Evolutionary Theory of Technological Change: Discussion of Missing Points and Promising Approaches

Devezas, T.C. (2005). Evolutionary Theory of Technological Change: Discussion of Missing Points and Promising Approaches. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-05-047

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Abstract

There are concerns that in order to exploit the powerful new capabilities provided by the Information Technology Era, it is necessary to advance Future-oriented Technology Analysis (FTA) of both product and process. Among these new capabilities, the FTA Methods Working Group has recently identified three main converging areas of development: complex networks, simulation modeling of complex adaptive systems (CAS), and the search of vast databases. Such convergence has rejuvenated the growth of FTA methods and practice, much in accordance with the perspective envisioned in Linstone (1999), following his optimistic view of a strong, confident technology-driven scenario, which would bring a renewed impetus toward new methods in technological forecasting.

Focusing on new methods related to the new capabilities, we must borrow the discussion of methods and tools that have explosively grown in recent years in the fields of biosciences, bioinformatics and evolution. Among the needs for FTA envisioned by the FTA Methods Working Group, we find a questioning about the validity of the analogy between technological evolution and biological evolution (TFA Methods Working Group, 2004): Can artificial technological worlds be created by simulation modeling analogous to biological ones? This question is hardly a new one, and we can even trace at least a three-decade long debate on this issue. What makes the difference today, are exactly those powerful new capabilities provided by the Information Technology Era and the manifold convergence of information and molecular technologies that are contributing enormously to new insights in simulation methods and evolutionary programming. In the previously cited 30-year anniversary issue of Technological Forecasting and Social Change, Bowonder et al (1999); briefly reviewed this topic by mainly focusing on some of the lessons learned from evolutionary theory as it anticipates changes in evolutionary trajectories, and proposed a research agenda for future research. But these authors have not considered, in detail, the new capabilities and have not identified the possible problems and obstacles that must be overcome to transform evolutionary approaches into useful forecasting tools.

The present paper intends to present the state-of-the-art on this debate and to address some important considerations necessary to answer the above question. The sense one gets from the published literature on this theme is that the effort to-date has been primarily centered on the striking similarities between biological evolution and technological evolution and is mostly based on verbal theorizing. It seems that a synthesis of biology and technology remains beyond reach, with some people even doubting whether it can ever be achieved. In the following lines we intend to point out and briefly discuss some quite important aspects that have been overlooked and misinterpreted in this exciting debate.

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