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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 610 · 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.🎨 This prompt asks a generative AI for: a drawing of a cat on the Moon. What kind of output is that? (a) text (b) music or sound (c) an image
  2. 2.Which of these is not AI? (a) a microwave timer (b) face unlock on a phone (c) voice typing (d) an image generator
  3. 3.True or false: “AI answers need checking” is a fact about AI. (a) True (b) False
  4. 4.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  5. 5.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  6. 6.🏠 AI or not AI: a map predicting traffic? (a) not AI (b) uses AI
  7. 7.Which of these uses AI? (a) video suggestions (b) a kitchen weighing scale (c) a stopwatch (d) a doorbell
  8. 8.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
  9. 9.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) True (b) False
  10. 10.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
  11. 11.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) check it on paper (c) copy it straight away (d) ask it to hurry
  12. 12.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
  13. 13.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  15. 15.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  16. 16.🤖 What does AI stand for? (a) automatic internet (b) actual information (c) artificial intelligence (d) app installer
  17. 17.True or false: “a thank-you note to the bus driver” asks for an image. (a) True (b) False
  18. 18.🧮 Which of these is NOT AI? (a) voice typing (b) face unlock (c) a basic calculator (d) a spam filter
  19. 19.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  20. 20.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, if it is long (c) yes, always
  21. 21.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  22. 22.🏠 AI or not AI: voice typing? (a) not AI (b) uses AI
  23. 23.Which of these adds to bias? (a) balance the data (b) ask different people (c) add more of the same (d) check who is missing
  24. 24.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  25. 25.True or false: “what training builds” is the model. (a) False (b) True
  26. 26.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) text (b) an image (c) music or sound
  27. 27.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
  28. 28.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  30. 30.🔍 Which is the odd one out? (a) AI can mix up numbers (b) confident means correct (c) AI always checks facts (d) AI has real feelings
  31. 31.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its screen size (d) its training data
  32. 32.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
  33. 33.🔍 Which is the odd one out? (a) drawing a new picture (b) predicting rain (c) spotting spam (d) suggesting a video
  34. 34.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
  35. 35.Which of these is a prediction? (a) 500 labelled leaf photos (b) what training builds (c) the learned patterns (d) typing a new spoken word
  36. 36.💬 What do we call the request you type to a generative AI? (a) a password (b) a prompt (c) a label (d) a battery
  37. 37.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
  39. 39.True or false: “the learned patterns” is training data. (a) True (b) False
  40. 40.Which of these is bad for training a model? (a) labels added at random (b) new data for testing (c) photos in many lights (d) correct labels

Answer key

  1. an image
  2. a microwave timer
  3. True
  4. a prediction
  5. a fact
  6. uses AI
  7. video suggestions
  8. good for training
  9. False
  10. balanced data
  11. check it on paper
  12. a fact
  13. False
  14. adds to bias
  15. one-sided data
  16. artificial intelligence
  17. False
  18. a basic calculator
  19. True
  20. no, check it anyway
  21. the learned patterns
  22. uses AI
  23. add more of the same
  24. True
  25. True
  26. an image
  27. needs AI (learning)
  28. True
  29. a myth
  30. AI can mix up numbers
  31. its training data
  32. adds to bias
  33. drawing a new picture
  34. bad for training
  35. typing a new spoken word
  36. a prompt
  37. the model
  38. spam
  39. False
  40. labels added at random

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