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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 268 · 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.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) text (b) music or sound (c) an image
  2. 2.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
  3. 3.True or false: a phone unlocking when it sees your face is AI recognising something. (a) True (b) False
  4. 4.🏠 AI or not AI: a digital watch? (a) uses AI (b) not AI
  5. 5.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  6. 6.True or false: “spots patterns in data” describes how a normal program works. (a) True (b) False
  7. 7.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  8. 8.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
  9. 9.True or false: converting metres into centimetres needs AI that learns from examples. (a) True (b) False
  10. 10.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  11. 11.Which of these is not AI? (a) photos grouped by face (b) a spam filter (c) a stopwatch (d) an AI chatbot
  12. 12.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
  13. 13.Which of these is training data? (a) what training builds (b) the trained program (c) old emails marked spam (d) flagging a new email
  14. 14.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  15. 15.🧐 Fact or myth: “AI has real feelings”? (a) a myth (b) a fact
  16. 16.Which of these is generative AI (it makes something new)? (a) turning speech to text (b) predicting rain (c) drawing a new picture (d) unlocking with a face
  17. 17.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
  18. 18.🔍 Which is the odd one out? (a) creating a cartoon (b) drafting a letter (c) drawing a new picture (d) unlocking with a face
  19. 19.Which of these is a fact about AI? (a) AI always checks facts (b) long answers are true (c) confident means correct (d) AI can make up facts
  20. 20.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) reading number plates (c) writing a new poem (d) composing a new tune
  21. 21.True or false: “examples of every type” is good for training a model. (a) True (b) False
  22. 22.True or false: “it uses big words” is NOT a real way to check an AI answer. (a) True (b) False
  23. 23.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) making up a story (c) creating a cartoon (d) turning speech to text
  24. 24.True or false: “improves with more data” describes how a normal program works. (a) False (b) True
  25. 25.True or false: turning spoken words into typed text needs AI that learns from examples. (a) True (b) False
  26. 26.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) copies one website (c) asks a person (d) uses magic
  27. 27.True or false: “follows fixed rules” describes how a normal program works. (a) True (b) False
  28. 28.🏠 AI or not AI: face unlock on a phone? (a) uses AI (b) not AI
  29. 29.True or false: “ask different people” helps reduce bias. (a) False (b) True
  30. 30.True or false: “a cheerful tune for Sports Day” asks for text. (a) True (b) False
  31. 31.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) only one kind of example (d) photos in many lights
  32. 32.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
  33. 33.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
  34. 34.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  35. 35.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recognising (b) generating (c) recommending (d) predicting
  36. 36.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  37. 37.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  38. 38.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  39. 39.True or false: “learns from examples” describes how a normal program works. (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) AI can be wrong (b) AI can make up facts (c) AI answers need checking (d) AI is never wrong

Answer key

  1. music or sound
  2. a simple rule is enough
  3. True
  4. not AI
  5. training data
  6. False
  7. False
  8. a simple rule is enough
  9. False
  10. reduces bias
  11. a stopwatch
  12. AI
  13. old emails marked spam
  14. balanced data
  15. a myth
  16. drawing a new picture
  17. bias from data
  18. unlocking with a face
  19. AI can make up facts
  20. reading number plates
  21. True
  22. True
  23. turning speech to text
  24. False
  25. True
  26. predicts likely words
  27. True
  28. uses AI
  29. True
  30. False
  31. photos in many lights
  32. a prediction
  33. a fact
  34. balanced data
  35. predicting
  36. a prediction
  37. adds to bias
  38. the trained program
  39. False
  40. AI is never wrong

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