Indeed, and there may be strong financial/legal incentives for doing so. Similarly, many developers may all be employed/funded by one organisation, and multiple clients may share large amounts of code (and be unable to avoid accepting large changes made to the upstream project).
So, while I appreciate the great effort to quantify the level of decentralization in the cryptocurrency space, I think the article mostly just exposes the subjective decisions being made by people who make claims about decentralization. Even that could be a big step forward for debating these technologies, though.
> We certainly don’t argue that the particular choice of six subsystems here is the perfect one for measuring decentralization; we just wanted to gather some data to show what this kind of calculation would look like. We do argue that the maximum Gini coefficient metric starts to point in the right direction of identifying possible decentralization bottlenecks.
It seems the article is mostly to reframe the discussion.
I haven't even seen bad versions of these measures compiled before. Debating the choice of bucketing strategy (and other such) is a massive improvement.
According to the author's definition, both Bitcoin and Ethereum have a Nakamoto coefficient of 1 and a Geni value of ~0.92, meaning that they are equally centralized and brittle.
How is the proposed metric any useful in measuring and comparing decentralization of blockchains?
They discuss this, it shows how both Bitcoin and Ethereum have different dominating factors, how one has centralization in some areas the other does not and vice versa. Use the resulting numbers are the same, but examining how they were arrived at is the interesting point. It's not like positions of two balls at time 0 is the interesting number, it's how their differing properties affect the equations that determine their eventual position.
