Tuesday, November 13, 2007

Scientists as Policy Advisers

One of the greatest problems of having scientists serving as policy advisers is that scientists are trained in an area that is NOT policy advising, and unless they are lucky, their advice should not be taken, except with a major grain of salt. Part of this reaction stems from (I believe) mainly two points. First was the age of planning that peaked in the 20th Century, to which many people are still reacting to, and basing their viewpoints on. The second is the understanding that stakeholder engagement is becoming more feasible, even with possibly complex scientific issues.

The first issue (the spectre of the age of planning) is important because it is the major legacy with which we (as members of society in the US) focus our lens on the science adviser. From a 1955 publication entitled Natural Resources and the Political Struggle (Wengert, 1955), the roles of science and planning are outlined thusly:

In the field of resource policy, there has been a pronounced effort to rationalize programs and proposals in scientific terms and to city the authority of science as justification for particular policies. In no other field is the role of the expert more significant for particular policies. In no other field is the role of the expert more significant, and concomitantly the tendency to abdicate private, lay judgment in favor of the specialist more evident.


The history of resource policy is the history of science and technology in the service of the nation. The political struggle marking that history has involved scientists and intellectuals whose object largely has been to convert the public and the politician to a recognition of the importance and significance of the results of science. The struggle represents the deliberate attempt of intelligence to subdue and control the environment.


Another significant characteristic of the political process in its dealing with resource policy is the extent to which planning has been an important factor in reaching decisions. ... To the question of how the planning job can best be carried out there is and can be no single or simple answer.

Perhaps because resource policy has been intimately related to science and the use of research data and because scientifically trained men have been leaders in the resource policy field, planning techniques have been emphasized as means for identifying resource problems and preparing solutions for them. ... The issue today in the field of resource policy is not whether there shall be planning, but rather who shall plan and to what ends.
I hope this illustrates that planning was considered important in conducting policy advice (usually by people who knew the physical system - the scientist). Taking a quote from John Wilkinson (1964) - apparently mis-attributed to Charles de Gaul - "generals are always fighting the last war, and educators ... are always instructing the last generation." Here I mean that many of those in the policy arena are learning from those who grew up in the paradigm of planning; it colors their viewpoints and attitudes toward the "correct" role of science. (A possibly interesting discussion would be the role of planning in policy and how it differs from science.)

The second point - greater possibility for useful stakeholder engagement - is being proven with increased ability to disseminate technical information (especially those affecting natural resource use/extraction) spatially through the use of GIS and terrain viewing programs, both of which can be altered to show potential policy futures. In areas where visualization in terms of maps and computer wire models are less useful, the various models (both procedural and statistical) underlying most forms of scientific forecasting can be tweaked to produce output that are more amenable to the consumption of different stakeholders. With the understanding that stakeholder engagement is a requisite quality for robust "good" policy, use of science in illustrating the most likely (i.e., conservative estimate) impact of the major factors of interest to each stakeholder can be input to a model. In more sophisticated models, such factors can even be taken synergistically to illustrate the impact of more fine-tuned policy decisions.

Because of the continually growing strength of scientific understandings of how discrete (i.e., disciplinary) systems operate more accurate predictions are able to be made within a single system. This lends itself to being able to plan the impacts of a policy decision within the boundary conditions of that system. However, like a piece of science fiction depicting a possible not-too-distant-future, the change of only one (or a few) variables on an otherwise unchanged world-of-today makes for relatively easy writing, but does not provide a plausible future. Who would have guessed the massive synergistic impact of the internet on the totality of life in the West, including e-mail communication; increasing connection speeds; search engines; increased web page complexity; flash programming; YouTube; online databases; Google Earth; etc. The lesson here is to understand the impacts of synergy on a network of systems.

However, within certain constrained situations, science can still pull together forecasts with variables working in synergy. The requirement, though, with anything in modeling, is how much is constrained and how it is constrained. What this means, though, is that science can still inform planning, but it can now do so through stakeholders or committees including non-scientists as participating members. The role of the expert scientist becomes constrained more to the efficacy, reliability, and accuracy of the model, and not on their "Best Professional Judgment" of a situation, based on their own ingrained bias.

Science still is working in the form of "planning," but it becomes possibly multi-system in analysis, and usable by stakeholders in investigating possible futures based on policy inputs (with the understanding that the constraints and uncertainties are understood by all). By the simple (ha!) process of making the output of a policy scenario legible and accessible to non-experts (and allowing for possibly easy iterations of inputs from stakeholder representatives and outputs from expert scientists), decision makers are empowered by the science, rather than by the scientist. (True, scientists still have opportunities in manipulating the science behind the model - the meta-science - but in a complex system model operated by several different experts, the possibility of having major favorable outcomes without raising suspicion becomes exponentially more difficult, and I'm therefore discounting this possibility, at least for the near future.)

Yes, we have been here before - trusting models to solve our problems, forgetting that models have intrinsic uncertainty and various levels of external validity problems. However, we have also come a long way, being able to work strongly within disciplines to answer those difficult-to-solve problems of yesterday (at least to some extent). We are entering an age (I feel) where thinking of how to integrate knowledge across somewhat arbitrary disciplines (and subdisciplines) is becoming feasible and a new area of scientific interest; just how do you integrate economic factors with social factors, physical environmental factors, ecological factors, etc.

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