My mission as a researcher is to develop, test, present my best
ideas about complexity and emergence in political systems.
“As in other departments of science, so in politics, the
compound should always be resolved into the simple elements or
at least parts of the whole.”
Aristotle. The Politics. Book 1, Section
Reductionism has long been a hallmark of science because of the hope
that we can observe the parts that make up the system we are interested
in. But, reductionism can only take us part of the way on the journey
of understanding. A much more difficult problem is faced when we try
to see what happens as the parts interact. Occasionally, we find that
very simple parts, interacting in very simple ways, give rise to very
complex behaviors. Complexity theory is a broad movement in science
trying to develop systematic ways to approach problems from both the
top-down and from the bottom-up. Because computers can implement rules
again and again while keeping track of the results, they are ideal
tools for the kinds of thinking that complexity theory is based on.
My broad ambition is to develop a theory of the emergence of ideology
that draws from multiple levels of analyses:
My work in neuropolitics aims to study the neural substrates of
differences in political behavior between people who know a lot about
politics and those who do not. My contention is that the transition
from novice to expert in politics is like the transition from novice
to expert in other domains and involves similar shifts from controlled
to automatic cognitive processes.
I am currently developing a computational model of political cognition
as a further test of my theory of neuropolitics. I am applying recent
work in artificial intelligence to the context of political decision
making. The framework I am using is a hybrid symbolic/neural network
model, designed to unify two camps of research in the artificial
intelligence community as well as reflecting the notion of dual processes
(controlled and automatic) from psychology.
Once I have thoroughly evaluated these models of individual political
cognition, I plan on embedding them into my macro-scale model of
political party dynamics. The current version of my party dynamics
model uses very simplistic "sub-rational" agents who mindlessly
obey a small set of rules. However, they still manage to demonstrate
a number of classic behaviors from American politics. They usually
form a two-party system, their parties tend toward the center of
the political spectrum, the winning party tends to just barely win,
and the introduction of new political issues can cause the parties
The plan is to show that ideology is emergent phenomena. Ideology
is created neither by the individual voters nor by the political
elites, rather it emerges as a consequence of their interaction.
Understanding the neural underpinnings of political cognition improves
our comprehension of the limitations that individuals face in processing
a complex political environment. And, understanding the ways in which
elites and masses interact should enable us to understand that ideology
is both created and constrains elites and masses.
Note, that I am not claiming that all politics
reduces down to neurons. In fact, I would make the opposite claim.
I believe that Aristotle was right and that "man is by nature
a political animal." Evolutionary psychology suggests that the
reason we have such a big and capable brain is to solve the complex
problems posed by being a political animal. If neuroscience is really
interested in understanding the human brain, I would argue that we
need to develop an understanding of the human brain in the context
that necessitated it, politics.
When I was a graduate student at UCLA, there was an article about
me in GQ (Graduate Quarterly, not the chic men's magazine). It will
give you a good idea of what I am working on. Another good place to
look for the big picture of my research interests is in this statement
on my research background.
Other projects: Housing Segregation, Model Evaluation, Race Perception, Cocktail