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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 306 · 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: “old emails marked spam” is a prediction. (a) False (b) True
  2. 2.Which of these describes how AI works? (a) one set rule per case (b) never learns from data (c) makes a best guess (d) same steps every time
  3. 3.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  4. 4.🧐 Fact or myth: “AI knows everything”? (a) a myth (b) a fact
  5. 5.Which of these is generative AI (it makes something new)? (a) spotting spam (b) creating a cartoon (c) unlocking with a face (d) predicting rain
  6. 6.🧐 Fact or myth: “AI learns from data”? (a) a fact (b) a myth
  7. 7.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
  8. 8.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
  9. 9.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  10. 10.🏷️ 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
  11. 11.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
  12. 12.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
  15. 15.True or false: “AI can mix up numbers” is a fact about AI. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
  17. 17.True or false: “test on many groups” helps reduce bias. (a) False (b) True
  18. 18.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  19. 19.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) labels added at random
  20. 20.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) blurry, unclear photos (d) correct labels
  21. 21.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
  22. 22.🔍 Which is the odd one out? (a) AI can be wrong (b) AI answers need checking (c) AI knows everything (d) AI copies data patterns
  23. 23.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) predicting (b) recommending (c) generating (d) recognising
  24. 24.Which of these is training data? (a) tomorrow’s rain guess (b) what training builds (c) past weather records (d) the learned patterns
  25. 25.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  26. 26.🎨 An image generator makes a picture from… (a) your password (b) the weather (c) a text description (d) a phone number
  27. 27.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, if it is long (b) yes, always (c) no, check it anyway
  28. 28.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  29. 29.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
  30. 30.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  31. 31.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  32. 32.True or false: “a drum beat for a dance” asks for text. (a) False (b) True
  33. 33.Which of these is not AI? (a) photos grouped by face (b) a stopwatch (c) a spam filter (d) an image generator
  34. 34.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) False (b) True
  35. 35.🏠 AI or not AI: a light switch? (a) uses AI (b) not AI
  36. 36.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  37. 37.Which of these uses AI? (a) a digital watch (b) a light switch (c) a voice assistant (d) a torch
  38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
  39. 39.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  40. 40.True or false: “balance the data” adds to bias. (a) True (b) False

Answer key

  1. False
  2. makes a best guess
  3. True
  4. a myth
  5. creating a cartoon
  6. a fact
  7. a normal program
  8. False
  9. True
  10. not spam
  11. bad for training
  12. good for training
  13. False
  14. the right answer tag
  15. True
  16. one-sided data
  17. True
  18. AI
  19. labels added at random
  20. correct labels
  21. False
  22. AI knows everything
  23. recognising
  24. past weather records
  25. a fact
  26. a text description
  27. no, check it anyway
  28. training data
  29. a simple rule is enough
  30. the model
  31. a prediction
  32. False
  33. a stopwatch
  34. False
  35. not AI
  36. a prediction
  37. a voice assistant
  38. many labelled photos
  39. balanced data
  40. False

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