There is a lot of talk in social science departments about the correlation/causation gap and to what degree can causal claims be justified from association data. Those discussions might be clichéd by now, but they are still important and furthermore address issues in decision theory, policy, and experiment design that are more relevant now than ever. But this post is not about the distinction between causation and correlation; it's about the distinction between causes and reasons. Both causes and reasons factor into explanations for social phenomena, but their roles ought to be different because causes and reasons are different. The distinction and their differences are sometimes less than fully appreciated and I've got a few things to say about that here and now.
There is a common inclination in cases of deep uncertainty to apply probabilities uniformly across all possible future states, despite this inclination being unsupported by any theoretical principle. The notion may be derived from (i.e. be applied analogously from) the behavior rules guiding distributive justice wherein it is accepted that, if differentiating reasons are not to be found, then dividing a resource (or requirement) equally among possible recipients is prescribed. The rule internalized for the historically common cases of distributive justice in past human society may be providing the uniform probability distribution intuition in the decision calculation procedure. This case might therefore be an instance of the evolutionary history of humans generating a reliable bias in modern human decision problems and thus merits consideration for institution design.
Anybody who is at least a quarter awake will realize that we need to be concerned with sustainable economies and ecologies in light of burgeoning populations and limited resources. Anybody at least half awake will realize that current practices and trends are not sustainable. While the notion to be "green" is given a lot of lip service, and companies claim to be environmental friendly as a publicity technique, the sad truth is that a vast majority of companies and people really don't give a damn. If people can't even be bothered to stretch their arm a few extra inches to put paper in the recycling bin instead of the garbage can, then the future of society looks rather dim. Perhaps a complex systems approach to institutional design can find a way shift people's behavior away from destroying the planet and mankind's future.
Jun 28: Foci for Modeling Social Systems
There are three core techniques for modeling behavior and interaction in social science models. Connectivity is the idea that the most important aspect of a social system is who interacts with whom and so ought to be modeled using networks. Other models, including rational choice models, focus on beliefs; the agents', and hence model's, behavior is generated by maximizing expected utility given the agents' beliefs and "learning" is captured via belief updating. The third main option in modeling is to focus on agent behavior, the actual acts they perform, instead of the invisible forces that produce it. Some of the differences are subtle and the techniques overlap, that is why I am referring to them as foci.
Jan 30: Institutions as Ecologies
One major focus in political science is the role of institutions, particularly for social choice problems. I was thinking about the relation of individual policy decisions and the institutional framework within which they are made and it occurred to me that the relationship has some analogies to the relationship of species evolution and ecological change. Specifically, analogies exist with regard to the i) time scales, the ii) forces exerted on each other, iii) endogenous stability, and iv) susceptibility to exogenous perturbations.