Learning In and About Complex Systems

Change is accelerating, and the complexity of the systems in which we live is growing.Increasingly change is the result of humanity itself.As complexity grows so do the unanticipated side effects of human action, further increasing complexity in a vicious cycle.Many scholars call for the development of 'systems thinking' to improve our ability to manage wisely.But how do people learn in and about complex dynamic systems?Learning is a feedback process in which our decisions alter the real world, we receive information feedback about the world, and using the new information we revise the decisions we make and the mental models that motivate those decisions.Unfortunately, in the world of social action various impediments slow or prevent these learning feedbacks from functioning, allowing erroneous and harmful behaviors and beliefs to persist.The barriers to learning include the dynamic complexity of the systems themselves, inadequate and ambiguous outcome feedback, systematic 'misperceptions of feedback' where our cognitive maps omit important feedback processes, delays, stocks and flows, and nonlinearities that characterize complex systems, inability to simulate mentally the dynamics of our cognitive maps, poor interpersonal and organizational inquiry skills, and poor scientific reasoning skills.To be successful methods to enhance learning about complex systems must address all these impediments.Effective methods for learning in and about complex dynamic systems must include (1) tools to elicit participant knowledge, articulate and reframe perceptions, and create maps of the feedback structure of a problem from those perceptions; (2) simulation tools and management flight simulators to assess the dynamics of those maps and test new policies; and (3) methods to improve scientific reasoning skills, strengthen group process and overcome defensive routines for individuals and teams. D-4428metaphor they draw on fields as diverse as anthropology, biology, engineering, linguistics, psychology, physics and Taoism, and seek applications in fields still more diverse.All agree, however, that a systems view of the world is still rare.The challenge facing all is how to move from generalizations about accelerating learning and systems thinking to tools and processes that help us understand complexity, design better operating policies and guide organization-and society-wide learning.However, learning about complex systems when you also live in them is difficult.We are all passengers on an aircraft we must not only fly, but redesign in flight.In this paper I review what we know about how people learn in and about complex dynamic systems.Such learning is difficult and rare because a variety of structural impediments thwart the feedback processes required for learning to occur.I argue that successful approaches to learning about complex dynamic systems require (1) tools to articulate and frame issues, elicit knowledge and beliefs, and create maps of the feedback structure of an issue from that knowledge; (2) formal models and simulation methods to assess the dynamics of those maps, test new policies and practice new skills; and (3) methods to sharpen scientific reasoning skills, improve group processes and overcome defensive routines for individuals and teams, that is, in the words of Don Sch6n (1983a), to raise the quality of the "organizational inquiry that mediates the restructuring of organizational theory-in-use."Systems approaches that fail on any of these dimensions will not prove useful in enhancing the capabilities of individuals or organizations to understand, operate effectively in, nor improve the design of the systems we have created and in which we live, nor can they form the basis for the scientific study of complexity. 1 Learning is a Feedback ProcessAll learning depends on feedback.We make decisions that alter the real world; we receive information feedback about the real world, and using the new information we revise our understanding of the world and the decisions we make to bring the state of the system closer to our goals (figure 1).The feedback loop in figure 1 appears in many guises throughout the social sciences.George Richardson (1991), in his history of feedback concepts in the social sciences, shows how * Implementation failure * Game playing * Inconsistency * Performance is goal <e~~~~~~~~I