Data Labeling
Tagging data (like photos or text) with labels so an AI model can learn from it.
👩🏫 How to Explain by Age Group
Elementary (K–5)
“Data labeling is like putting name tags on things, like calling a picture of a dog “dog” so the computer knows what it is. It helps AI learn by giving it clues.”
Middle School (6–8)
“When we label data, we’re telling the AI what it’s looking at, like marking an email as “spam” or tagging a photo with “tree.” It uses these labels to learn how to spot patterns.”
High School (9–12)
"Data labeling is the process of annotating raw data with categories or descriptions so AI can learn from it. High-quality labels are critical for training accurate models in tasks like classification, sentiment analysis, or object recognition.”
🚀 Classroom Expeditions
Mini-journeys into AI thinking.
Elementary (K–5)
Give students a set of pictures and have them group and label them. Then explain: “This is what we do for computers when we want them to learn.”
Middle School (6–8)
Let students create their own mini-datasets by labeling sets of sample text or images. Then talk about how AI uses these to “practice.”
High School (9–12)
Assign a mini project where students label a dataset (like class survey responses or image categories). Then analyze how quality and consistency affect AI accuracy.
