← 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 512 · 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.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
  2. 2.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) copies of one photo (d) clear, sharp examples
  3. 3.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recognising (b) recommending (c) predicting (d) generating
  4. 4.True or false: “improves with more data” describes how AI works. (a) False (b) True
  5. 5.📦 What happens during training? (a) it prints labels (b) it charges up (c) it learns patterns (d) it takes photos
  6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
  7. 7.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  8. 8.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  9. 9.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program
  10. 10.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
  11. 11.🛠️ What helps make an AI system fairer? (a) ignoring mistakes (b) fewer tests (c) one group only (d) more varied data
  12. 12.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
  13. 13.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
  14. 14.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  15. 15.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
  16. 16.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
  17. 17.True or false: “AI has real feelings” is a myth about AI. (a) True (b) False
  18. 18.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) very few examples (d) labels added at random
  19. 19.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on many groups (d) add more of the same
  20. 20.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) AI answers need checking (b) confident means correct (c) AI knows everything (d) AI always checks facts
  22. 22.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, always (c) yes, if it is long
  23. 23.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) nobody at all (d) people
  24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
  25. 25.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) blurry, unclear photos (d) examples of every type
  26. 26.🛠️ Which does this job need: recognising a friend’s face in photos? (a) needs AI (learning) (b) a simple rule is enough
  27. 27.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
  28. 28.True or false: “redo the maths yourself” is NOT a real way to check an AI answer. (a) False (b) True
  29. 29.🔍 Which is the odd one out? (a) AI is never wrong (b) AI has real feelings (c) long answers are true (d) AI learns from data
  30. 30.True or false: “AI answers need checking” is a myth about AI. (a) True (b) False
  31. 31.Which of these helps reduce bias? (a) copy old unfair choices (b) use one group only (c) ignore complaints (d) add varied examples
  32. 32.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) clear, sharp examples (d) wrong labels
  33. 33.True or false: “a poster of a rainforest” asks for text. (a) True (b) False
  34. 34.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
  35. 35.✅ Is this a real check of an AI answer: it uses big words? (a) a real check (b) not a real check
  36. 36.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
  37. 37.🔍 Which is the odd one out? (a) a microwave timer (b) an app translating signs (c) a digital watch (d) a fan regulator
  38. 38.📱 What is the AI doing here: a video app suggesting what to watch next? (a) predicting (b) recommending (c) recognising (d) generating
  39. 39.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can make up facts (c) AI has real feelings (d) AI copies data patterns
  40. 40.🏠 AI or not AI: an AI chatbot? (a) uses AI (b) not AI

Answer key

  1. bad for training
  2. copies of one photo
  3. predicting
  4. True
  5. it learns patterns
  6. spam
  7. one-sided data
  8. adds to bias
  9. a normal program
  10. uses AI
  11. more varied data
  12. better at its task
  13. the right answer tag
  14. reduces bias
  15. makes something new
  16. good for training
  17. True
  18. clear, sharp examples
  19. test on many groups
  20. False
  21. AI answers need checking
  22. no, check it anyway
  23. people
  24. a prediction
  25. examples of every type
  26. needs AI (learning)
  27. a normal program
  28. False
  29. AI learns from data
  30. False
  31. add varied examples
  32. wrong labels
  33. False
  34. good for training
  35. not a real check
  36. uses AI
  37. an app translating signs
  38. recommending
  39. AI has real feelings
  40. uses AI

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