✨ Study topic - How people classify , reason , and learn and what that means for AI
📌 Main Idea - This project explores how different people , shaped by their backgrounds and experiences , identify and do everyday tasks. The goal…? To understand how human learning works not just to study people , but to uncover principles that can inspire better AI.
👀 Objective - We’re trying to answer a simple but powerful question - “How do humans know what something is” By observing people in everyday situations looking at objects , reacting to jokes , recalling facts we can break down how human thinking actually happens. And then we can compare that to how artificial intelligence models work.
Prompt: “Why do you think the thing in front of you is an AC and not a cooler…?”
Siblings ( same home, same environment )
| Feature Used | Type | Notes |
|---|---|---|
| Cooling speed | Functional | AC cools faster — felt in real life |
| Water tank visibility | Sensory | Coolers need water , AC don’t |
| Sound | Auditory | Coolers are noisier |
| Size | Visual | Cooler is bigger, AC is smaller |
| Color bias | Visual bias | ACs often white, coolers grey visual shortcuts |
| Language exposure | Repetition | “Turn on the AC”, “Where’s the remote?” language shapes recognition |
| Social correction | Social feedback | Mistaken labels corrected by others and remembered |
| Electricity bill awareness | Contextual | ACs are known to increase bills, coolers don’t |
Humans don’t use just one rule they mix sensory input, habits, social corrections, and context. It’s a multi-sensory, multi-layered system, kind of like how AI models use multiple inputs and feedback loops.
Prompt: “By looking at this image, how can you tell it’s a pen and not a pencil?”
Friends ( Different personalities and thinking styles )