“ taxonomy is not automatically a great category for regular usage.”
This is great, and I love the specific example of trees as a failure to classify a large set into subsets.
Something that’s not exactly the same problem, but rhymes, is that of genre classification for content discovery. Consider Spotify playlists. There are millions of songs, and hundreds of classified genres. Genres are classified much like species/genus taxonomies— two songs share a genre if they share a common ancestor of music. Led Zeppelin and the Beatles are different, but they both derive from traditions of electric guitar which grew out of the blues which… and so on. So we say Led Zeppelin and the Beatles are the same genre, “Rock”. You can do this kind of classification in much greater detail to carve out new genres and subgenres.
However when it comes to utility and discovery, genres underperform. Despite being the same genre, there are few parties which shuffle between the melancholic “Yesterday” and the screaming “Ramble On”. People seek songs which are similar to others in strategy, NOT in tradition. As you said:
“tree is a strategy. Wood is a strategy. Fruit is a strategy. A fish is also a strategy”
Successful user created playlists on Spotify (ones which are public with lots of likes) tend NOT to use genre. The tend to be called something line “rainy tuesday drive home from work”, or “music school nerds playing ALL the notes”. Rather than carve out a subset using genre (a playlist is a subset of music), they define it by strategy.
A failure in taxonomy.
I’d be interested to see a cognitive consciousness model built around
considerations, the state space of consciousness. These are zallerian style associations of words and phrases that are either positive or negative
tracking. This is the active-conscious activity which is triggered an input
input. This of course is an element of the input space, either language or the union of language visual