Social sciences are becoming increasingly interested in Evolutionary Theory. For instance, management research is making increasingly usage of the NK-Model.
However, Evolutionary Theory is only partially known by social scientists. In particular, the two following aspects have gone unnoticed hitherto:
Scholars point to organizational routines as the equivalent of genomes. However, nobody has ever exploited the similarity between organizational routines, that are sequences of actions, to connectionist concepts and tools that describe distributed memories in the brain as sequences of neuronal signals that circulate in closed loops. Organizational decision-making, organizational cognition and organizational culture can be better understood if connectionist concepts are employed.
Evolutionary dynamics includes non-trivial phenomena such as:
Punctuated equilibria: Long periods where nothing happens punctuated by occasional revolutionary breakthroughs;
Multi-level selection: Selective pressures may either operate on the organism, or on the species, or else;
Exaptation: Traits that have been selected for a specific function may be used for a different function after some time.These and other features could be used to gain a better understanding of social and economic dynamics, yet to our knowledge little has been done in this sense hitherto.
A further difficulty is that substantial progress in the application of Evolutionary Theory to social sciences requires extensive computer simulations. With this course we want to teach concepts and tools that provide social scientists with opportunities to carry out innovative research based on evolutionary computational models. Assuming that students know the basics of computer programming, we would illustrate the following tools:
Unsupervised neural networks;
The NK model and the Tangled Hierarchies model.
Emphasis on computational tools will be complemented by due discussions of relevant psychological, sociological, economic and biological theories including:
Naturalistic Decision-Making;
Actor-Network Theory;
Technological Paradigms and Technological Trajectories;
Biosemiotics and Code Biology.
Students will be exposed to possibilities for carrying out empirical research, including:
Further information: