← 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 596 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
  2. 2.True or false: “uses rules people wrote” describes how a normal program works. (a) True (b) False
  3. 3.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  4. 4.Which of these is not AI? (a) video suggestions (b) photos grouped by face (c) a map predicting traffic (d) a calculator
  5. 5.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  6. 6.True or false: “new data for testing” is good for training a model. (a) False (b) True
  7. 7.🤖 Who builds and trains AI systems? (a) the Moon (b) people (c) nobody at all (d) the weather
  8. 8.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) predicting (b) recommending (c) recognising (d) generating
  9. 9.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  10. 10.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
  11. 11.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  12. 12.True or false: “flagging a new email” is a prediction. (a) False (b) True
  13. 13.🧐 Fact or myth: “long answers are true”? (a) a myth (b) a fact
  14. 14.True or false: “test on many groups” adds to bias. (a) True (b) False
  15. 15.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) a sticker on a laptop (d) the price
  16. 16.True or false: “AI copies data patterns” is a myth about AI. (a) True (b) False
  17. 17.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  18. 18.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) no, it finds patterns (c) only on weekends (d) yes, it gets sad
  19. 19.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  20. 20.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  21. 21.True or false: “correct labels” is bad for training a model. (a) True (b) False
  22. 22.True or false: “balance the data” helps reduce bias. (a) False (b) True
  23. 23.Which of these uses AI? (a) a fan regulator (b) photos grouped by face (c) a digital watch (d) a calculator
  24. 24.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  25. 25.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  26. 26.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) yes, if it is long (c) no, check it anyway
  27. 27.True or false: “flagging a new email” is the model. (a) True (b) False
  28. 28.Which of these is a fact about AI? (a) AI learns from data (b) AI is never wrong (c) confident means correct (d) AI has real feelings
  29. 29.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
  30. 30.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  31. 31.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add varied examples (d) use one group only
  32. 32.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  33. 33.📺 A video app suggests what to watch next. What is the AI doing? (a) charging (b) printing (c) cooking (d) recommending
  34. 34.True or false: “labelled fruit photos” is a prediction. (a) False (b) True
  35. 35.✅ Is this a real check of an AI answer: ask your teacher? (a) not a real check (b) a real check
  36. 36.True or false: “match it to the textbook” is a real way to check an AI answer. (a) True (b) False
  37. 37.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program
  38. 38.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
  39. 39.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  40. 40.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program

Answer key

  1. spam
  2. True
  3. the model
  4. a calculator
  5. balanced data
  6. True
  7. people
  8. recognising
  9. False
  10. it may get it wrong
  11. False
  12. True
  13. a myth
  14. False
  15. the right answer tag
  16. False
  17. False
  18. no, it finds patterns
  19. a prediction
  20. to see if it works
  21. False
  22. True
  23. photos grouped by face
  24. AI
  25. 500 labelled leaf photos
  26. no, check it anyway
  27. False
  28. AI learns from data
  29. a normal program
  30. a prediction
  31. use one group only
  32. a fact
  33. recommending
  34. False
  35. a real check
  36. True
  37. a normal program
  38. no, it can be wrong
  39. balanced data
  40. a normal program

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