This is a great topic, the idea that contemporary computer systems are not atomically understandable or model-able. And it's a topic that's almost entirely abse

This is a great topic, the idea that contemporary computer systems are not atomically understandable or model-able. And it's a topic that's almost entirely absent from computer science discourse. We passed the point quite a while back where "applied CS" -- what it's like to build and maintain scalable systems in the real world -- looks a lot more like anthropology than like mathematics. We have tools like sampling profilers, loggers that do stateful packet inspection on a small percentage of traffic, and sophisticated A/B testing frameworks that reason about user populations rather than individuals. But I think we could probably build a whole 'nother generation of these tools by thinking about this problem of understanding complex systems from some new perspectives. I nominate anthropology as a discipline that has many years under its belt wrestling with the impossibility of complete description. (And wrestling with other tough issues, sometimes not well, but that's another conversation.) I'm not talking about the kind of "anthropology" work that companies like Intel have done for a long time, which are firmly in the social sciences tradition and are really user studies. (Though that work is valuable.) I'm talking about porting ideas such as "thick description" to our technical toolkit. http://en.wikipedia.org/wiki/Thick_description