Interesting read. I'm all for decentralized systems but one important consideration which will likely be different for each scenario: is whether distributed consensus in x (ie. traffic lights, water, power) is more valuable to the participants than a statistical machine-learning based approach. The latter is optimized towards some predefined metrics (minimizing total average wait times in traffic), whereas a cryptocurrency approach is distributed to the whims/needs of independent actors ("I want to cross the street now").
The benefits of distributed independent actors is clear in some areas such as economics, where the system is so massive and chaotic attempts to control it via machine or human intervention often fail. Even when they continually adapt their models over time, they will never be a full replacement for the consensus of a market.
While markets are efficient they famously at times have a habit of acting irrational and counter-productive to participants needs. This is where in the present times human intervention (occasionally) out-performs pure markets. In the future, most of us expect machine-optimized models to out-perform both markets and centralized systems.
That may be the differentiation in the long term for which is better, which can provide the best value? Human consensus -> human consensus via machines -> machine consensus. We'll likely keep moving farther to the right of that flow as machine learning (AI) becomes better.
>While markets are efficient they famously at times have a habit of acting irrational and counter-productive to participants needs. This is where in the present times human intervention (occasionally) out-performs pure markets.
I think that this happens because markets are not yet perfect. You end up with conditions where one party can gain by doing damage to the rest.
As time moves forward, I imagine that markets will get a lot better. Game theory is a growing field where people are exploring this problem. I think that in many ways, cryptocurrencies address this problem for certain applications, and will continue to improve as we figure out exactly where cryptocurrency is most useful to us.
Markets can not change the fact that humans are not rational, no matter what assumptions people like to make about that. Game theory is littered with examples where the rational behaviour is X, but where humans largely favour decision Y because X rubs us the wrong way in some way or other. E.g. humans are in some cases perfectly content to put our lives at risk out of sheer stubbornness if someone has annoyed us enough - accounting for that in systems aiming for perfection is at best incredibly hard, but far more likely pretty much impossible. You won't see perfect markets. There is no "yet".
I don't think this is about human rationality, or a lack thereof. It's a about whether individual rationality leads to group rationality. Whether the interest of the individual is also the interest of the group. This story is a good example: https://www.youtube.com/watch?v=sb5hr-f3Tfg#t=95
I think you are right that things will improve, but for exactly the wrong reason. Truly efficient markets are the toy problems of economic modeling, not typically achievable in real problem domains. Perhaps counter intuitively, I think we will gain efficiency by getting better at modeling the inefficiencies... but the end result of this is no more a "pure" (in your sense) market than a modern particle model consists of Aristotelian atoms.
Having the intended behavior as an emergent property of a lot of independent actors is always better than programming it top-down in a way that can be controlled by a single entity or shutdown.
Unless you're trying to make a specific thing happen quickly. Emergent properties are are very hard to construct intentionally and are often unexpected. It's easier to reason about single-threaded programs or about multiple threads acting independently. Once you're talking about multiple threads of execution that don't act independently systems can get pretty hairy. I think that's the reason client-server/master-slave architectures dominate computing today. Here's hoping for a p2p future!
The benefits of distributed independent actors is clear in some areas such as economics, where the system is so massive and chaotic attempts to control it via machine or human intervention often fail. Even when they continually adapt their models over time, they will never be a full replacement for the consensus of a market.
While markets are efficient they famously at times have a habit of acting irrational and counter-productive to participants needs. This is where in the present times human intervention (occasionally) out-performs pure markets. In the future, most of us expect machine-optimized models to out-perform both markets and centralized systems.
That may be the differentiation in the long term for which is better, which can provide the best value? Human consensus -> human consensus via machines -> machine consensus. We'll likely keep moving farther to the right of that flow as machine learning (AI) becomes better.