Blue uncertainty: Warding off systemic risks in the Anthropocene—Lessons from COVID-19

Abstract

COVID-19 has made evident the complex interdependence of social and ecological systems and that to reduce the risk of future zoonotic pandemics we must safeguard nature. Approaches based on complexity science taking into account that interdependence and its associated systemic risks must be mainstreamed in current policy making, in general. However, at present, that could result in failure for three main reasons: (1) those approaches might be too sophisticated for current policy making pursuing sustainable development; (2) the reductionist views from conventional economics still deeply influence economic and environmental policy making; (3) it is unlikely that far-reaching policies aimed at stimulating post-pandemic economic development can be steered through radically innovative approaches that remain untested. Here, using COVID-19 as an example, I suggest that the use of innovative complexity-based approaches could be enabled through intermediary approaches equipped to resonate with the mindset pervading current policy making.

How to Handle Reasonable Scientific Disagreement: The Case of COVID-19

“…It is rather a symptom of deeper systemic problems, a complex phenomenon, which is characterized by indeterminateness, systemic complexity and, finally, absence of 'right' or definite solutions, as it is argued (ibid.). Or as Méndez (2020) put it, it is '…a symptom of more profound global problems', which nevertheless '…cannot be tackled now, since resources are scarce and directed towards the resolution of the symptom, as are political action, and media and public attention', the point being that the values involved in the implications of the actions that need to be taken (or not taken) to combat the spread of the disease exceed the very disease and its biomedical basis and impact (e.g., they involve apparent restrictions in basic human rights).…”

“…It can be modelled or described through probabilistic reasoning (cf. Méndez, 2020). The risk of error is reduced with further data collection and probability redistribution.…”

“…While, for example, one year ago we were still confronting radical uncertainty and high systemic risks (Méndez, 2020), in the period from the emergence of COVID-19 pandemic to date, research has already led to more (reliable) data and a much better understanding of the nature of the disease and the possibility of COVID-19 transmission risk and prevention. We now know more about the symptoms of coronavirus or the adverse effects occurring during (or even after) its healing treatment.…”