Most actions people take are not the result of deliberate reasoning.
You may be able to explain why a cat is different than a dog, but your brain doesn't go through that categorization process before recognizing a cat.
You may be able to explain why a cat is different than a dog, but your brain doesn't go through that categorization process before recognizing a cat.
Take for example persons with androgynous features and the difficulty some people have with identifying them. Children are particularly useful for this insight since they are unabashedly curious and inquisitive, and it's not uncommon to hear a child blurt out "is that a boy or a girl?"; it would seem to me that their categorization process, even if not refined, gets goofed by androgyny; something as simple as hair length or facial hair greatly influences a child's ability to easily discern if persno is male or female.
At some level there is a categorization process that seems to happen with humans when it comes to recognition, we just assign high confidence to certain factors. In the case of children, it seems to be they look at person and use common factors like hair length, facial hair, and body shape to determine gender. The sound of one's voice also helps, but this usually isn't something we can pick up as easily or from afar in public places. As an adult, we probably have more refined points, but they are essentially the same as a child's point of view. Instead of "body shape" adults look for specific facial features, size of breasts, walking gait, style of clothing, hair style, etc. These are all just granular differences of how a child understands it.
This gets into personal experience, but when I was in college, I had long hair and really fine skin/facial features. All the time I would hear little kids ask "why does he look like a girl?" or "why does that girl have a beard?". I had no issue with their confusion, they were just curious kids. Something confused their understanding, and once it was explained "sometimes men have long hair", they just sort of accepted it.
We've added instrumentation to our recognition capabilities in order to socialize and gossip about derived categories through language. In addition, we (can sometimes) use the formalized expressions of these categories prepared for socialization to ensure internal consistency.
Artificial neural networks that did something similar could have a number of major philosophical and practical advantages: - enable decentralization of data sets - grow with humans rather than apart from them - enable identifying problematic internal inconsistencies
Sometimes I "know" a design is bad. Explaining why to others requires stepping through a process that May or may not be the one my brain used to make that approach "feel" wrong.