Leader: Michael Puma, Center for Climate Systems Research
About the Readings
Globally Networked Risks and How to Respond
Helbing, 2013, Nature
Today’s strongly connected, global networks have produced highly interdependent systems that we do not understand and cannot control well. These systems are vulnerable to failure at all scales, posing serious threats to society, even when external shocks are absent. As the complexity and interaction strengths in our networked world increase, man-made systems can become unstable, creating uncontrollable situations even when decision-makers are well-skilled, have all data and technology at their disposal, and do their best. To make these systems manageable, Helbing finds that a fundamental redesign is needed. A ‘Global Systems Science’ might create the required knowledge and paradigm shift in thinking.
The Precautionary Principle (with Application to the Genetic Modification of Organisms)
Taleb et al., 2014, NYU Extreme Risk Initiative
The precautionary principle states that if an action or policy has a suspected risk of causing severe harm to the public domain (affecting general health or the environment globally), the action should not be taken in the absence of scientific near-certainty about its safety. Under these conditions, the burden of proof about absence of harm falls on those proposing an action, not those opposing it. The precautionary principle is intended to deal with uncertainty and risk in cases where the absence of evidence and the incompleteness of scientific knowledge carries profound implications and in the presence of risks of “black swans,” unforeseen and unforeseeable events of extreme consequence. Tabel et al. look at the precautionary principle with regards to genetically modified organisms (GMOs) and nuclear energy. Their analysis makes clear that the precautionary principle is essential for a limited set of contexts and can be used to justify only a limited set of actions
Discussion Summary
What do we do about addressing systemic instability? One option is to intervene early. Another is to redesign our systems and prevent them from becoming overly interconnected. Such innovations, however, can lead to unintended consequences. For example, the rapid emergence of AI in a variety of sectors (agriculture, business, war) introduces a level of uncertainty that we can’t deal with.
With climate change, it is hard to identify, in the worst case scenarios, how there will be ‘winners.’ We need to understand the type of risk that we face and then differentiate between local and global risks. We also need to find a way to translate the scientific findings to facilitate the connections to policy.
If you have interconnected networks, shocks that lead to failure in one network now cascade to other networks. The investment required to stabilize these networks is also rarely, if at all, discussed. Resilience often comes from human networks. If we do not unpack institutions and how people act, we are going to have an abstract conversation that doesn’t tie to an agenda. Global public health networks are a good example of trying to counteract some of the dangers of a globalized world. Even with disasters, weak governments, etc., there is a global response (i.e. vaccine). Food security is another example. There is no U.S. institution that feels it is within their mandate to be responsible for global food security. This raises questions like what is the U.S. strategy if there is a global spike in food prices? How can we work with the government to build the capacity to respond?
Universities can help with data problems, figure out where to get better information, and conduct scenario-planning. It is impossible to have a grand model of everything, but we can create larger frameworks. The modeling of impacts is particularly complicated. We need to categorize systems and threats, local versus global threats, threats that have risk of ruin, etc. One approach could be to categorize approaches for a class of challenges. Another would be to examine historic events and consider how scenarios would be different if XYZ were in place.