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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 3 · 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.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) trust the textbook (c) stop studying (d) share it online
  2. 2.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  3. 3.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  4. 4.⏩ In machine learning, which comes first: 500 labelled leaf photos or tomorrow’s rain guess? (a) 500 labelled leaf photos (b) tomorrow’s rain guess
  5. 5.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  6. 6.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  7. 7.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  8. 8.🔍 Which is the odd one out? (a) AI can be wrong (b) AI is never wrong (c) AI has real feelings (d) AI always checks facts
  9. 9.True or false: “examples of every type” is bad for training a model. (a) True (b) False
  10. 10.Which of these is a myth about AI? (a) AI can make up facts (b) AI answers need checking (c) confident means correct (d) AI can be wrong
  11. 11.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
  12. 12.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
  13. 13.Which of these describes how a normal program works? (a) handles unseen examples (b) uses rules people wrote (c) makes a best guess (d) learns from examples
  14. 14.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
  15. 15.🔍 Which is the odd one out? (a) face unlock on a phone (b) a printed timetable (c) a map predicting traffic (d) a spam filter
  16. 16.True or false: “a poster of a rainforest” asks for an image. (a) False (b) True
  17. 17.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  18. 18.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  19. 19.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) text (b) an image (c) music or sound
  20. 20.Which of these is the model? (a) what training builds (b) flagging a new email (c) 500 labelled leaf photos (d) naming a new fruit photo
  21. 21.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) bias from data (c) a fair model (d) a broken screen
  22. 22.📚 An AI chatbot names a book that does not exist. This is called… (a) a backup (b) a password (c) a summary (d) a hallucination
  23. 23.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
  24. 24.Which of these is a prediction? (a) tomorrow’s rain guess (b) the learned patterns (c) old emails marked spam (d) recorded spoken words
  25. 25.True or false: turning your spoken words into typed text is AI generating something new. (a) True (b) False
  26. 26.True or false: an image generator drawing a robot from a sentence is AI recognising something. (a) False (b) True
  27. 27.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
  28. 28.True or false: “follows fixed rules” describes how a normal program works. (a) False (b) True
  29. 29.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  30. 30.True or false: “it has a neat layout” is NOT a real way to check an AI answer. (a) False (b) True
  31. 31.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
  32. 32.Which of these describes how a normal program works? (a) follows fixed rules (b) improves with more data (c) handles unseen examples (d) makes a best guess
  33. 33.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
  34. 34.🏷️ 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
  35. 35.🔍 Which is the odd one out? (a) a stopwatch (b) a spam filter (c) a digital watch (d) a printed timetable
  36. 36.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  37. 37.Which of these uses AI? (a) a map predicting traffic (b) a doorbell (c) a calculator (d) a stopwatch
  38. 38.True or false: “asking the same AI again” is a real way to check an AI answer. (a) True (b) False
  39. 39.Which of these is not AI? (a) an image generator (b) video suggestions (c) a map predicting traffic (d) a torch
  40. 40.True or false: “ask different people” adds to bias. (a) True (b) False

Answer key

  1. trust the textbook
  2. AI
  3. one-sided data
  4. 500 labelled leaf photos
  5. reduces bias
  6. the model
  7. True
  8. AI can be wrong
  9. False
  10. confident means correct
  11. a myth
  12. bad for training
  13. uses rules people wrote
  14. False
  15. a printed timetable
  16. True
  17. training data
  18. False
  19. an image
  20. what training builds
  21. bias from data
  22. a hallucination
  23. reduces bias
  24. tomorrow’s rain guess
  25. False
  26. False
  27. makes something new
  28. True
  29. AI
  30. True
  31. AI
  32. follows fixed rules
  33. good for training
  34. spam
  35. a spam filter
  36. adds to bias
  37. a map predicting traffic
  38. False
  39. a torch
  40. False

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