Interesting — almost as if artificial complexity wasn’t such a massive subset of the modern economy (and therein employment), that “wicked learning environments” wouldn’t have to exist in the majority of domains.
Thanks, Eric. I take your point, especially in as much as it reflects how rent-seeking behavior shows up in so many systems. A lot of the complexity we deal with today feels like it's less about solving real problems and more about keeping certain structures in place—creating barriers and hoops to jump through instead of adding actual value. It’s like industries figured out that making things unnecessarily complicated helps ensure people need them, and that ends up creating these wicked learning environments where the challenge isn’t solving the problem itself but just navigating the mess. That said, it’s also why being a generalist feels like such a smart move. Hyper-specialization and all these silo effects we see are often downstream of the same rent-seeking behavior—forcing people into narrow lanes so they can’t question the bigger picture. Generalists, on the other hand, can connect dots across domains and spot where the artificial complexity might be masking simpler, better solutions.
The only use case that I’m aware of where artificial complexity can have value is in games. Apart from that, it has several use-cases, all of which are grounded in negative value propositions. Perhaps ironically, they are however often grounded in positive financial propositions.
I’ve come to learn that, in the modern world, economic value and financial value are all too often grossly asymmetrical. Perhaps this is partially related to the global economy being driven more by debt than by currency.
Interesting — almost as if artificial complexity wasn’t such a massive subset of the modern economy (and therein employment), that “wicked learning environments” wouldn’t have to exist in the majority of domains.
Thanks, Eric. I take your point, especially in as much as it reflects how rent-seeking behavior shows up in so many systems. A lot of the complexity we deal with today feels like it's less about solving real problems and more about keeping certain structures in place—creating barriers and hoops to jump through instead of adding actual value. It’s like industries figured out that making things unnecessarily complicated helps ensure people need them, and that ends up creating these wicked learning environments where the challenge isn’t solving the problem itself but just navigating the mess. That said, it’s also why being a generalist feels like such a smart move. Hyper-specialization and all these silo effects we see are often downstream of the same rent-seeking behavior—forcing people into narrow lanes so they can’t question the bigger picture. Generalists, on the other hand, can connect dots across domains and spot where the artificial complexity might be masking simpler, better solutions.
The only use case that I’m aware of where artificial complexity can have value is in games. Apart from that, it has several use-cases, all of which are grounded in negative value propositions. Perhaps ironically, they are however often grounded in positive financial propositions.
I’ve come to learn that, in the modern world, economic value and financial value are all too often grossly asymmetrical. Perhaps this is partially related to the global economy being driven more by debt than by currency.