← 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 820 · 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.Which of these is a myth about AI? (a) AI learns from data (b) AI knows everything (c) AI can make up facts (d) AI can mix up numbers
  2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
  3. 3.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  4. 4.True or false: “find a trusted source” is NOT a real way to check an AI answer. (a) True (b) False
  5. 5.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
  6. 6.True or false: turning your spoken words into typed text is AI predicting something. (a) False (b) True
  7. 7.True or false: a car camera reading a speed sign is AI predicting something. (a) False (b) True
  8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  9. 9.True or false: counting the words in an essay needs AI that learns from examples. (a) False (b) True
  10. 10.📱 What is the AI doing here: a camera app naming the flower you point at? (a) generating (b) predicting (c) recognising (d) recommending
  11. 11.True or false: “add varied examples” adds to bias. (a) True (b) False
  12. 12.🔍 Which is the odd one out? (a) writing quiz questions (b) suggesting a video (c) spotting a sick leaf (d) unlocking with a face
  13. 13.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  14. 14.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
  15. 15.Which of these describes how a normal program works? (a) gives a likely answer (b) handles unseen examples (c) never learns from data (d) learns from examples
  16. 16.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  17. 17.Which of these is training data? (a) past weather records (b) what training builds (c) tomorrow’s rain guess (d) the trained program
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  19. 19.🔦 Is a torch with an on/off switch AI? (a) no (b) only if it is bright (c) yes
  20. 20.True or false: recognising a bird from its song only needs a simple fixed rule. (a) True (b) False
  21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  22. 22.True or false: “testing on training data” is good for training a model. (a) True (b) False
  23. 23.✅ Is this a real check of an AI answer: see if the book exists? (a) not a real check (b) a real check
  24. 24.🛠️ Which does this job need: finding 10% of a price? (a) a simple rule is enough (b) needs AI (learning)
  25. 25.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
  26. 26.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) a simple rule is enough (b) needs AI (learning)
  27. 27.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) more varied data (d) one group only
  28. 28.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a hallucination (c) a summary (d) a backup
  29. 29.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
  30. 30.🔍 Which is the odd one out? (a) a digital watch (b) an AI chatbot (c) a fan regulator (d) a kitchen weighing scale
  31. 31.✨ Generative or not: composing a new tune? (a) makes something new (b) sorts or predicts
  32. 32.True or false: “ask your teacher” is a real way to check an AI answer. (a) False (b) True
  33. 33.🛠️ Which does this job need: reading messy handwriting? (a) a simple rule is enough (b) needs AI (learning)
  34. 34.Which of these describes how AI works? (a) learns from examples (b) one set rule per case (c) never learns from data (d) does exactly as coded
  35. 35.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
  36. 36.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the right answer tag (d) the font size
  37. 37.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  38. 38.🔍 Which is the odd one out? (a) check who is missing (b) copy old unfair choices (c) test on one group only (d) use one group only
  39. 39.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
  40. 40.✨ Generative or not: turning speech to text? (a) makes something new (b) sorts or predicts

Answer key

  1. AI knows everything
  2. spam
  3. a fact
  4. False
  5. uses AI
  6. False
  7. False
  8. reduces bias
  9. False
  10. recognising
  11. False
  12. writing quiz questions
  13. needs AI (learning)
  14. True
  15. never learns from data
  16. a myth
  17. past weather records
  18. training data
  19. no
  20. False
  21. training data
  22. False
  23. a real check
  24. a simple rule is enough
  25. to see if it works
  26. needs AI (learning)
  27. more varied data
  28. a hallucination
  29. uses AI
  30. an AI chatbot
  31. makes something new
  32. True
  33. needs AI (learning)
  34. learns from examples
  35. False
  36. the right answer tag
  37. True
  38. check who is missing
  39. many labelled photos
  40. sorts or predicts

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