AI for Kids Worksheet: Part 1 Test
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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
- 2.True or false: “what training builds” is training data. (a) False (b) True
- 3.True or false: “learns from examples” describes how AI works. (a) False (b) True
- 4.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) wrong labels (d) clear, sharp examples
- 5.Which of these adds to bias? (a) skip testing (b) fix wrong labels (c) test on many groups (d) check who is missing
- 6.💬 What do we call the request you type to a generative AI? (a) a prompt (b) a battery (c) a label (d) a password
- 7.True or false: “labelled fruit photos” is the model. (a) True (b) False
- 8.True or false: converting metres into centimetres only needs a simple fixed rule. (a) True (b) False
- 9.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
- 10.Which of these is a myth about AI? (a) AI learns from data (b) AI answers need checking (c) AI can make up facts (d) long answers are true
- 11.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
- 12.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it will shut down (d) it may get it wrong
- 13.True or false: “AI is never wrong” is a myth about AI. (a) True (b) False
- 14.True or false: “follows fixed rules” describes how AI works. (a) False (b) True
- 15.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
- 16.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add varied examples (d) ignore complaints
- 17.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
- 18.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
- 19.Which of these is bad for training a model? (a) labels added at random (b) correct labels (c) new data for testing (d) many varied examples
- 20.Which of these uses AI? (a) a stopwatch (b) a light switch (c) a microwave timer (d) photos grouped by face
- 21.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
- 22.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
- 23.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
- 24.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
- 25.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) test on many groups (d) copy old unfair choices
- 26.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
- 27.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
- 28.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) new data for testing (d) blurry, unclear photos
- 29.Which of these describes how a normal program works? (a) gives a likely answer (b) does exactly as coded (c) improves with more data (d) learns from examples
- 30.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
- 31.True or false: “does exactly as coded” describes how AI works. (a) True (b) False
- 32.True or false: a book app suggesting a story like your last one is AI recognising something. (a) False (b) True
- 33.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
- 34.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
- 35.True or false: “match it to the textbook” is NOT a real way to check an AI answer. (a) False (b) True
- 36.🧮 Which of these is NOT AI? (a) face unlock (b) a spam filter (c) voice typing (d) a basic calculator
- 37.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) an image (b) music or sound (c) text
- 38.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) the weather (c) its training data (d) its colour
- 39.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
- 40.True or false: an image generator drawing a robot from a sentence is AI recognising something. (a) True (b) False
Answer key
- not spam
- False
- True
- clear, sharp examples
- skip testing
- a prompt
- False
- True
- a real check
- long answers are true
- bias from data
- it may get it wrong
- True
- False
- True
- ignore complaints
- False
- a simple rule is enough
- labels added at random
- photos grouped by face
- makes something new
- a prediction
- True
- False
- test on many groups
- one-sided data
- True
- blurry, unclear photos
- does exactly as coded
- True
- False
- False
- True
- True
- False
- a basic calculator
- text
- its training data
- few child voices in data
- False
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students