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AI Hallucination Worksheet

AI for students lesson 6: When AI is wrong: hallucinations · Set 534 · 40 questions
TalentJR

AI tip (Sounds sure ≠ is true): A hallucination is a made-up fact, name or source that an AI states as if it were true. Facts: AI can be wrong, can make up facts and can sound sure while wrong. Myths: AI is never wrong, AI knows everything, confident means correct. Real checks: match it to the textbook, ask your teacher, find a trusted source, redo the maths yourself. Not checks: it sounds sure, it is long, it looks neat, asking the same AI again.

NameDateTime takenScore ___ / 40
  1. 1.🔍 Which is the odd one out? (a) AI can be wrong (b) AI copies data patterns (c) AI can mix up numbers (d) long answers are true
  2. 2.True or false: “AI always checks facts” is a myth about AI. (a) True (b) False
  3. 3.📅 An AI gives a date for a history event. How can you check? (a) pick a lucky number (b) look in your textbook (c) guess (d) ask it to repeat
  4. 4.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) share it online (c) trust the textbook (d) stop studying
  5. 5.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
  6. 6.🧐 Fact or myth: “confident means correct”? (a) a myth (b) a fact
  7. 7.🔍 Which is the odd one out? (a) confident means correct (b) AI can make up facts (c) AI knows everything (d) AI always checks facts
  8. 8.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  9. 9.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI copies data patterns (c) AI knows everything (d) AI learns from data
  10. 10.True or false: “asking the same AI again” is a real way to check an AI answer. (a) True (b) False
  11. 11.True or false: “AI can mix up numbers” is a fact about AI. (a) False (b) True
  12. 12.✅ Is this a real check of an AI answer: it uses big words? (a) a real check (b) not a real check
  13. 13.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, if it is long (b) no, check it anyway (c) yes, always
  14. 14.Which of these is a fact about AI? (a) AI has real feelings (b) confident means correct (c) AI can be wrong (d) long answers are true
  15. 15.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) ask it to hurry (c) check it on paper (d) never do maths
  16. 16.Which of these is a fact about AI? (a) AI is never wrong (b) AI answers need checking (c) AI has real feelings (d) confident means correct
  17. 17.Which of these is a myth about AI? (a) AI can be wrong (b) AI copies data patterns (c) AI can mix up numbers (d) AI is never wrong
  18. 18.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
  19. 19.True or false: “AI knows everything” is a myth about AI. (a) False (b) True
  20. 20.✅ Is this a real check of an AI answer: it sounds very sure? (a) a real check (b) not a real check
  21. 21.Which of these is a fact about AI? (a) AI has real feelings (b) confident means correct (c) long answers are true (d) AI can mix up numbers
  22. 22.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
  23. 23.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can make up facts (c) confident means correct (d) AI can mix up numbers
  24. 24.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check
  25. 25.True or false: “try the sum on paper” is NOT a real way to check an AI answer. (a) False (b) True
  26. 26.True or false: “see if the book exists” is a real way to check an AI answer. (a) False (b) True
  27. 27.True or false: “it has a neat layout” is a real way to check an AI answer. (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) AI knows everything (b) AI copies data patterns (c) AI is never wrong (d) AI has real feelings
  29. 29.🔍 Which is the odd one out? (a) AI knows everything (b) AI has real feelings (c) AI answers need checking (d) AI always checks facts
  30. 30.✅ Is this a real check of an AI answer: try the sum on paper? (a) a real check (b) not a real check
  31. 31.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI learns from data (c) AI copies data patterns (d) confident means correct
  32. 32.True or false: “redo the maths yourself” is NOT a real way to check an AI answer. (a) True (b) False
  33. 33.True or false: “long answers are true” is a fact about AI. (a) True (b) False
  34. 34.🔍 Which is the odd one out? (a) AI can be wrong (b) AI has real feelings (c) AI can make up facts (d) AI answers need checking
  35. 35.True or false: “AI can be wrong” is a fact about AI. (a) False (b) True
  36. 36.Which of these is a myth about AI? (a) AI can make up facts (b) AI can be wrong (c) long answers are true (d) AI learns from data
  37. 37.🔍 Which is the odd one out? (a) AI answers need checking (b) AI knows everything (c) AI can be wrong (d) AI copies data patterns
  38. 38.Which of these is a fact about AI? (a) AI has real feelings (b) AI knows everything (c) long answers are true (d) AI learns from data
  39. 39.True or false: “AI can be wrong” is a myth about AI. (a) True (b) False
  40. 40.Which of these is a fact about AI? (a) AI knows everything (b) AI always checks facts (c) AI copies data patterns (d) confident means correct

Answer key

  1. long answers are true
  2. True
  3. look in your textbook
  4. trust the textbook
  5. a fact
  6. a myth
  7. AI can make up facts
  8. a fact
  9. AI knows everything
  10. False
  11. True
  12. not a real check
  13. no, check it anyway
  14. AI can be wrong
  15. check it on paper
  16. AI answers need checking
  17. AI is never wrong
  18. a fact
  19. True
  20. not a real check
  21. AI can mix up numbers
  22. a fact
  23. confident means correct
  24. not a real check
  25. False
  26. True
  27. False
  28. AI copies data patterns
  29. AI answers need checking
  30. a real check
  31. confident means correct
  32. False
  33. False
  34. AI has real feelings
  35. True
  36. long answers are true
  37. AI knows everything
  38. AI learns from data
  39. False
  40. AI copies data patterns

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