← Part 1 test: what AI is lesson New set →

AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 937 · 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.True or false: “a summary of chapter 3” asks for music or sound. (a) True (b) False
  2. 2.🏷️ 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
  3. 3.Which of these is training data? (a) the trained program (b) naming a new fruit photo (c) what training builds (d) recorded spoken words
  4. 4.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
  5. 5.📱 What is the AI doing here: a car camera reading a speed sign? (a) predicting (b) recommending (c) generating (d) recognising
  6. 6.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) predicting (b) recognising (c) recommending (d) generating
  7. 7.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  8. 8.True or false: sorting names in A to Z order needs AI that learns from examples. (a) True (b) False
  9. 9.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) fix wrong labels (d) test on one group only
  10. 10.🤖 Who builds and trains AI systems? (a) the weather (b) nobody at all (c) the Moon (d) people
  11. 11.True or false: showing the time on a clock only needs a simple fixed rule. (a) True (b) False
  12. 12.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  13. 13.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
  14. 14.Which of these is a prediction? (a) naming a new leaf (b) labelled fruit photos (c) past weather records (d) what training builds
  15. 15.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) only one kind of example (d) examples of every type
  16. 16.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  17. 17.True or false: “long answers are true” is a myth about AI. (a) True (b) False
  18. 18.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  19. 19.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
  20. 20.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
  21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
  22. 22.🧮 Which of these is NOT AI? (a) face unlock (b) a basic calculator (c) voice typing (d) a spam filter
  23. 23.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
  24. 24.Which of these describes how a normal program works? (a) never learns from data (b) gives a likely answer (c) learns from examples (d) improves with more data
  25. 25.True or false: “AI always checks facts” is a myth about AI. (a) False (b) True
  26. 26.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
  27. 27.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
  28. 28.🔍 Which is the odd one out? (a) a fan regulator (b) a spam filter (c) a microwave timer (d) a kitchen weighing scale
  29. 29.True or false: “wrong labels” is bad for training a model. (a) True (b) False
  30. 30.True or false: “recorded spoken words” is training data. (a) False (b) True
  31. 31.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
  32. 32.True or false: “ask different people” helps reduce bias. (a) True (b) False
  33. 33.🔍 Which is the odd one out? (a) a torch (b) video suggestions (c) a map predicting traffic (d) an image generator
  34. 34.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  35. 35.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) text (b) music or sound (c) an image
  36. 36.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
  37. 37.True or false: finding 10% of a price only needs a simple fixed rule. (a) False (b) True
  38. 38.Which of these is a prediction? (a) the learned patterns (b) past weather records (c) what training builds (d) typing a new spoken word
  39. 39.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  40. 40.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) an image (b) music or sound (c) text

Answer key

  1. False
  2. not spam
  3. recorded spoken words
  4. False
  5. recognising
  6. generating
  7. adds to bias
  8. False
  9. test on one group only
  10. people
  11. True
  12. to see if it works
  13. False
  14. naming a new leaf
  15. examples of every type
  16. adds to bias
  17. True
  18. the model
  19. uses AI
  20. sorts or predicts
  21. spam
  22. a basic calculator
  23. more varied data
  24. never learns from data
  25. True
  26. True
  27. it may get it wrong
  28. a spam filter
  29. True
  30. True
  31. True
  32. True
  33. a torch
  34. balanced data
  35. an image
  36. better at its task
  37. True
  38. typing a new spoken word
  39. adds to bias
  40. an image

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students