4. predicts likely words
  5. uses AI
  6. no, it can be wrong
  7. makes something new
  8. the model
  9. photos in many lights
  10. making up a story
  11. False
  12. old emails marked spam
  13. good for training
  14. False
  15. a map predicting traffic
  16. its training data
  17. a normal program
  18. True
  19. not AI
  20. uses rules people wrote
  21. voice typing
  22. a fact
  23. a prompt
  24. recommending
  25. a fact
  26. photos grouped by face
  27. AI always checks facts
  28. no, check it anyway
  29. an image
  30. a prediction
  31. balanced data
  32. new data for testing
  33. True
  34. sorts or predicts
  35. predicting
  36. no
  37. False
  38. good for training
  39. True
  40. confident means correct

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