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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 110 · 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.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) charging (c) cooking (d) printing
  2. 2.Which of these is not AI? (a) an image generator (b) a fan regulator (c) face unlock on a phone (d) a spam filter
  3. 3.🔍 Which is the odd one out? (a) composing a new tune (b) making up a story (c) turning speech to text (d) creating a cartoon
  4. 4.🏠 AI or not AI: a printed timetable? (a) uses AI (b) not AI
  5. 5.True or false: “learns from examples” describes how AI works. (a) False (b) True
  6. 6.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  7. 7.💬 What do we call the request you type to a generative AI? (a) a battery (b) a password (c) a prompt (d) a label
  8. 8.⏩ In machine learning, which comes first: labelled fruit photos or tomorrow’s rain guess? (a) labelled fruit photos (b) tomorrow’s rain guess
  9. 9.🔍 Which is the odd one out? (a) AI knows everything (b) AI is never wrong (c) long answers are true (d) AI can be wrong
  10. 10.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
  11. 11.Which of these describes how a normal program works? (a) makes a best guess (b) one set rule per case (c) handles unseen examples (d) learns from examples
  12. 12.🎨 An image generator makes a picture from… (a) a text description (b) a phone number (c) your password (d) the weather
  13. 13.Which of these describes how a normal program works? (a) never learns from data (b) handles unseen examples (c) learns from examples (d) improves with more data
  14. 14.📱 What is the AI doing here: turning your spoken words into typed text? (a) generating (b) recommending (c) predicting (d) recognising
  15. 15.✅ Is this a real check of an AI answer: try the sum on paper? (a) a real check (b) not a real check
  16. 16.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) False (b) True
  17. 17.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  18. 18.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a label error (d) a password
  19. 19.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  20. 20.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  21. 21.✨ Generative or not: suggesting a video? (a) makes something new (b) sorts or predicts
  22. 22.True or false: “checking labels twice” is good for training a model. (a) True (b) False
  23. 23.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) learn from data (d) charge faster
  24. 24.🔍 Which is the odd one out? (a) photos in many lights (b) copies of one photo (c) very few examples (d) wrong labels
  25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  26. 26.True or false: recognising a friend’s face in photos needs AI that learns from examples. (a) False (b) True
  27. 27.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  28. 28.🔍 Which is the odd one out? (a) add more of the same (b) test on many groups (c) ignore complaints (d) test on one group only
  29. 29.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
  30. 30.📱 What is the AI doing here: an AI tool making a brand-new tune? (a) recognising (b) predicting (c) recommending (d) generating
  31. 31.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  32. 32.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it may get it wrong (d) it will turn yellow
  33. 33.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  34. 34.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  35. 35.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  36. 36.✨ Is everything a generative AI makes true? (a) no, it can be wrong (b) yes, always (c) only on Mondays
  37. 37.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) music or sound (b) text (c) an image
  38. 38.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recommending (b) recognising (c) predicting (d) generating
  39. 39.Which of these is training data? (a) naming a new fruit photo (b) recorded spoken words (c) typing a new spoken word (d) naming a new leaf
  40. 40.True or false: “balance the data” helps reduce bias. (a) True (b) False

Answer key

  1. recommending
  2. a fan regulator
  3. turning speech to text
  4. not AI
  5. True
  6. the model
  7. a prompt
  8. labelled fruit photos
  9. AI can be wrong
  10. good for training
  11. one set rule per case
  12. a text description
  13. never learns from data
  14. recognising
  15. a real check
  16. True
  17. a normal program
  18. a prediction
  19. balanced data
  20. balanced data
  21. sorts or predicts
  22. True
  23. learn from data
  24. photos in many lights
  25. not spam
  26. True
  27. data, model, prediction
  28. test on many groups
  29. True
  30. generating
  31. AI
  32. it may get it wrong
  33. one-sided data
  34. labelled fruit photos
  35. False
  36. no, it can be wrong
  37. an image
  38. recognising
  39. recorded spoken words
  40. True

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