In The Economists’ World in 2013 edition, I came across a very interesting statement about forecast uncertainty, and just who are the ones doing all the squirming about it.
…recent reforms to the IPCC’s procedures will do little to change its tendency to focus on the areas where there is greater consensus, avoiding the uncertainties which, though unpalatable for scientists, are important to policy. (link)
What struck me about this claim is that it runs completely counter to what I’ve been told during my training as a scientist. It is the scientist, it goes, that possesses a deep understanding of uncertainty. The policy maker, on the other hand, is an oaf who wishes to hear only of black and white pronouncements about the effect of x on y. Could it be that this perception is inverted in each camp?
Certainly the scientist and policy maker each wish to decrease uncertainty. However, it ought to be that neither finds it ‘unpalatable’ in and of itself, but rather an inextricable part of our predictions about complex systems (or even the simplest ones, for that matter). Acknowledgement, understanding, and quantification of uncertainty are absolutely crucial to conducting good science as well as informing science directed policy.
Indeed, I agree. Moreover: L.A.Smith, N.Stern, “Uncertainty in science and its role in climate policy”, Phil. Trans. R. Soc. A (2011) 369, 1–24
doi:10.1098/rsta.2011.0149, argues (from its Abstract): “There is value in scientists engaging in a deep conversation with policy-makers and others, not merely ‘delivering’ results or analyses and then playing no further role. Communicating the policy relevance of different varieties of uncertainty, including imprecision, ambiguity, intractability and indeterminism, is an important part of this conversation. Uncertainty is handled better when scientists engage with policy-makers. Climate policy aims both to alter future risks (particularly via mitigation) and to take account of and respond to relevant remaining risks (via adaptation) in the complex causal chain that begins and ends with individuals.
Policy-making profits from learning how to shift the distribution of risks towards less dangerous impacts, even if the probability of events remains uncertain. Immediate value lies not only in communicating how risks may change with time and how those risks may be changed by action, but also in projecting how our understanding of those risks may
improve with time (via science) and how our ability to influence them may advance (via technology and policy design).”
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