The past few days at Sentosa have been clouded in gloom, with light rain starting every midnight. At this time, both outside the window and inside the room are quiet, but there's also a slight feeling of melancholy seeping in. Finally, today, while walking on the wooded path in front of the house, a few rays of sunlight shone down, warming my surroundings. I couldn't help but stop for a few minutes and spread my arms to embrace this long-lost warmth.
“At midnight, the sound of rain awakens, hastily closing the windows for calm.
Never fearing that the sky grows old, one day it will clear.”
Continuing from the previous discussion on Trust-Minimization, we explored the difference between trust minimization and trustless and discussed trust minimization's fuzzy concept from various perspectives. Today, we primarily look at the attributes of trust minimization when computed.
If computation is required, the first step might be to simplify the model. We can create a basic trust model to attempt to simplify and simulate the current trust situation in a system and calculate the current trust cost. For example, the trust cost between individuals in our society can be simplified by modeling society as a complex system of interactions between people, language, culture, social hierarchy, governance, and belief systems. However, constructing a trust model in this way is evidently complicated. If we simplify this model, we can generally abstract society into a system of human interaction, with other subsystems seen as subsets of this interaction. We could call this simplified model the "mini-society" model.
Once the system is simplified into a "mini-society", the construction of trust costs within the system can be analyzed.
The question is straightforward: what is the energy expenditure required to maintain a long-term relationship channel? Explicit costs are easier to analyze. For example, the apparent trust cost in the Bitcoin system often comes from its evident energy consumption. If a system starts with initial trust, as the system's entropy increases, the physical cost to maintain that trust increases.
Next are the explicit economic and governance costs. To maintain trust between us and the US dollar, the capitalist society has built an economic system mainly guaranteed by the US to ensure the safety and stability of this accounting system. To maintain a relationship with an object, the explicit trust costs involved in our interactions in the production and trading process are crucial. The strong association, Ownership, involves significant economic operating costs.
Additionally, there are explicit governance and cultural costs. Trust within a system also requires shared values communicated through language and culture. If friction in communication is too high, the trust cost for the entire system will rise. Within every system, trust costs among participants need to be ensured to a certain extent. If computable, this abstraction could focus on achieving consistency.
Lastly, there are implicit trust costs within the mini-society. These relate to past hidden trust costs, ongoing unseen trust costs, and potential future trust costs.
These three implicit costs are actually quite specific. Regardless of which level we are discussing, they are based on the past. This is because for most systems, a lot of the information we can obtain about the past often comes from the system's governance. Naturally, the actual trust costs that arise often exceed our estimates. Simply put, in theory, we cannot estimate the trust costs consumed by a society in the past because the history we know may not be the complete history. The existence of information entropy means that our estimates of past trust costs are often underestimated, whether this concealment of the past is deliberate or not. From a practical point of view, there is no system that operates completely transparently, let alone in smaller societies.
Another type is the trust cost that is currently occurring, but we find it very difficult to understand or see. For example, whether it's Bitcoin, the US dollar, or within our families and companies, when we analyze them, it's hard to see some trust costs that are consumed in the background to maintain some kind of ongoing consistency. We are all in a state of localized information bias, and this locality makes it difficult for us to understand the trust costs occurring in different parts. This local trap basically makes it difficult for us to analyze those invisible trust costs that are currently happening. For instance, it's hard to know the specific costs the US currently incurs to maintain the stability of the dollar.
Another type is the opportunity cost for potential choices. Due to the inertia of a certain trust model, the probability of making another choice naturally decreases, which is clearly an implicit trust cost. To maintain a certain fixed choice, the likelihood of a new type of trust model emerging is severely restricted. Simply put, having too many options is not always a good thing, but not having any options is often a bad thing. When a system operates and evolves over a long and complex period, higher degrees of freedom will naturally lead to many unexpected new opportunities. Whether it's the system's limitation on imagination or its long-term excessive pessimism, the probability of these opportunities emerging is greatly reduced. This reduces the overall luck value of a system, and this potential cost is also a very important aspect.
Of course, these implicit trust costs in smaller societies are often hard to detect, but they are often spread among all participants in the system in the form of cost shifting. If we continue to follow this philosophy of minimizing trust, we can simplify the trust model of a system through this small society model, then simulate the costs through the accumulation of these types of trust costs. Simplifying this calculation is key. To verify the validity of our simulation, we need a simpler verification method to make calculations simpler. That is to say, even if the simulation on the first day is very rough and vague, this minimization of trust allows us to constantly iterate in the future, which is crucial. However, we can elaborate on this part later.
“On paper, soldiers and horses are but grass and trees, not as vivid as dreaming of marching troops.
Only feeling the rapid passage of time, unlike the slowly entering scenery before the eyes.”
It's suddenly interesting to think about where I might be this time next year, just as I didn't know last year where I would be this year, and as this year I seem to have forgotten where I went last year. But it's indeed a bit exciting to think about this question itself.