← 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 463 · 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: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
  2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
  3. 3.🏷️ 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
  4. 4.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  5. 5.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  6. 6.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  7. 7.🔍 Which is the odd one out? (a) very few examples (b) new data for testing (c) labels added at random (d) testing on training data
  8. 8.True or false: “ignore complaints” adds to bias. (a) False (b) True
  9. 9.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  10. 10.True or false: a video app suggesting what to watch next is AI recognising something. (a) True (b) False
  11. 11.True or false: “very few examples” is bad for training a model. (a) True (b) False
  12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
  13. 13.✨ Generative or not: suggesting a video? (a) sorts or predicts (b) makes something new
  14. 14.🏠 AI or not AI: a printed timetable? (a) uses AI (b) not AI
  15. 15.Which of these is generative AI (it makes something new)? (a) making up a story (b) spotting a sick leaf (c) sorting photos by face (d) predicting rain
  16. 16.🛠️ Which does this job need: sorting names in A to Z order? (a) a simple rule is enough (b) needs AI (learning)
  17. 17.🧪 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
  18. 18.🏠 AI or not AI: a voice assistant? (a) not AI (b) uses AI
  19. 19.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
  20. 20.✨ What does generative AI do? (a) only stores files (b) charges batteries (c) only adds numbers (d) makes new content
  21. 21.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) recognising (b) recommending (c) predicting (d) generating
  22. 22.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) False (b) True
  23. 23.🧐 Fact or myth: “long answers are true”? (a) a fact (b) a myth
  24. 24.🧐 Fact or myth: “confident means correct”? (a) a fact (b) a myth
  25. 25.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
  26. 26.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  27. 27.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) fix wrong labels (d) add varied examples
  28. 28.Which of these is a prediction? (a) labelled fruit photos (b) the trained program (c) tomorrow’s rain guess (d) 500 labelled leaf photos
  29. 29.🔍 Which is the odd one out? (a) copies of one photo (b) very few examples (c) testing on training data (d) checking labels twice
  30. 30.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  31. 31.🏠 AI or not AI: a light switch? (a) not AI (b) uses AI
  32. 32.🔍 Which is the odd one out? (a) AI answers need checking (b) AI learns from data (c) AI can make up facts (d) AI is never wrong
  33. 33.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
  34. 34.🔍 Which is the odd one out? (a) making up a story (b) creating a cartoon (c) spotting a sick leaf (d) composing a new tune
  35. 35.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
  36. 36.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
  37. 37.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  38. 38.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  39. 39.Which of these describes how a normal program works? (a) makes a best guess (b) does exactly as coded (c) handles unseen examples (d) learns from examples
  40. 40.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new

Answer key

  1. False
  2. False
  3. spam
  4. one-sided data
  5. a normal program
  6. a prediction
  7. new data for testing
  8. True
  9. a prediction
  10. False
  11. True
  12. not spam
  13. sorts or predicts
  14. not AI
  15. making up a story
  16. a simple rule is enough
  17. to see if it works
  18. uses AI
  19. True
  20. makes new content
  21. predicting
  22. False
  23. a myth
  24. a myth
  25. a fact
  26. True
  27. ignore complaints
  28. tomorrow’s rain guess
  29. checking labels twice
  30. past weather records
  31. not AI
  32. AI is never wrong
  33. False
  34. spotting a sick leaf
  35. good for training
  36. a real check
  37. good for training
  38. what training builds
  39. does exactly as coded
  40. makes something new

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