Thomas Malthus’s concern over the differential between the growth of populations and the growth of the resources to support them underlies both Charles Darwin’s theory of natural selection, and much of traditional economics. But Malthus was wrong, at least over the long term.  Contrary to the predictions of the logistic growth model of Pearl and Reed in 1920, the population of the US did not top out at 197 million and has just reached 300 million. Economists have extensively addressed the issue of creation of wealth, most recently through the development of endogenous growth theory, and a clear conclusion of this work is the pivotal role played by innovations in ideas, physical technology and social institutions. Similarly in natural systems, Malthus was undoubtedly correct over the short term, but over the long-term, evolutionary innovations have proven sufficient to steadily expand the planet’s carrying capacity. Innovation is consequently of substantial theoretical and practical concern. Research at SFI on innovation focuses on evolutionary processes in biological, technological, and market systems. For a comprehensive list of SFI researchers working on innovation, click here.

• Innovation in Biological Systems

• Innovation in Technological Systems

• Innovation in Markets

Robustness in Biological and Social Systems

Innovation in Biological Systems

Two critical objectives of SFI research are (a) accounting for the diversity and complexity of forms, and (b) developing a theory of form transitions. ‘Form’ is broadly defined to include alternative virus life cycles, animal body plans, social organizations, and syntactical structures in genomic and signaling systems. Of interest is how the invention of new information processing mechanisms and new control, robustness and variation production mechanisms interact with the environment in the generation of organizational complexity and diversity, and how robustness requirements, the availability of neutral space, niche construction, and conflict drive or impede these inventions.  This research, led by SFI Professors Doug Erwin and David Krakauer, and SFI Research Fellow Jessica Flack, draws data and insight from a number of fields, including macroevolution, evolution of development, phenotypic integration, behavioral, social and cultural evolution, population genetics, game theory, computer science, and information theory. Erwin and Krakauer work on the role of ecological niche construction in evolutionary innovation and the evolution of developmental programs and toolkits. Erwin also studies the role of innovation in mass extinctions and recovery processes and has written a major book, Extinction, on the topic. Krakauer and Flack work on social niche construction and inheritance, the analog to evolution of development at the societal level, the role of conflict as a driver of organizational complexity, and the role of conflict management and feedback in organizational robustness and evolvability and network structure and dynamics. Flack also works on innovation in signaling systems. Closely related work includes SFI Professor Jon Wilkins’ research on genomic imprinting – a form of intragenomic conflict that has been implicated in the evolution of baroque molecular mechanisms at the genetic level, SFI External Professor Walter Fontana’s research on RNA, showing that neutral networks can simultaneous promote evolvability and robustness, SFI External Professor Jim Crutchfield’s work analyzing evolutionary dynamics on neutral networks, and SFI External Professor Marcus Feldman’s research on ecological and cultural niche construction. Finally, research on innovation is closely tied to research on robustness. SFI External Professor Erica Jen heads up SFI’s Robustness Program funded by the James S. McDonnell Foundation. For more on robustness, please visit the SFI "Robustness in Biological and Social Systems Robustness Pages".

Return to top

Innovation in Technological Systems

Technological learning, represented by learning curves or experience curves, is a topic that spans economics, physical sciences and complex systems. Historical data shows that the performance of technologies tends to improve as a function of both time and cumulative production or installation, typically following trajectories that are reasonably well approximated as power laws. However, some technologies, e.g. those associated with computer information processing, follow exponential improvement curves (Moore's law). Here ‘technology performance’ is being used broadly to refer to phenomena ranging from the cost of solar electricity, to information processing speed, to the output of an assembly line process, to lathe operation productivity.

SFI Professor Doyne Farmer, External Professors Seth Lloyd and Brian Arthur, and SFI Postdoctoral Fellow, Jessika Trancik have started a new research program on technological learning and innovation. Collaborative work by Farmer, Lloyd, Arthur and Trancik will tackle several critical questions. How reliable are extrapolations of empirical learning curves?  What does the improvement rate depend on? Why are some learning curves power laws and others exponentials?  Are these the only possibilities?  How do factors such as physical characteristics, relationship to other technologies, geography, and government funding, affect learning rates?  For a given technological sector, how does one properly construct a portfolio of research and development in order to maximize the overall improvement rate and reliability of the sector?

Return to top

Innovation in Markets

Co-Evolution of State and Market in Renaissance Florence
Part of SFI’s mission is the study of organismal and/or organizational invention and evolution, over long periods of time. SFI External Professor John Padgett pursues this topic in the historically rich context of Renaissance Florence, site of many dramatic organizational inventions important to the social evolution of politics, economics, art and science in Western civilization. Under the sponsorship of both SFI and NSF, Padgett and his research team over 15 years have assembled from primary archival sources an unprecedented time-series data set on 200 years of political, economic, and social networks, spanning an entire city. This relational data set comprises over 100 original files of marriages, genealogies, loans, economic partnerships, account books, tax returns, political elections and office holdings, guild memberships, factional alliances, and personal letters among 60,000 individuals. So far the data have been used to discover the dynamic social-network processes involved in the birth of historically unprecedented forms of social organization in these domains: political party formation, corporate business organization and economic credit. These processes of organizational genesis or invention are the following: (a) extension and differentiation, (b) fusion and hybridity, (c) transposition and refunctionality, and (d) multivocality and robust action. Although these processes were discovered in the specific historical context of Renaissance Florence, these social-network processes of organizational invention operate in other times and places of social evolution as well.

Return to top

Robustness in Biological and Social Systems

Perhaps one of the most remarkable features of the world around us is that it is full of objects -corporations, nations, animal societies, computer software, organisms, genomes, airplanes and car engines, economies, the world wide web, cells, and ecosystems-- that persist despite continuous perturbations caused by, for example, viruses, noise, internal conflict, a changing environment, mutation, or drought. A goal of the Robustness Program at SFI is gain insight into the processes and mechanisms enabling biological and social organizations to remain 'phenotypically' and/or functionally stable in the face of predictable and unpredictable challenges like those listed above. Another important concern is how robustness requirements tradeoff against other potentially desirable organizational features like diversity and the capacity for innovation.

Like many research areas at SFI, the Robustness Program is highly interdisciplinary. This is due largely to the fact that perturbations are problematic in natural, cultural, and engineered systems. This generality presents researchers working on apparently disparate systems with a common set of issues. Although on the one hand this means that the study of robustness covers a vast and complicated space of research projects, it also suggests that problems related to robustness and persistence might be among the few resulting in general principles influencing the evolution of structure across the wide variety of systems observed in the world. The possibility of such general principles is particularly exciting for biology where contingency and initial conditions are thought to play such a big role in evolution.

Examples of specific robustness-related research projects at SFI include Steve Lansing's work how Balinese rice farmers have, over centuries, successfully negotiated water usage rights through elaborate cultural institutions called Water Temples; Colleen Webb's work on how spatial modularity in the distribution of organisms might influence the ability of an ecosystem to recover following disturbances like forest fires; research by Nihat Ay and David Krakauer using information theory to quanitfy network robustness in terms of node contribution to information flow and consequence to information flow of node removal; Jessica Flack's and David Krakauer's work on the generality of conflict management as a robustness mechanism and the role of robustness mechanisms in social niche construction; Simon Levin's work on the relation between biodiversity and ecosystem resilience; Stephanie Forrest's efforts to improve computer security using modified versions of solutions that have evolved to fight pathogens in natural immune systems; Andreas Wagner's work on the relative contributions of distributed robustness verses redundancy to mutational robustness, and Michelle Girvan's work on the relation between multiple, overlapping networks and robustness. This is only a small sampling of SFI robustnes-related projects. For a comprehensive list of researchers working on this topic, please click here.

The SFI Robustness Program, headed by Erica Jen, is funded by the James A. McDonnell Foundation and has been funded previously by the David and Lucile Packard Foundation.

Please direct comments on the content of this page to Jessica Flack ().