“Wicked problems” Part 2: In relation to policy as part of the systems thinking (applications)

Addressing environmental challenges is not always straightforward. The effectiveness of Canada’s plan to plant 2 billion trees, for example, is impacted by logistical challenges  and ecological dynamics such as insect pest outbreaks or increased fire risks.

Contributor: Brian Leung 

This blog is the second of a two-part series on “Wicked Problems”. Read Part One Here.

On the surface, solutions to many current problems appear straightforward: if we want to address climate change, reduce emissions; if we want to conserve species, protect more areas; if we want to improve air and water quality, stop pollution. Indeed, policies have been put in place for these purposes and should be lauded. The difficulty comes in actually achieving the goals in a meaningful way. This comes about arguably because of the high level of socio-ecological complexity of these problems (e.g. the cause of “wicked” problems). 

For ecological complexity, we often do not fully understand the dynamics of the system at play. The models that we use to make predictions are either missing important factors or incorrectly model them as we can only model the phenomenon that we have thought of, and for which we have some information. Some main difficulties include interactions and feedbacks within the system. An example of interactive effects: Canada has a plan to plant 2 billion trees to help reduce amounts of CO2 in the atmosphere. Beyond the logistical challenges of doing this, ecological dynamics such as insect pest outbreaks or increased fire risk reduce the effectiveness of the plan. Indeed, it may actually cause forests to be net emitters of CO2, which has additional, unintended social consequences.  What is known as “tipping points” can also occur, wherein after a certain degree of change, positive feedback loops (a closed system of amplifying disturbances) occur. For example, the progression of climate change could reduce snow cover in northern latitudes, which reduces reflectivity (white snow versus dark bare ground) resulting in an increase in heat absorption and thus, air temperature, which then further accelerates warming. This highlights the fact that predicting outcomes is not actually straightforward.

In societies, feedbacks can also occur due to human behaviour and motivation. Even if a company (or country) wants to be proactive, this could cause a competitive disadvantage compared to other companies/countries whose only focus is monetary gain and is then able to expand more and become more dominant. Put another way, actions do not occur in isolation, but rather, occur given a landscape of all other actors and their potential actions. Accounting for these dynamics and putting the appropriate incentive structures in place requires substantial insight and coordination (e.g., so that the socially responsible company “wins,” everyone would be willing to pay a little more and not buy from the other companies).   

Human values and motivations are not uniform and are not always geared towards societal improvements. People can be innovative and smart, and even when policies are in place, actors may not necessarily comply, or will find ways to navigate around the policies.  These dynamics of human behaviour and response are critical for policy success, and should be predictable to a certain extent, yet rarely enter the models which inform policy. How systems perpetuate and how to break detrimental feedback loops remain an open question. Finally, policies have costs and benefits, with often the most vulnerable sections of society disproportionately, and negatively affected. 

Categories: Beyond Sustainability Blog