EAGER: A Quantitative Theory for Technology Evolution and Innovation

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Technology innovation is critical to the social welfare, health, economy, and security of the USA and the world. A fundamental understating of innovation is elusive. It can be observed, but it is hard to predict, and even harder to execute. The difficulty in understanding and executing innovation rests in part on the complexity of the technology ecosystem. For example, the invention and development of Corning's Gorilla Glass supports the smartphone which in turn synergizes with social media to drive new types of software development. At the same time, observation of a single technology through time shows an evolutionary improvement in performance. Compared to the first generation, current smartphones store more photographs and operate longer without the need for charging. This EArly-Concept Grant for Exploratory Research (EAGER) award supports fundamental research to create a mathematical theory that describes technology performance evolution and, simultaneously, ecological synergies between technologies. The created theoretical model will have sufficient fidelity and causal indicators such that one can predict and effect innovation. This new theory will inform individual and enterprise-scale technology innovation. Also, by knowing the impact and by predicting the evolution of new technologies, policy makers can make sound investment and funding decisions for key research initiatives. The enhanced understanding will also help public policy officials develop appropriate regulations and incentive structures for future technology development. The technology ecosystem model of technologies and their interaction is modeled using generalized Lotka-Volterra (L-V) population models. The intellectual impact of this work includes the extensions made to the general format of L-V equations to connect them to microscale technology performance improvement (the improved performance of a single technology). The microscale technology evolution model will follow S-curve trends, but in fact be created with L-V equations. This general model of technology evolution will be extended using theories from The Theory of Inventive Problem Solving (TIPS). The hypothesis is that this multiscale, hierarchical, L-V model will be able to capture the ecosystem type interaction of engineered products and technologies as well as performance evolution.