a complicated system is defined by a finite and bounded (unchanging) set of possible dynamic states, while a complex system is defined by an infinite and unbounded (growing, evolving) set of possible dynamic states.
. . .In the case of complication, the optimal choice is to become an “expert”. That is, to grasp the whole of the system such that one can make precise predictions about how it will respond to inputs.
In the case of complexity, the optimal choice goes in a very different direction: to become responsive. Because complex systems change, and by definition change unexpectedly, the only “best” approach is to seek to maximize your agentic capacity in general. In complication, one specializes. In complexity, one becomes more generally capable.
I found this distinction to be interesting. I would argue that mainstream economists treat economic problems as complicated, to be mastered by the expert. Those of us who lean toward Austrian heterodoxy treat economic problems as complex, best dealt with by adaptation.
I recommend the entire essay. His theme is the challenge that social media poses for human culture. As you know, this topic interests me a great deal.
Great essay.
4 foundational problems:
Supernormal stimuli;
Replacing strong link community relationships with weak link affinity relationships;
Training people on complicated rather than complex environments; and
The asymmetry of Human / AI relationships
On the first one, there is a huge amount more that could be written.
Our ability to give ourselves what we want has far outstripped our ability to sense what we really need.
This is the true problem of civilization, but also Libertarianism. And why J. Peterson is so successful right now, millions of mostly men know he’s offering what they really need.
The free market is great when rational agents want what is good for themselves, but not always so great when what they want is bad.
To the great difference between mostly static complicated (often zero-sum) and complex, needing responses because of changes, the macro folk are wrongly trying to solve for a complicated equilibrium (or other model solution). The micro folk are usually doing this, too, but better. In any given micro regime, the expert who knows more of the complications is more likely to give a better result.
We need much better game theory than 2 person zero-sum stuff; there’s a big hole in economics about this.
A bit of bunk. Austrians treat the unknown as unknowable whenever knowing would be unpleasant, like Hogan’s Heros Shultz, ‘I know nothing’ but as unquestionably known when it favors their pre existing aims, just an ideology.
Pot meet Kettle
The generally capable manager has a specific trait, he has the deja vu antenna. He thinks, ‘I have seen that before, and take preventative action. nHis action is equivalent to setting up a hedge against the repeat.
The result,in sample space, is an asymmetrical, two sided sampler, customers and clerks in WalMart. The astute manager slight undersamples with clerks and over samples with customers, gets them congestion to match orderbook uncertainty.
The person you want is the WalMart floor manager. He can live in the congested chaos of inventory in and out while working stable queues of 1 or 2 people per line at check out or 0 to 1 clerks at the register.
This person minimizes matching error. In the job, the person allows just enough chaos to define the limit, or boundary of very symmetric distributions. So finance has a real good idea on price an and out bounds that keeps the store stable.
So far the progress in AI has been in his “complicated” domain. I wonder whether expanding into his “complex” domain will be as easy. This question bears directly n his last point.
Having read Boudreaux for years he always makes the case that you can determine some things by correct economic thinking. It may be complicated, but there are answers. Going even further he rejects empirical evidence when it disagrees with his economic thinking. So I think there is a fair bit of truth in the assertion above that libertarians often conveniently decide what is complex vs complicated.
Steve