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Two scientific premises guide the Institute’s approach.

1. The global system is complex

Today’s planetary socio-ecological system is “complex” in the technical sense of the term. The Institute therefore uses, as its core analytical tools, theories, concepts, and methods drawn from complexity science. This interdisciplinary field has emerged from research in mathematics, computer science, systems engineering, ecology, and economics, and its insights have been applied to explain diverse phenomena, including the origins of the 2008-09 financial crisis, the Arab spring, the sharp rise in the appeal of populist political ideology, and the ramifying consequences of the COVID-19 pandemic.

All complex systems—whether natural ecologies, mammalian immune systems, or human economies—have dense and recursive causal connections across multiple scales of organization. These connections create high levels of combinatorial interaction—where many causes operate simultaneously, often synergistically— as well as large numbers of destabilizing (“positive”) and stabilizing (“negative”) feedback loops. The result is disproportionate causation: sometimes a small change in one component of a complex system causes an enormous shift in the system’s overall behavior; but other times, even large changes in multiple components produce little effect. Complexity scientists call this phenomenon “nonlinear behavior.”

Nonlinearity is a key reason why complex systems like Earth’s climate, forests, and fisheries, and our global financial and political systems sometimes shift or “flip” unexpectedly from one macro-state to another. Scientists generally cannot predict with any precision when such “critical transitions” might happen; they might know that the likelihood of a flip is rising but have little idea when the event will occur. Also, these flips are usually extremely difficult to reverse. When a pandemic strikes, fishery collapses, Earth’s climate reorganizes itself, or a population’s predominant worldview shifts, the system in question likely cannot be returned to its former state, even if the conditions that caused the flip are wound back entirely.

Taken together, these features of our planetary socio-ecological system present humanity with extreme dangers—and extreme opportunities. The dangers arise from the real possibility that this system is close to an irreversible shift to a new pathway that would radically degrade human well-being and civilization’s long-term prospects. The opportunities arise from the enormous leverage available in highly nonlinear systems, if the right intervention points can be found and exploited. In today’s complex, hyper-connected global systems, a series of precisely targeted and timed interventions could produce a virtuous cascade of change that helps flip humanity onto a far more positive path.

Unfortunately, complex social systems are usually so opaque that key intervention points are invisible; and even in the rare circumstances where they’re visible, means of exploiting them are not obvious. The Cascade Institute confronts both challenges.

2. Societies are organized around cohesive sets of worldviews, institutions, and technologies

We call these sets “WITs.”

In simplest terms, worldviews are mental networks of concepts, beliefs, and values—usually emotionally charged—that allow people to interpret things around them and plan their actions. Worldviews also give people’s lives meaning and therefore some sense of security, so they are resistant to change. Institutions are, broadly, a community’s rules, ranging from formal laws to unwritten social norms about what behavior is appropriate or ethical at specific times and places. Finally, technologies are problem-solving tools that people create by using energy and information to exploit properties of their physical and social environments. These three components are tightly interdependent within each WIT: they influence each other, depend on each other, and so hang together in a cohesive way.

By creating detailed graphical, statistical, and computational models of dominant WITs, the Cascade Institute’s researchers identify opportunities for stimulating rapid nonlinear change within societies, among clusters of societies, and at the global level. The Institute’s researchers are currently examining, for instance, how specific changes in people’s worldviews could produce a “norm cascade” that dramatically boosts political mobilization for more aggressive action to address the climate crisis—mobilization many times larger than that seen among youth around the world in 2019. Such an event could heighten financial markets’ estimation of the risks associated with fossil-fuel energy, in turn helping to shift massive resources towards faster development and deployment of carbon-free energy systems.

Reference:

Beddoe, Rachael, et al. "Overcoming systemic roadblocks to sustainability: The evolutionary redesign of worldviews, institutions, and technologies." Proceedings of the National Academy of Sciences 106.8 (2009): 2483-2489.

Methods for System Mapping

The Cascade Institute’s researchers have pioneered the development of several methods for mapping the causal structure and mechanisms of complex social systems. The Institute’s researchers combine these methods to understand opportunities for intervention in dominant WIT (worldview, institution, and technology) systems.

Two methods—Boolean causal loop analysis and cross-impact balance analysis—help reveal a system’s underlying causal processes, including its synergistic interactions and feedback loops (both positive and negative) that can lead to sudden transitions (“tipping points”) between equilibria. Two other methods—cognitive-affective mapping and ideological state space modeling—help reveal the structure of people’s worldviews and the psychological and social mechanisms of rapid belief transformation.

Methods for Causal Mapping

Causal Mapping Methods Explained

Boolean causal loop analysis (BCLA)

This method, developed by Cascade Institute director Thomas Homer-Dixon, integrates standard causal diagraming with Boolean logic to represent causal interaction and feedbacks in complex social systems. Its theoretical predecessors include the causal loop diagrams of System Dynamics and cybernetics (now widely used in control systems engineering) and the INUS set-theoretic causal analysis of the philosopher JL Mackie. (In formulating the INUS approach, Mackie noted that a cause can be "an insufficient but necessary part of a condition which is itself unnecessary but sufficient for the result.") System variables are identified and then connected with unidirectional causal arrows that indicate positive or inverse correlations. Temporally simultaneous causes can be grouped in sets of necessary causes (using the “and” Boolean operator) or sufficient causes (using the “or” Boolean operator). A given cause can have multiple possible causal effects (exhibiting “multifinality”), while a given outcome can be a result of multiple, discrete causal pathways (exhibiting “equifinality”).

References:

Ludvig von Bertalanffy, “The history and status of general systems theory,” The Academy of Management Journal 15, No. 4 (1972): 407–426.

Vladimír Bureš, “A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-oriented Reduction,” Systems 5, No. 46 (2017), doi: 10.3390/systems5030046.

Jaegwon Kim, “Causes and Events: Mackie on Causation,” The Journal of Philosophy 68, No. 14 (22 July 1971): 426-441.

Cross-impact balance (CIB) analysis

This method, formulated originally by Wolfgang Weimer-Jehl of the University of Stuggart in Germany and further developed by Vanessa Schweizer of the University of Waterloo, allows researchers to formalize a qualitative description of a complex social system, which in turn allows the researchers to model the system’s evolution over time and responses to interventions. It takes as inputs a representation of the causal relationships operating within a given system (perhaps in the form of a BCLA, see above) or the beliefs of experts about that system’s causal mechanisms. It then disaggregates these hypothesized mechanisms into pair-wise (bivariate) relationships, showing whether and how each system component is believed to directly affect other individual components. The pair-wise relationships are then encoded in a cross-impact table that reveals indirect system influences, including interaction effects and positive and negative feedbacks. The method can be used to produce influence diagrams, causal-chain analyses, and plausibility rankings of scenarios. It can identify: 1. a system’s stable configurations (i.e., system attractors) and the degree of their stability, 2. the system’s overall stability landscape, and 3. the location of any given system state on that landscape. As an algorithmic method, it records mental models transparently, so it can be used to settle disputes over what scenarios for the system should be deemed plausible and why.

Reference:

Vanessa Schweizer and Elmar Kriegler, "Improving environmental change research with systematic techniques for qualitative scenarios," Environmental Research Letters 7 (2012): 044011, doi:10.1088/1748-9326/7/4/044011.

Wolfang Weimer-Jehle, “Cross-impact balances: A System-Theoretical Approach to Cross-Impact Analysis.” Technological Forecasting & Social Change 73 (2006): 334-361, doi: 10.1016/j.techfore.2005.06.005.

Methods for Socio-Cognitive Mapping

Socio-Cognitive Mapping Method Explained

Cognitive-affective mapping (CAM)

This method, formulated originally by Paul Thagard of the University of Waterloo and further developed by Cascade Institute researchers, generates diagrams—called "cognitive-affective maps” (or CAMs)—of the concept network that a person or group uses to represent a specific subject, such as another individual or group or an issue in dispute. In the network, each concept is assigned a positive or negative emotional valence, and the types of links between concepts indicate whether the valences are directly or inversely correlated. The result is a detailed image of a system of emotionally charged concepts that can assist in-depth analysis of worldview change over time, possibilities for future change, and the avenues for dispute resolution.

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Reference:

Thomas Homer-Dixon, Manjana Milkoreit, Steven J. Mock., Tobias Schröder, and Paul Thagard. “The Conceptual Structure of Social Disputes: Cognitive-affective Maps as a Tool for Conflict Analysis and Resolution.” Sage Open (January-March, 2014): 1-20, doi: 10.1177/2158244014526210.

Ideological State-space (ISS) modeling

This method, developed by Cascade Institute director Thomas Homer-Dixon, allows researchers to identify and analyze key differences between worldviews. It exploits the idea of a state space, which is a picture, much like a three-dimensional map, of all possible states of a system. In this case, the position of a given political-economic worldview is plotted on fifteen distinct dimensions. Each dimension is a continuum of possible answers to a single question that most worldviews commonly address, such as “Are differences between human groups large and essential or small and unimportant?” and “Are moral principles relative (subjective) or absolute (objective)?” Taken as whole, this high-dimensional space allows researchers to judge the cognitive distance between worldviews, map possible migration pathways between them, and identify previously unrecognized worldviews.

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Reference:

Thomas Homer-Dixon, “Mindscape,” Chapter 18 of Commanding Hope: The Power We Have to Renew a World in Peril (Toronto: Knopf Canada, 2020), pp. 298-320.