Defining What We Need to Know
DANIEL R. SAREWITZ
How do we know what we need to know? This is not a question that we as a society approach in a particularly rigorous manner. When a technical problem rears its head in a political way—anything from global climate change to the AIDS epidemic to nuclear waste disposal—we are often quick to call for more research but not to define the problem we are trying to solve. Our casualness about defining research problems has often meant that we conduct world-class science that is ill-suited to addressing the problem at hand. Sometimes our approach to research can complicate the political challenges surrounding a problem.
New knowledge is usually a good thing, but all new knowledge is not equally useful; in some cases, existing knowledge may be sufficient to enable action. In the areas of global climate change and human health, for example, research agendas have strongly focused on advancing our fundamental understanding of climate dynamics and molecular genetics. But we haven’t really defined the particular problems we are trying to solve or the types of knowledge best suited to enabling progress. I believe one mistake we often make is to define such problems as scientific in nature, when in fact it would be more productive to consider them, at least partly, as engineering challenges. This mistake reflects a widely held predisposition that fundamental understanding must always precede action. This assumption may reflect the political strength of the basic research community in the science-policy pecking order, but it does not do justice to the complexities of the real world. To illustrate my point, I want to reframe two well known and well understood challenges concerning the environment and the developing world. Let me begin with a story.
The term Lupang Pangako means promised land—the sardonic name given to a garbage dump outside the city of Manila inhabited by almost 100,000 people. I visited Lupang Pangako about 15 years ago in a different life as a geologist, and the place really is hell on earth. As you drive through the Promised Land, you see stygian mists rising from the hillsides, the mountains of garbage, and if you look closely you see movement everywhere in the distance. You soon realize that the mountains are covered with people scavenging for their livelihoods.
You may remember that in July 2000 torrential typhoon rains caused a huge landslide in the Promised Land that buried more than 200 people under a mountain of garbage. To me, this horrific event provides a powerful indicator of how we should be thinking about the impacts of climate on people and about human adaptation. The problem was not whether the typhoon was an above-average or below-average event. It was not a problem whose root causes could be revealed through a better understanding of anthropogenic climate change. The problem was that 100,000 people were living in poverty so deep that they could survive only by culling garbage.
The results of humanity’s mistreatment of the environment fall disproportionately on poor people, on developing countries, and on tropical regions. Although these impacts are most severe in their chronic forms, they are most spectacular in their catastrophic versions, such as this landslide. As Figure 1 shows, the number of disasters has risen sharply throughout the world in the last 30 years, most markedly in the developing world. This trend does not reflect a changing climate; it reflects changing demographics—growing numbers of poor people living in urban areas, living in coastal regions, living on garbage dumps. Unlike changes in climate, this trend is something we can control. These are not natural disasters; these are intersections of natural phenomena and complex sociopolitical and socioeconomic processes.
The number of disasters will continue to rise because we know that demographic trends are pointing toward more urbanization and greater numbers of impoverished people moving from agrarian areas to cities—often to areas in harm’s way. Megacities like Jakarta and Manila that have nearly 10 million people apiece are subject to typhoons, volcanoes, earthquakes, landslides, epidemics, and floods, for example. Because generating more knowledge on climate dynamics cannot help us in the short term, it is worth talking not just about the behavior of the climate and our capacity to modify it by reducing greenhouse gas emissions, but also about the interactions of social systems with climate and the engineered systems that sustain human beings. These systems are not sensitive to emissions of carbon dioxide but are very sensitive to demographic and socioeconomic trends. We have much less control over the future behavior of the climate than we do over the behavior of human beings.
Given the complexity of these interdependent systems, the practical challenge is to learn to operate in ways that minimize our impact on the planet and maximize our resilience in the face of unpredictable events and the ever-changing
relationship between humanity and the environment. But the key is to focus on the human condition, because, in a world of 6 billion or more people, that is the central variable in the relationship between society and environment. This focus will require both much less and much more of engineering than we have asked in the past: much less because the idea of complete knowledge of, and control over, nature has been revealed as illusory; much more because we also know that, in the absence of complete knowledge and control, our most feasible course is to learn by doing—and doing means engineering.
Until recently, efforts to connect climate research to specific social outcomes, such as reducing people’s vulnerability to climate and weather and improving management of water resources, have been afterthoughts at best, modestly funded—typically at a level of about 5 percent of total program support—and poorly integrated into larger programs. However, researchers on the human dimensions of climate change are beginning to understand how to generate
knowledge that improves the capacity of people and organizations to respond to a dynamic climate. Much of this knowledge will have to come from Earth systems engineering (ESE).
The social outcomes of science and engineering do not emerge fully formed from the laboratory; they are created by evolving interactions between the results of research and the needs and capacities of society. One central concept of ESE is that many complex problems must be framed in an integrated technical and social context. This is both a technical and a political insight. Just as no single discipline can capture the complexities of the interactions between natural and social systems, neither can any single perspective provide a vision that is responsive and accountable to diverse stakeholders. The ESE approach is to develop a repertoire of tools that can be applied as needed to move toward a vision. Both the approach and the vision will change over time. A solution to a problem, therefore, is the formulation and implementation of an integrative and iterative process, using a combination of social and technical approaches. A solution is not a static condition of complete control—such a condition is impossible.
Now I want to turn to the public health effects of poverty and environmental degradation. This subject may seem to be far from an environmental engineering issue, but I maintain that it can productively be considered in that light, and that the failure to do so reflects our inability to “know what we need to know.” Figure 2 shows the relationship between GDP per capita and life expectancy. On
the left side is disability-adjusted life expectancy; these are the years one can expect to live without a serious disability or hospitalization.
About 80 percent of the world population resides on the very steep part of the curve, where there is a strong correlation between increasing GDP per capita and increasing life expectancy. The direction of causation runs both ways—more wealth may enable a person to have better health, but better health also enables a person to be economically productive. Yet the majority of biomedical research dollars are aimed at diseases that mostly afflict people on the flat part of the curve, where the correlation is very weak. GDP per capita rises to great heights, but life expectancy remains fairly level once one’s income tops about $5,000 per year. Even if a health problem afflicts people on both ends of the curve—AIDS, for example—the interventions useful for people living in the flats may be irrelevant to those living on the slope, as we have discovered to our shame in Africa.
The problems faced by nations on the steep part of the curve cannot be best addressed through biomedical research; they are often problems of Earth systems engineering. They are about finding innovative, efficient, and affordable ways to deliver water, sanitation, food, basic health care, safe shelter and workplaces, and higher environmental quality—that is, making it unnecessary for people to live on garbage dumps. These kinds of challenges require putting some basic infrastructure elements into place. Although this is fundamental, on-the-ground engineering, past failures attest to the extreme difficulty of implementing changes. We must ensure that the technical criteria for engineered systems are compatible with the social, political, economic, and environmental contexts in which they must operate. This is an enormous challenge for ESE.
As these examples of the interactions between public health and climate change illustrate, science policy is often not well aligned with social needs—even if proponents have explicitly invoked those needs to justify the science in the first place. This misalignment reflects a failure to think carefully about what we need to know to address a given problem, a failure to define problems in a way that can stimulate positive action. Some problems we have defined as scientific might be reconsidered as engineering challenges. The obvious justification for this reevaluation is that we already know enough to take action now on some problems, such as climate impacts and public health. But something more subtle is also going on. By redefining a difficult environmental challenge as an engineering problem rather than a scientific problem, we acknowledge we must inevitably take action in the face of uncertainties and complexities. This is what engineering is all about—finding solutions that can work despite our imperfect knowledge. This is also, interestingly enough, what politics is all about.
The central point is simply this: setting effective research priorities for solving environmental problems requires that we think carefully about what we really need to know to take action. This will require an explicit articulation of the social goals we are trying to achieve. In the absence of such clarity, we often define environmental problems in terms of scientific opportunity rather than real-world
issues. Not surprisingly, this can lead to distortions—spectacular climate-modeling capabilities paralleled by growing global climate change, for example. In this context, it seems to me that a new and clearer look at our most serious environmental problems demands a more central role for Earth systems engineering.
REFERENCES
Office of Foreign Disaster Assistance/The Centre for Research on the Epidemiology of Disasters. 2000. EM-DAT: The OFDA/CRED International Disaster Database. Available online at <http://www.cred.be/emdat/intro.html> (December 6, 2001).
World Health Organization. 2000. World Health 2000. Geneva: World Health Organization. Available online at <http://www.who.int/whr/2000/en/report.htm> (December 6, 2001).