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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 508 · 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.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
  2. 2.🔍 Which is the odd one out? (a) writing quiz questions (b) turning speech to text (c) creating a cartoon (d) making up a story
  3. 3.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  4. 4.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
  5. 5.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
  7. 7.Which of these describes how AI works? (a) never learns from data (b) does exactly as coded (c) follows fixed rules (d) spots patterns in data
  8. 8.🔍 Which is the odd one out? (a) AI knows everything (b) AI is never wrong (c) AI learns from data (d) long answers are true
  9. 9.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
  10. 10.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  11. 11.🏠 AI or not AI: face unlock on a phone? (a) uses AI (b) not AI
  12. 12.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  13. 13.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) yes, just like us (c) yes, it gets sad (d) no, it finds patterns
  14. 14.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.🔍 Which is the odd one out? (a) AI is never wrong (b) long answers are true (c) AI has real feelings (d) AI can make up facts
  16. 16.🎨 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) text (c) an image
  17. 17.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) reading number plates (c) drawing a new picture (d) predicting rain
  18. 18.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  19. 19.🤖 What does AI stand for? (a) actual information (b) app installer (c) automatic internet (d) artificial intelligence
  20. 20.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) yes (c) no
  21. 21.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
  22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a prediction (d) a label error
  23. 23.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
  24. 24.Which of these is the model? (a) the learned patterns (b) flagging a new email (c) tomorrow’s rain guess (d) old emails marked spam
  25. 25.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) copies of one photo (d) many varied examples
  26. 26.Which of these is not AI? (a) face unlock on a phone (b) voice typing (c) a light switch (d) a spam filter
  27. 27.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) confident means correct (b) AI learns from data (c) AI can be wrong (d) AI copies data patterns
  29. 29.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
  30. 30.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) charging (c) printing (d) recommending
  31. 31.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  32. 32.📱 What is the AI doing here: a video app suggesting what to watch next? (a) recognising (b) generating (c) predicting (d) recommending
  33. 33.True or false: “AI answers need checking” is a myth about AI. (a) True (b) False
  34. 34.🏷️ 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
  35. 35.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
  36. 36.Which of these is AI that sorts, spots or predicts (not generative)? (a) sorting photos by face (b) composing a new tune (c) creating a cartoon (d) drafting a letter
  37. 37.🔍 Which is the odd one out? (a) writing a new poem (b) turning speech to text (c) suggesting a video (d) predicting rain
  38. 38.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  39. 39.Which of these uses AI? (a) a stopwatch (b) a fan regulator (c) video suggestions (d) a digital watch
  40. 40.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts

Answer key

  1. reduces bias
  2. turning speech to text
  3. data, model, prediction
  4. uses AI
  5. adds to bias
  6. not spam
  7. spots patterns in data
  8. AI learns from data
  9. False
  10. False
  11. uses AI
  12. training data
  13. no, it finds patterns
  14. a simple rule is enough
  15. AI can make up facts
  16. text
  17. drawing a new picture
  18. the model
  19. artificial intelligence
  20. no
  21. to see if it works
  22. a prediction
  23. False
  24. the learned patterns
  25. many varied examples
  26. a light switch
  27. True
  28. confident means correct
  29. bad for training
  30. recommending
  31. a normal program
  32. recommending
  33. False
  34. spam
  35. good for training
  36. sorting photos by face
  37. writing a new poem
  38. AI
  39. video suggestions
  40. sorts or predicts

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