Complexity and Scientific Advice

Why do we need a complexity revolution when dealing with the production and use of scientific information for and by a process of decision making? This Uncomfortable Knowledge Hub (UKH) series consists of one teaser video and two video lectures illustrating the need for that revolution. The first video addresses the epistemological predicament of the use of scientific information (especially quantitative scientific information) to inform policy, from a conceptual angle. The second video presents the lessons learned in a four-year project—the EU MAGIC project—in relation to the actual problems experienced in the EU with the use of scientific information to inform sustainability policies.

What is uncomfortable knowledge?

Uncomfortable knowledge is a concept introduced by Steve Rayner*. As Rayner puts it: “to make sense of the complexity of the world so that they can act, individuals and institutions need to develop simplified, self-consistent versions of that world”. The chosen, self-consistent narratives and explanations necessarily leave out some relevant aspects of the issue in order to remain simple and useful. In this situation “knowledge which is in tension or outright contradiction with those versions must be expunged. This is uncomfortable knowledge which is excluded from policy debates, especially when dealing with ‘wicked problems’”.

*Steve Rayner, 2012. Uncomfortable knowledge: the social construction of ignorance in science and environmental policy discourses. Economy and Society 41(1): 107-125.

What is quantitative storytelling?

Quantitative storytelling (QST), the systematic approach used to present material on the Uncomfortable Knowledge Hub, does not claim to present the “truth” about a given issue, nor that all the numbers used in the story are uncontested. When dealing with wicked issues, all numbers can always be calculated in a different way and narratives are always contested. QST simply presents alternative stories useful to check the quality of existing narratives and to enrich the diversity of insights about a given issue.

Videos

Complexity in sustainability​ (1 min 55 sec)

What are the implications of complexity in quantifying sustainability challenges, and what do they mean in terms of scientific advice to policy? When we deal with problems that require a complex perception and representation—i.e. the simultaneous adoption of non-equivalent descriptive domains across dimensions and scales—the adoption of reductionism translates into the adoption of simplistic models.

Complexity and the problem with scientific evidence​ (19 min 53 sec)

This video illustrates with practical examples the implications of four epistemological challenges faced when trying to check the quality of scientific advice: (i) social incommensurability—the coexistence of difference priorities over concerns found in society; (ii) technical incommensurability—the coexistence of non-equivalent descriptive domains useful to represent a given situation; (iii) the need of situating the policy deliberation—the definition of the best thing to do changes depending on the context; and (iv) the unavoidable generation of hypocognition—hypocognition (the missing of relevant aspects of the issue) is determined by the definition of an epistemic box (the formalization of the problem structuring).

Post-normal science: Lessons from the MAGIC project (27 min 40 sec)

This video is based on the lessons learned in the activities of the MAGIC project, which in turn are based on an understanding of the insights of Post-Normal Science grounded on complexity. Three sets of results are illustrated: (i) the first sustainability predicament to be overcome is not determined by biophysical constraints, but by the refusal to acknowledge the implications of uncomfortable knowledge, existing in society; (ii) it is possible to avoid the hypocognition determined by the adoption of simplistic narratives by using analytical frameworks based on complexity. However, the creation of new and better analytical tools by themselves is insufficient; we also need (iii) to use the Post-Normal Science perspective to improve the quality of governance. This entails acknowledging that: (i) when dealing with sustainability analysis, it is impossible to decouple passion from reason; (ii) quality control, in sustainability science, requires an extended peer community; and (iii) sustainability is about learning how to update the identity of the society while remaining operational—i.e. how to deal with the “tragedy of change”.

Resources

Teams Involved