SFI Innovation Short Course 2016 - A theory of invention and innovation
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|Networks Short Course 2017|
A theory of invention and innovation
Building on the empirical, modeling and theoretical research of SFI-affiliated researchers, our project seeks to develop a rich understanding of invention and innovation in specific domains, to identify robust similarities in the processes by which invention and innovation occur in different areas as well as the connections and between them, and to build a formal theory for the origins of novelty.
Innovation research at SFI falls into five broad categories:
1. A General Framework for Explaining the Origins of Novelty
The history of life and human history is a history of change: of adaptations exquisitely matching structures to function; of species diverging in response to changing environments; of Homo sapiens spreading far beyond its original habitat; of new cultural practices and enduring norms becoming obsolete; of institutions transforming to avoid irrelevance; of technologies improving. This biological and socioeconomic-cultural history is also one of novelty. New metabolic pathways, species, cultural practices, occupations, technologies and ideas are “new” in the sense that they have few antecedents, and it is difficult to connect them with what existed before. A useful distinction is that between invention and innovation. Invention is the generation of something new: a new object, product, process, design, functionality or material not previously available. In contrast, innovations are successful or adopted inventions: successful in the sense that they are put into production or wide-spread use, or are selected and thus leave an evolutionary footprint. Innovations often involve the incremental improvements of existing solutions. The strongest suggestion that there are common generative processes at work—and therefore a general and formal description (i.e., theory) waiting to be built—is the common treatment of cultural, socioeconomic and cultural change as resulting from evolutionary processes. The terms “evolutionary economics”, “cultural evolution” and “technological evolution” or “knowledge evolution” denote not just rich metaphors but analytically formal descriptions. There are also empirical similarities in the processes that originate variations and novelty, which have been studied and measured in the biological and socioeconomic-cultural-technological domains. But these initial clues have not yet led to a cohesive framework, nor have the specific forms of selection involved in different realms been clearly identified. Our project moves towards the ambitious goal of building a general framework for understanding the origins of novelty in the biological and socioeconomic-cultural domains.
Our research is animated by the following specific questions:
While evolution is primarily a process of tinkering, the process needs variations and novelty to tinker with. Where does evolutionary novelty come from?
Are there commonalities in the processes that generate novelty, regardless of their physical manifestations?
What features of systems make them capable of innovating?
What is the role of scale (size) in making systems inventive and “innovable”? If more is indeed different, is more also more innovative?
Is there a theory that might explain the basic mechanism of creating novelty that we might use to better understand and shape our world?
2. Understanding Technological Change
Technological change has long been recognized as a major driver of human development and economic growth. (Technologies are ideas about how to re-arrange matter, energy and information; they are means to fulfill human needs; they are artifacts, devices, methods and materials available to humans to accomplish specific tasks.) Major historical epochs, eras and transitions—the transition from hunter/gatherer lifestyle to sedentarianism, the agricultural revolution, the Iron Age, Age of Sail, the Industrial revolution—are delineated largely on the basis of what technologies were deployed by humans and by the cultural, economic and institutional practices enabled by the prevailing technologies. Yet the archaeological and historical records unmistakably tell us that the pace of technological change has accelerated over the past two centuries. What circumstances engendered this acceleration? And are these circumstances ephemeral or do they constitute a semi-permanent feature of human civilization? Besides being inherently interesting, a robust understanding of the nature of technology and technological change, for which a theory, or set of theories, of technological change is needed as a precondition for the design of effective policies to address the challenges of sustainable development and adaptation to climate change? We aim to integrate insights from anthropology, archaeology, human ecology, economies, operations research, engineering, economics and evolutionary biology. Specific questions include: What is the nature of technology? What is the nature of technological change? Are there generators of technological change common across the history of our species? Is technological change an instance of cultural evolution? Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Are there robust empirical regularities in the manner and rate of technological change? Can these regularities inform the construction of predictive models of technological change?
3. Innovation in Cities
Inventors and innovators do not operate in isolation; the creation of new ideas is a process that very often involves the integration and recombination of existing knowledge from different individuals, locations, institutions and organizations. The size, density and compactness of urban centers foster interpersonal interactions, thus creating greater opportunities for enhanced information flows. As a result, historically cities have been the places where much innovation has occurred. The privileged role that cities have played in the development of science and technology, and more broadly, in the generation of inventions and innovations—intellectual and material, cultural and political, institutional and organizational—has been well documented by historians, urbanists, geographers, anthropologists and regional economists. Invention and innovation in cities has been a central concern within the overall effort at developing a general framework for understanding the drivers of urbanization (http://www.santafe.edu/research/cities-scaling-and-sustainability/)) across time and space. Cities are social networks embedded in physical space: under what specific conditions do these networks generate inventions and innovations? Conversely, what can dampen the innovativeness of agglomerated populations? What are the general features of invention and innovation networks in human settlements and cities?
How does innovation in cities generate socioeconomic development?
In what ways do inventive and innovative behaviors manifest themselves in urban agglomerations?
4. Evolutionary Innovations as a Case of Extended Evolution Theory
Here we focus on the challenge of re-conceptualizing parts of evolutionary theory in order to account for the evolution of innovations within complex systems across scales. Innovation, the generation of novel characters or behaviors, as opposed to standard patterns of variation and adaptation, involves not only the transformation of regulatory systems, but also the kind of interactions between systems and their environment that have been described as niche construction. Explanations of innovations require a detailed understanding of the generation of phenotypic variation that goes beyond referring to mutation as the fundamental variation-generating mechanism. These explanations must account for the specific features of regulatory networks at different scales—including changes to both the structure of these regulatory networks in form of rewiring genomic and other forms of interactions, the transformation of individual elements of these networks by means of mutations in a broad sense, the addition of new elements to the network, as well as a more complex account of the interactions between systems and their various environments than is provided by an aggregate measurement of fitness. Rather, we also need to understand how systems actively construct their relevant niches (or how technologies create demand) and how these constructed niches, in turn, affect the possibilities of future transformation of these systems. This last point captures the path-dependent nature of evolutionary change. Technically this is a question about the structure of search spaces and how they affect evolutionary dynamics. Of the competing views—one that defines a search space abstractly as the sum of all possible combinations at a particular level of a biological hierarchy (such as a sequence space for RNA or DNA molecules of a particular length or sum of all possible metabolic interactions within a particular pathway); the other that argues that in the case of complex systems the search space of future possibilities is actively constructed by the actions and properties of currently existing systems—we clearly argue for the latter. For us, within the current extended landscape of evolutionary biology, the challenge of explaining evolutionary innovations translates into the need to integrate the complex transformations of regulatory networks and their elements with niche construction perspectives, a challenge we refer to as extended evolutionary theory.
5. The Evolution of Knowledge
We aim to develop a conceptual framework for analyzing the history of knowledge from the perspective of extended evolution. This framework analyzes evolutionary processes as transformations of extended regulatory network structures, and is designed to apply to a whole range of phenomena, from genome and biological to cultural and technological evolution. All of these phenomena can be seen as a form of extended knowledge evolution. A general feature of this framework is the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches. Externalization refers to the stable or lasting transformation of niches (biological, cultural, social and technological) through the actions of systems whereas internalization captures those processes that lead to the incorporation of stable features of the environment(s) into the regulatory structures governing the actions of systems. These processes extend previous evolutionary models and focus on several challenges, such as the path-dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems that characterizes cultural products such as science, technology, institutions and cultural traditions.