Innovation in Biological, Social, Cultural and Technological Systems
The ability to innovate or to generate novelty is a defining characteristic of complex systems. Evolutionary, technological and social transformations all presuppose that at some point in time novelties occur. But what drives the origin of new processes, structures, organizations, artifacts, solutions or behaviors has until recently not been the focus of systematic research. Rather, models in evolutionary theory and economics have focused on the (adaptive) dynamics of variation and treated the origins of variation (i.e., novelty) as a black box. But, as science, technology and economic policy is increasingly concerned with fostering innovation and biological systems are analyzed within an engineering paradigm (systems biology and synthetic biology), integration of generative mechanisms that govern the origin of novel features of systems, with (adaptive) dynamics that describe the fate of variation in populations, cultures and markets is crucial if we want to understand and ultimately shape evolutionary, social and technological innovations.
Our project aims to develop a conceptual and modeling framework for the integration of generative mechanisms with population-level dynamics. We will approach this task in a broadly interdisciplinary fashion by first analyzing generative and dynamical models in different domains (phenotypic evolution, cultural evolution, technological change and scientific change) and extracting common principles and isomorphic processes. Next we will test to what degree these models can actually account for well characterized empirical test cases in those different domains. Focusing on the common structures of these models will then allow us to develop a generalized model for the origin and dynamics of novelties and innovations that combines generative and dynamical processes.
Our project is building on new insights in developmental evolution, complexity theory, anthropology, economics. technology studies and the history of science that have contributed to a conceptual shift recognizing the problem of the origin of novelty and innovation as a key theoretical issue in all those fields. It is now widely accepted that any complete theory of (evolutionary) transformations has two complementary dimensions: the origin of novelty and the (adaptive) dynamics that account for the subsequent fate of these novelties within populations. However, these two approaches are characterized by distinct epistemologies, methodologies and theoretical frameworks that present substantial hurdles for a seamless integration of these perspectives.
The problem is that one the one hand a set of generative theories and models focus on how different combinations of parts and rules of interactions (grammar) are able to generate both variation in character states as well as new characters (novelties), while on the other hand dynamical models describe the fate of variation within populations. This dichotomy is often cast as one between internal (generative, developmental) vs external (dynamical, statistical) causes. In reality, however, the problem is even more complex as the distinction into internal and external is often not as straightforward as it might seem. Environmental (external) factors can be an important part of generative mechanisms and in some cases generative processes can include adaptive or selective dynamics. Given these complexities we propose to first investigate well characterized test cases that include studies in in silica synthetic experimental evolution, the developmental evolution of the superorganism, the history of science and technology and the growth of societies and cities.
Between all these domains, we observe the emergence of common new perspectives and new questions:
These similarities raise the question whether they are the consequence of the application of the new 'complex systems' epistemology in both domains, and thus primarily an artifice of perception, or whether there are indeed substantive phenomenological similarities. In other words, whether the observed similarities are the consequence of a similarity in perspective (or 'lens'), or a more fundamental similarity between the processes and phenomena that characterize the two domains studied.