Hierarchical modular network structure is an organizing principle found in many complex systems, ranging from ecosystems to human brain, and of course it is commonly seen in social networks. By “modularity” we mean, technically speaking, that there are parts of a network that are more densely connected than in random networks. This can have various causes, like spatial proximity or functional consideration. These densely connected parts often form hierarchies, where smaller units are parts of larger ones. Hierarchical structures is the way how things are done in real world.
We can view the effective altruism movement as a network. Then, we may ask what its network structure is and what processes generated it. We may also ask a question what network structure it should have: how the network should be optimized for a given purpose (like changing the world for better).
In general, this seems a hard question, but possibly just looking from this perspective leads to some easier and more practical questions. Like:
- \ What is the optimal level of hierarchicality?
- \ How much should geography correlate with function?
- \ How much should things be localized
For the first question, we can easily imagine two possible answers:
1) Two level structure, where there are global EA organizations, and local groups.
2) Three level structure, where there are global EA organizations, country, region or language-specific organizations, and local groups.
It seems what effective altruism movement has at the moment is a mixture of both. There is CEA, which is at the same time the global organization and an anglosphere one, but also has some UK and Oxford flavour. On the other hand, we have also Effective Altruism Foundation, which is a mixture of country-wide organization for Germany, language-based organization, and a global one.
For the second question, at the moment we have a strong correlation of physical space and functional or meme-space. For example in Germany, people are much more than average focused on suffering reduction. People in Bay Area are more than average on long-term plans to influence AI, etc.
For the third question, it seems there are various forces pulling in different directions.
If we take an outside look, the whole does not seem to be a result of a design or some intentional optimization, but more likely a legacy of some “organic” evolutionary process with a lot of usual network effects and randomness. By network effects I mean for example homophily - people tend to link to people who are similar to themselves. This also leads to a disproportionate amount of influence of the “founding core” members of a cluster on the whole cluster.
Also what is interesting, the level of hierarchicality seem to be area-specific.
My intuition is this whole structure is far from optimal. Multinational corporations don’t work that way: imagine Google US being focused on search, Google UK on advertising, Google Germany on machine translation, and a lot of local Google subsidiaries doing recruitment of engineers. Or Wikimedia having not one organization for running the Wikipedia site and local chapters supporting different language versions of Wikipedia, but chapters which would mix topic and language focus.
I don’t want to propose solutions at this point: I’d like more effective altruists thinking about the question.