Agricultural Biotech as a Complex Adaptive System
(Primary Investigator: Steve Sonka)
Goals: The primary purpose of this project is to explore whether viewing technology
development and adoption as a complex adaptive system (CAS) can provide useful insights that
further our understanding of innovation and of the processes by which innovations, such as
agricultural biotechnology, are socially evaluated. This framework explicitly recognizes that
successful innovation is co-determined by the forces of technology and by those of society. The
direct result of the effort will be a report based upon literature review, synthesis of associated
methods and a research workshop/symposium focusing on "Agricultural Biotech as a Complex
Adaptive System". If this initial work produces promising results, additional efforts will be
pursued to implement the framework with decision makers in both the public and private sectors.
Procedures: This section will provide a brief overview of complex adaptive systems and
approaches employed to employ the CAS concept. Then the specific activities proposed for this
project will be detailed.
Pascale (1999) specifies that complex adaptive systems have four characteristics. They
are non-hierarchical, being comprised of many actors operating in parallel. Second, there are
multiple, shifting layers of organization and structure. Third, subject to the third law of
thermodynamics, CAS’s can wind down over time unless replenished with energy. Fourth,
CAS’s exhibit a capability for pattern recognition and learning.
Of particular interest for the study of technology development and adoption, complexity
science focuses on non-linear outcomes driven by rapid phase transitions and co evolutionary
forces (fueled by positive feedback loops) set in force by seemingly inconsequential instigating
events (McKelvey, 2004). Sometimes referred to as strange attractors, the interplay of these
inconsequential and seemingly unrelated events, when combined with positive