In the Center for Complexity and Collective Computation at the Wisconsin Institute for Discovery
C4 scientists are interested in an exciting new computational, cultural and evolutionary trans-discipline emerging at the intersection of (i) computational tools for the analysis of large textual databases and highly structured network data, (ii) high quality widely accessible cultural databases, and (iii) advances in the analysis of evolutionary dynamics.
Rarely—if ever—has the intersection of all three of these areas been the focus of a research program. Different communities tend to emphasize one of these at the expense of the others, and this has limited our ability to ask fundamental questions about cultural evolution. Some of the deepest questions include:
Are there fundamental units of cultural transmission?
What are the rules of cultural transmission when dealing with complex and structured data beyond simple one dimensional-traits?
How do these units come together to assume new meanings, giving rise to new cultural entities?
What are the major transitions in cultural evolution?
Are there trends in cultural evolution, such as towards increasing hierarchy, efficiency, complexity or ultimately collapse?
What are the driving forces behind cultural change? These could include increased robustness, ongoing conflict, and the need to manage uncertainty.
What is the relationship among cultural systems - such as art and politics, law and economics, technology and growth? And how do these coevolve?
How do we move between individuals as the agents of cultural change, to the pervasive role of institutional feedback in constraining and guiding agent activity?
Can we map out socio-cultural differences in terms of the relative roles of agents versus institutions, and how these vary through time?
These are all very big questions, which have long been considered by anthropologists and a wide range of social scientists. However, although descriptive knowledge of these questions has grown significantly, our theoretical-modeling understanding has not grown apace. Recently great increases in the quality and abundance of cultural data, coupled to ever increasing computer power and algorithm design, brings many of these fascinating issues into the reach of quantitative research in completely new ways, and we believe that such research will shed much light on the "hows" and "why" of cultural evolution.