Science has reached a strange crossroads. On the one hand, our media is full of images of "mad scientists," and "Dr. Science" provides a daily dose of nonsense to a radio audience increasingly skeptical of science’s relevance. On the other, some people place too much trust in science, and political leaders routinely cite individual scientists – who may or may not be representative of majority opinion – for priestly explanations that justify a particular policy decision.
Science, however, should neither be dismissed as irrelevant nor looked to for absolute "answers." A look at how science and policy-making interact on the issue of global climate change illustrates both the limits to science and how science can – and should – influence action.
But first, what is "science"? Many different things. It is a body of knowledge – observations about the world. It is a systematic description of knowledge – theories that attempt to organize information into rules or laws. It is a modeling tool that helps us stretch time to look into the future. Perhaps most important, science is a set of processes that comprise a paradigm for investigation of the world – a method of study.
Each of these aspects of science has only a piece of the whole truth, and science is only one among many ways of studying the world. If we forget that, and expect science to give us an absolute answer to a problem, we invite misunderstanding and consequent policy errors. When we demand certainty from science before setting policy or acting on problems, we ask too much of science and expect too little from policy makers.
As a body of knowledge, science is limited by our ability to observe and measure the world. It is also limited by the sheer volume of data available to us, and the uneven quality of the information we do have. It is expensive to collect, verify, process, and store information. The act of measurement and presence of the observer change the thing being investigated, sometimes destroying it. Consequently we are forced to make inferences about the whole based on partial knowledge.
To explain our observations, we develop theories. Scientific theories provide a framework for identifying critical uncertainties and focusing our quest for new information. A proposed theory is rejected if it fails to explain the facts at hand. Theoretical science thus advances by gathering new information and testing the existing body of theory against it. When a theory can no longer explain all the information, it is rejected in favor of one that better explains the facts. In a sense, then, science proceeds by error and revision, through a process of debate and argument. Paul Tillich wrote, "The truth of science is correctness," which may be true about science as a body of knowledge. In theoretical science, however, truth is not in correctness, but in the possibility for error.
The branch of science that gets the most attention of late is that branch which make models of reality and predictions about the future. It is also the most contentious, simply because it relies so heavily on subjective judgments about what features of a highly complex system to include in a model, how to interpret theories, and what data to consider. Because modeling is subjective, it is subject to debate – which makes good press.
On complex issues like global climate change, what typically gets reported is not the consensus among scientists about major underlying assumptions, the main body of knowledge, the solid theories that seem to be robust, or the best models. The disputes make better sound bites and more interesting headlines. The resulting appearance of chaos is inaccurate. It is important that we keep the differences in mind so that we don’t fall into the trap of wrongly believing that science has final, absolute answers – but we need to also be aware that there is substantial agreement among scientists.
Simply put, science cannot provide the sort of truth that can help us make error-free policy, nor should we expect it to. We certainly don’t demand that policies related to non-technical matters be error-free. We don’t require absolute certainty from economists before setting economic policy, nor from educators before designing education policy.
When we design policies in the face of uncertainty – i.e., virtually all policies – we should design them to permit monitoring the outcome, so that we can learn from our actions; to be reversible, in case we have missed a critical uncertainty; and to reduce the consequences of being wrong. In environmental circles, this is called "adaptive management." (Other people have called it common sense.) Interestingly, when we design actions that are consistent with the adaptive management criteria, they often make the most sense whether the underlying science is right or wrong.
ACTING DESPITE UNCERTAINTY
Turning to the specifics of the global climate example, we have good data over a period of decades that demonstrates increasing concentrations of carbon dioxide in the atmosphere at a Hawaiian mountain observatory. But the information we have on the Earth’s temperature is not as good, so we cannot yet demonstrate with the same certainty that the climate is either warming or cooling.
Scientific theory explains the observed increase in carbon dioxide and other "greenhouse" gases in the atmosphere and their observed effect on heat reflection and radiation. The theory says that the more greenhouse gases we add to the atmosphere, the more incoming solar radiation will be trapped, tending to raise the temperature of the Earth. The theory cannot be considered "absolutely correct." But it does explain most of what we now know about atmospheric carbon dioxide and its effect on heat, and no competing theory offers a better explanation at this time.
The best global climate models predict that the greenhouse gases already in the atmosphere, and those we are likely to add to it over time, will lead to an increase in the Earth’s temperature and changes in precipitation patterns. The models can’t tell us much about regional changes in storm patterns, or predict precisely how much or how soon the climate will warm up – but they do point toward a significant warming over the next decades. That’s the limit of what science can tell us. Decisions we make based on that science are policy.
It makes very good sense, as policy, to implement cost-effective energy conservation measures to reduce carbon dioxide emissions and thus abate global warming. This action is in line with "adaptive management" principles: it is potentially reversible, we can monitor the results, and it makes sense (because it would save money, improve air quality, and perhaps even avert future wars over oil) even if the predicted climatic warming is wrong. Therefore we should reduce our use of carbon fuels, while continuing to monitor atmospheric carbon dioxide levels and the global temperature. At the same time, we must prepare to mitigate the impacts of predicted climatic changes.
The alternative is to study the situation further, gather more information about the Earth’s temperature, test our theories against new information, and refine our models – while we continue to release more carbon into the air. It is unlikely, however, that even several years of scientific study will improve a policy we could develop today. A delay in taking appropriate action is not reversible, and there would be severe consequences if the predicted global warming is right.
Using vague notions of "scientific uncertainty" to avoid making difficult public policy decisions reflects an inaccurate understanding of science at best, and a dangerous foolishness at worst. Unless we take action to limit the impacts of our unsustainable activities, and make restorations where we can, we will only increase the damage created by our current policies. We should look to the consensus and agreement that exists in our current science, consider the risks as well as the costs and benefits of our proposed policies – and then get on with doing the right thing.
Duane H. Fickeisen is an associate editor of IN CONTEXT and a research ecologist formerly associated with Battelle Memorial Institute. He manages the Context Institute ToolBox Program and serves as the Institute’s Administrator.