Planning for Resiliency and Robustness
Building on the last post, insights on resilience from cities: Marina Alberti argues for planning toward robustness rather than optimality, since there is no one ideal, stable state.
In a recent post, "Coping With Complexity," we examined dealing positively with complexity, and I generalized that given the strength of the chaotic unknown and the tendency towards entropy, we must try multiple strategies, while looking for long-term trends, and demonstrate a willingness to stick to those strategies even when, in the short-term, some might fail.
Building on that idea, here are some insights on cultivating resilience in cities. Acknowledging that complexity necessitates that there is no one ideal, stable state, Marina Alberti suggests policies for robustness, rather than optimality in her article on "The Nature of Cities": Planning Under Uncertainty: Regime Shifts, Resilience, and Innovation in Urban Ecosystems
The idea of optimality—that one can find the optimum among a set of possible alternatives given a set of conditions—is a direct consequence of the steady-state paradigm. Planners come to assume that an optimal solution exists. Decisions based on seeking the optimum assume that we can quantify risks. However, in the presence of irreducible uncertainties, we encounter multiple plausible futures whose relative probabilities are unknown. The farther we look into the future, the more the uncertainty increases—and it may increase even more with new understanding from advancement in scientific research. For systems to function in an uncertain environment, robustness rather than optimality is a more appropriate target for planning and decision-making.
Evidence emerging from the study of complex systems can provide insights for planning and management. In a recent paper in Science, Sheffer et al. (2012) suggest that system shifts may result either from unpredictable external shocks or from critical transitions. Drawing on two separate lines of investigation—on complex networks and on the proximity of critical thresholds—they suggest that both the heterogeneity of the components and their connectivity affect the stability of systems on the long run. By building on such observations in ecological systems, we can develop hypotheses about the fragility and robustness of coupled human-natural systems and test them in urban ecological systems.
There's a lot to ponder even in these two paragraphs, but I'd like to highlight some points that connect to concepts we've explored here on Schools as Ecosystems.
- There is no one-size-fits-all solution. "Give up romantic notions of a stable Eden," as Emma Marris puts it 2) We cannot quantify everything, given the scale of the unknown 3) We can't make accurate predictions. Therefore, we must plan for resiliency. 4) Diversity, interconnectivity, and redundancy will better build resiliency and robustness.
Alberti then outlines some recommendations for planning and building for robustness in an urban ecosystem. I would suggest that all of these points are salient to education policy and planning:
- Create and maintain diverse development patterns that support diverse human and ecosystem functions
- Focus on maintaining self-organization and increasing adaptation capacity instead of aiming to control change and to reduce uncertainty.
- Expand the consideration of uncertainty and surprise by designing strategies that will be robust under the most divergent but plausible futures.
- Create options for learning through experiments, and opportunities to adapt thorough flexible policies and strategies that mimic the diversity of environmental and human communities.
- Expand the capacity for change through transformative learning by challenging assumptions and actively reconfiguring problem definition and policy action.