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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 320 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
  2. 2.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI can make up facts (c) AI answers need checking (d) AI knows everything
  3. 3.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  4. 4.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
  5. 5.True or false: “copy old unfair choices” helps reduce bias. (a) False (b) True
  6. 6.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  7. 7.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  8. 8.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
  9. 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  11. 11.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) text (b) music or sound (c) an image
  12. 12.True or false: “the trained program” is the model. (a) True (b) False
  13. 13.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  14. 14.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it takes photos (d) it charges up
  15. 15.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  16. 16.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
  17. 17.True or false: “AI can make up facts” is a fact about AI. (a) False (b) True
  18. 18.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
  19. 19.Which of these is bad for training a model? (a) new data for testing (b) copies of one photo (c) checking labels twice (d) clear, sharp examples
  20. 20.✅ Is this a real check of an AI answer: find a trusted source? (a) not a real check (b) a real check
  21. 21.True or false: “AI can be wrong” is a fact about AI. (a) False (b) True
  22. 22.True or false: “long answers are true” is a myth about AI. (a) True (b) False
  23. 23.True or false: “it answered quickly” is a real way to check an AI answer. (a) True (b) False
  24. 24.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  25. 25.🔍 Which is the odd one out? (a) checking labels twice (b) labels added at random (c) blurry, unclear photos (d) very few examples
  26. 26.Which of these is a fact about AI? (a) long answers are true (b) AI learns from data (c) AI has real feelings (d) AI is never wrong
  27. 27.Which of these uses AI? (a) a kitchen weighing scale (b) a printed timetable (c) a stopwatch (d) a map predicting traffic
  28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
  29. 29.🧮 Which of these is NOT AI? (a) a basic calculator (b) voice typing (c) face unlock (d) a spam filter
  30. 30.True or false: “many varied examples” is good for training a model. (a) False (b) True
  31. 31.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
  32. 32.Which of these is a prediction? (a) past weather records (b) naming a new leaf (c) labelled fruit photos (d) old emails marked spam
  33. 33.True or false: “ignore complaints” adds to bias. (a) False (b) True
  34. 34.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
  35. 35.🧐 Fact or myth: “AI learns from data”? (a) a fact (b) a myth
  36. 36.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  37. 37.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
  38. 38.Which of these uses AI? (a) face unlock on a phone (b) a calculator (c) a light switch (d) a fan regulator
  39. 39.✅ Is this a real check of an AI answer: it is long and detailed? (a) not a real check (b) a real check
  40. 40.True or false: “test on many groups” adds to bias. (a) True (b) False

Answer key

  1. spam
  2. AI knows everything
  3. balanced data
  4. False
  5. False
  6. True
  7. AI
  8. good for training
  9. False
  10. adds to bias
  11. an image
  12. True
  13. data, model, prediction
  14. it learns patterns
  15. a myth
  16. bad for training
  17. True
  18. bias from data
  19. copies of one photo
  20. a real check
  21. True
  22. True
  23. False
  24. training data
  25. checking labels twice
  26. AI learns from data
  27. a map predicting traffic
  28. not spam
  29. a basic calculator
  30. True
  31. True
  32. naming a new leaf
  33. True
  34. bad for training
  35. a fact
  36. True
  37. a prediction
  38. face unlock on a phone
  39. not a real check
  40. False

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