Evolutionary theory of technological change: State-of-the-art and new approaches

Abstract

It is well known the fact that the world of technology is full of biological metaphors, as for instance, evolution, mutation, selection, life cycle, survival of the fittest, etc. One of the most powerful technological forecasting tools, the logistic equation, has its origin in the biological realm and has won the status of a ‘natural law’ of technology diffusion due to its considerable success as an empirically descriptive and heuristic device capturing the essential changing nature of technologies, products, markets and industries. Viewed on the most general level, living systems, from cells to societies, exhibit common properties, with some attending intrinsic fundamental invariants. Recognition of this fact in last decades is leading firmly to a new scientific paradigm, a complex bio-socio-economics, with the convergence of different fields of science toward what may be the clue to understand the modus operandi of ‘evolution’ per se—the development of evolutionary algorithms for many different problem-solving and/or theoretical applications. The fields of evolutionary computation and artificial life have reached a stage of some maturity and we are witnessing today an intense debate on ‘universal Darwinism’ as a broad theoretical framework for the analysis of the evolution of all open, complex systems, including socio-economic systems. This debate has been in great part centered on the striking similarities between biological evolution and technological/cultural evolution. This paper, divided into four parts, intends to present the state-of-the-art on this debate and tries to answer the question on the validity of evolutionary models of technological change. After some introductory thoughts in the first part, it is tried in the second part to summarize in five points some of the still missing pieces to complete the puzzle to developing a firmly based Evolutionary Theory of Technological Change (ETTC). Each of these five points are then discussed more in detail in the third part, being also commented on briefly the most promising approaches under way. The fourth part with conclusions closes the article, making six fundamental theoretical considerations that were not yet accounted for in formal models and/or simulations of technological systems stand out.