COMPUTATIONAL SOCIAL SCIENCE

DOCTORAL DISSERTATION PROPOSAL DEFENSE - THOMAS

October 23, 10:00 a.m.
92 Research Hall
Fairfax Campus

Shaping Possibility Space: Coevolution of Thinking and Doing In Organizational and Institutional Innovation

Russell Thomas, Ph.D. Student
Computational Social Science
Department of Computational and Data Sciences
George Mason University

ABSTRACT: This dissertation will explore how communities of innovators think and act in the face of radical uncertainty and in pursuit of genuine novelty. How does the way they think shape what becomes possible? How do new possibilities shape how they think? And how does this coevolution process shape the trajectory of innovation?

Two computational models will be developed and analyzed. First, an existing simple percolation model of innovation will be extended and revised to incorporate an emergent, graph-structured possibility space, differential knowledge, and collective learning. Second, a multi-level computational model of institutional innovation in cyber security will be developed that incorporates reflective agents who cope with radical uncertainty and genuine novelty. Two formalisms will be developed to support this work, including an ecology-based ontology for endogenous innovation and a formalization of Boisot’s Information Space. When complete, this research should shed light on mechanisms of organizational and institutional innovation, including what conditions might promote or inhibit innovation in complex socio-technical systems. This research will also make methodological contributions regarding computational models of multi-level systems and endogenous innovation.