The history of science is replete with error and fraud. Environmental science is no exception. Indeed, this area of science provides a hyperabundance of examples, thanks to the presence of two factors: a good cause and extensive reliance upon modelling, especially that involving sophisticated computer models.
The good cause - one that most of us support - can all too readily corrupt the conduct of science, especially science informing public policy, because we prefer answers that support our political preferences, and find science that challenges them less comfortable.
The combination of the precautionary principle with endangered species legislation is a particularly seductive one, but it is the use of models into which value-laden assumptions can be smuggled that is particularly pernicious - as a recent Australian example shows.
A case involving the Orange-Bellied Parrot in 2006 saw the merest hint of a parrot, together with some mathematical modelling (and the precautionary principle) used by the then Australian Commonwealth Environment Minister to disallow the construction of a wind farm that was environmentalists’ preferred response to climate change, but was opposed by residents in a marginal Coalition government constituency.
Modeling for the Bald Hills wind farm on the Orange-bellied Parrot embodied very conservative assumptions to err on the side of caution. So, while no parrot had been sighted within 50km of the proposed site, the minister then acted in accordance with the precautionary principle (and an election promise) to block Bald Hills on the basis of cumulative impact - compounding the precaution already embedded in the assumptions underlying the modeling.
This “noble cause” corruption of science - named for the “framing” by police of suspects “known” to be guilty is helped not just by the virtuous cause, but by the virtual nature of both the science and the context within which it occurs. Both conservation biology and climate science rely on virtual science.
The revolution in information technology has transformed the conduct of science. Many of the scientists working with models appear to have forgotten that science is about testing predictions against data. Observational data in areas like climate science are subject to substantial massaging by computers before they are of any use. Even data collection, therefore, provides opportunities for subjective assumptions to intrude into the adjustments made to data to make them useful.
This highlights the importance of quality assurance processes, and there are no greater guarantors of quality assurance in science than contestation and transparency - full disclosure of data properly archived and of methods, including computer code.
Society deems this fundamentally important when we are dealing with science such as drug trials, which are conducted under fully transparent conditions, ideally with separate teams making up doses, administering them, diagnosing effects and analysing data. We insist on regulatory guidelines, and we audit laboratories. We know that even when researchers are fastidious in pursuing impartiality, subjective assumptions can find their way into what become “data”.
In areas such as climate science we have made no similar demands. Data are routinely gathered, manipulated and modelled by the same research teams and the discipline has not insisted on anything like full transparency. Many of the people engaging in this science are then acting as advocates for particular policy responses.
Those of us who see value in both social democracy and liberal democracy - who are committed to humanist ideals but are open to evidence-based reasoning rather than ideology in determining how we are to advance them - must acknowledge that it is from liberal views of the celebration of different points of view, and the battle of contending ideas, that good science derives.
The philosopher of science, Paul Feyerabend, warned that scientists might engage in all manner of devices - from the rhetorical to the reprehensible - to have their points of view prevail. The only protection against any kind of corruption in science is to celebrate the liberalism inherent in Karl Popper’s philosophy of science, regardless of whether we share his political liberalism.
As I said at the beginning, the history of science is replete with error and fraud. In science, the best kind of quality assurance is to celebrate sceptical dissent and reject any call to bow to a consensus, that “the science is settled”, on principle - not just even, but especially when it supports our preferences. Because as Carl Sagan once put it, “Where we have strong emotions, we’re liable to fool ourselves”.
This article is an edited version of a speech given for the Institute of Public Affairs’ Brisbane Club lecture series on May 1, 2008..