(This blog post is written following a reading of Science and Public Policy – The Virtuous Corruption of Virtual Environmental Science by Aynsely Kellow, published by Edward Elgar in 2007. I strongly recommend this book. The arguments below are largely based on it).
Some of the claims made by respected scientists with respect to the environment and climate change will, with the benefit of hindsight, look ridiculous. Let us just cite one example from amongst many. Sir David King, former Chief Scientist for the UK Government, said in 2004 that “Antarctica is likely to be the only habitable continent by the end of the century”.
What leads these scientists to make such claims is the increasing reliance, especially in the environmental sciences and climatology, on computer simulations largely based on scenarios. Given that randomized control trials of environmental change or climate change are not possible, researchers have moved increasingly to simulators and models which depend for their data not on observations, though some are used in the building of models, but on assumptions. Such models now dominant some branches of science and their results, as opposed to the results of direct observation are seen as ``superior``. One example of this is the preference for the models which show continuous global warming in this century, whereas the direct observations suggest that the global temperature has been cooling for some time.
E.O Wilson’s biodiversity loss assumption, which newspapers escalate routinely as indicating a loss of between 50,000 and 100,000 species each year, is another example of the model being seen as preferable to actual data. Wilson has claimed that some 27,000 species are lost each year. The claim is based on a simple mathematical equation, not observation. The equation looks at the probability of biodiversity within a geographic area and then makes assumptions about what will happen in that area if its character of that area is changed (e.g. through deforestation or flooding) and what species may survive and which will not. It is a scenario, not a prediction and certainly not a fact. Direct observations of actual locations suggest that species loss is less than three species, not accounting for the hundreds of new species found each year.
Computer models are complex. They rely for their veracity on equations which show the relationships between variables, generally driven by regression and multi-dimensional scaling. Such equations in turn depend on interpretation of a theory – a theory of the relationship, for example, between the sun, sun spots, clouds, CO2 and other greenhouse gasses, the tilt of the planet, ocean currents, the effective of the oceans as heat and CO2 sinks, the impact of volcano’s and so on. Only when these equations are built and the relationships between the variables established following a theory does actual data come into play.
These data often have to be manipulated to take into account a variety of concerns – partial data is manipulated to gain completeness, data sets are adjusted for errors in both collection and transcription, outliers are often excluded and so on. In climate science, for example, actual temperature measurements are adjusted to take into account the location of the thermometers which measure temperature. Such adjustment involves decisions about what is expected, which are in turn influenced by assumptions.
One of the ways in which those building models verify their model and its veracity is not by comparing its output to observed data – for example, comparing the scenarios developed in the IPCC assessment reports which what then actually happens – but by comparing the output of one computer model with that of another computer model. This is rather like comparing two computer simulated basket ball games between the Lakers and the Bulls and then and determining who really won as opposed to comparing a computer simulation of this game with a real game between the two teams. Part of the reason this is done is that computer models of climate, for example, have yet to accurately simulate actual events.
Let us take an actual example. Computer models of global climate are used to develop a scenario for deaths from disease – as the planet warms, the theory goes, so diseases normally associated with extreme weather events increase. This leads the World Health Organization to claim that there are already 160,000 deaths each year directly because of global warming – the figure coming from a computer simulation and the counting of all extreme weather events as being due to global warming. The actual evidence is that deaths from extreme weather events has declined as the planet has warmed – 73,700 in the period 1970-79 and 42,200 in the period 1995-2004.
What leads scientists to make such claims and predictions? There are several different explanations, none of which question the beliefs or conviction of the scientists concerned. They all focus on the corruption of science as a process in favour of science as a tool in the pursuit of a noble cause.
Noble cause corruption is a standard topic in the philosophy of science. The idea is simple. The cause is seen by those who support the cause as vitally important and one that society needs to act on – a failure to do so could, in the view of supporters, have serious consequences. Every tool – the media, political influence, film and television, investment etc – should be harnessed to support the cause so that action is taken. Science is one of the tools.
This view of science as a tool in the service of a noble cause is not, then, new. It is fundamentally a Marxist view of science as an instrument of ideology. It is a view advocated by Feyerabend, an anarchist philosopher of science writing in the late decades of the last century. Feyerabend sanctioned the introduction of theories that are inconsistent with well-established facts if they lead to an advancement of social understanding or a noble cause. Feyerabend also advocated that science should be subjected to democratic control: not only should the subjects that are investigated by scientists be determined by popular election, scientific assumptions and conclusions should also be supervised by committees of lay people – something we see now in action at the United Nations Inter-Governmental Panel on Climate Change whose Summary for Policy Makers is written by lay people on the advice of some selected scientists, sometimes containing information and texts written over the objections of those scientists.
The idea that science is “poetic inventiveness that is story telling or myth making – the invention of stories about the world” in pursuit of a noble cause, as Sir Karl Popper observed, is not new, but has achieved a remarkable poignancy in our current politics. Though not new, it is now very problematic. Proposals are being made, “based on the science”, that will fundamentally change the developed world through decarbonising the means of production – essentially, the government will seize control of the means of production through its regulation of carbon dioxide – is the noble cause done in the name of saving mankind from him or herself.
Governments claim that there is a scientific consensus, when there clearly is not – look at the disputes in the scientific literature and the work of the Non Governmental International Panel on Climate Change. They claim that 4,000 scientists endorsed the IPCC fourth assessment in 2007, when only some 2,000 scientists were involved in that assessment, with only 20% of these (around 400 persons) “deal” or had some connection with climate science – meaning that most did not. They claim that sceptics are the mouthpieces of the oil industry, when many of the IPCC scientists have also benefited from oil grants and cash or grants from parties with vested interests.
Further, while a large group of scientist may support a particular view of some matter in science, it does not make them right. A large group of scientists were wrong about the geological formation of continents, about the human papilloma virus (HPV) and its links to cancer and may well be wrong about the nature of multiple sclerosis. Science is not about consensus; it is about evidence and theory – always subject to falsification.
It is time for us to restore some balance into the scientific study of climate and the environment, to fund science differently and to challenge the role played by the gatekeepers of science. Science is itself under threat.