Using Material Models to Investigate Agency, Innovation, and Directionality in Evolution
Using Material Models to Investigate Agency, Innovation, and Directionality in Evolution is a two-year initiative involving an international collaboration among the University of Calgary, University of California – Irving, University of Minnesota, and UNAM. I am the principal investigator with Maria Rebelled-Gomez (UCI), Michael Travisano (Minnesota), and Valaria Souza (UNAM) as teams leaders and Nahui Medina-Chavez as postdoctoral research (Minnesota). The project is generously funded by the John Templeton Foundation ($600,000 USD).
This project develops a pragmatic approach for learning about agency by investigating the dynamics underlying the evolution of agency (rather than constructing theoretical definitions of agency). We use a minimal concept of agency to design experiments employing three material models. The biological entities in these models effectively identify and choose evolutionary pathways encompassing novel directions of change. We hypothesize that eco-evolutionary feedback is central to evolutionary innovation: preexisting ecology shapes evolutionary outcomes, which subsequently shape ecology, and these feedbacks open new pathways that can be selected. To investigate how agency can originate in simple non-cellular systems, we trace its emergence in a new model for experimental evolution, which consists of single-stranded DNA. We follow the coevolution of microbial species in a laboratory community to investigate how agency evolves in preexisting complex systems. To investigate how the evolution of agency can be constrained, we track evolution in a field model in which there has been significant evolutionary change without the dramatic innovations that have occurred elsewhere. These models enable us to investigate evolution as it is occurring. Together, they provide a broad scope for exploring and depicting the dynamics underlying the evolution of agency. This project demonstrates how material models can be used to play roles attributed to the use of mathematical, computational, and verbal models. To explore how material models can be used to play these roles, philosophers and scientists regularly meet as the empirical research is conducted. This conceptual work will, in turn, influence and inform the design of experiments.
[project website forthcoming]
This project develops a pragmatic approach for learning about agency by investigating the dynamics underlying the evolution of agency (rather than constructing theoretical definitions of agency). We use a minimal concept of agency to design experiments employing three material models. The biological entities in these models effectively identify and choose evolutionary pathways encompassing novel directions of change. We hypothesize that eco-evolutionary feedback is central to evolutionary innovation: preexisting ecology shapes evolutionary outcomes, which subsequently shape ecology, and these feedbacks open new pathways that can be selected. To investigate how agency can originate in simple non-cellular systems, we trace its emergence in a new model for experimental evolution, which consists of single-stranded DNA. We follow the coevolution of microbial species in a laboratory community to investigate how agency evolves in preexisting complex systems. To investigate how the evolution of agency can be constrained, we track evolution in a field model in which there has been significant evolutionary change without the dramatic innovations that have occurred elsewhere. These models enable us to investigate evolution as it is occurring. Together, they provide a broad scope for exploring and depicting the dynamics underlying the evolution of agency. This project demonstrates how material models can be used to play roles attributed to the use of mathematical, computational, and verbal models. To explore how material models can be used to play these roles, philosophers and scientists regularly meet as the empirical research is conducted. This conceptual work will, in turn, influence and inform the design of experiments.
[project website forthcoming]