a new look at Achieving consensus requires the identijiication of the components, organization and simplification of the data, and the gathering of all interested participants into the process at the outset
Donald 8. Straw American Association New York, N . Y . 10020 When contemplating how we make environmental decisions, the words of Winston Churchill come to mind: “Democracy is the worst form of government, except for all others.” The process is a political one. That is to say, the decision is not made by one person or even one governmental agency, but rather it results from the countervailing tugs of myriad political forces. The makeup of these forces varies; most visible are the lobbies representing business, labor, single-issue political groups, and environmentalists. In the short run, the interplay of these lobbies will determine the outcome. But in the long run, the evolving attitude of the electorate will influence the tradeoffs between the use of our resources and the protection of our environment. Individual value judgments, averaged into a political consensus is, for better or worse, how we resolve highly complex technical issues. One means of 0013-936X/79/0913-0661$01.00/0
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achieving this resolution is mediation-a term that includes a growing number of methods used by impartial persons to assist in finding a consensus. The decisionmaking process begins by simplifying available information-both scientific facts and value
judgments. Simplification can be both a tool for creative collaborative problem-solving, and a weapon for advocacy. One way of protecting this tool from being converted into a weapon is
1979 American Chemical Society
to devise a procedure for reaching joint decisions with regard to the simplification process itself. A story on the front page of the Sunday New York Times of November 26, 1978 provides an example of how “data mediation” one of the newer variations of mediation, might have precluded a long, expensive lawsuit and might also have assisted the problem - solving process. The headline of the story is: “Documents Indicate Corps Mislead Congress On Major Southern Canal.” T h e story alleges that the Army Corps of Engineers practiced “accounting manipulation, guesswork and misleading statements to Congress to justif y construction of the 2 billion dollar Tennessee-Tombigbee Waterway. The story states that the Corps, in arguing for the canal, “predicted barge traffic that ranged from unlikely to physically impossible,” presented a “cost-benefit ratio based’on a channel width nearly twice as large as Congress authorized,’’ and “reported to Congress and the public a cost figure of $8 15 million for the project while inVolume 13, Number 6, June 1979
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ternal communications show that the Corps was aware that the true costs would exceed $ 1 billion.” Whether or not these allegations are true is not germane to our argument. The mere fact that they are being contested in court so late in the controversy-the project has been under consideration for many years-is what is of importance to this story. I f the Corps, as the lead agency involved in this decision, had been forced by the process to share with the other concerned participants the facts upon which it was going to base its arguments, and if an early procedure for a data mediation had been employed, it is my contention that an important element of controversy might have been identified and resolved at the outset. A mailroom example will help explain data mediation. Let us consider that instead of simply alphabetical designations, each pigeonhole represents one element that has to be considered in an environmental decision; for example, a decision concerning the development of surface coal mining. Among the many factors to be considered are these: the mining method, the disposal of overburden of soil above the coal, the predicted life of the mine, production levels under various conditions, the maximum coal that can be recovered, the fish and wildlife which inhabit the area, the likely air pollution and methods for controlling it, the likely dust that will be created and methods for controlling it, disposal of acid and toxic materials, and required revegetation and its cost. The above is only a partial listing, with no attempt yet made to consider interrelationships. But under each of the above headings, many other subheadings must be considered along with their “facts” and “assumptions,” before arriving at some determination regarding their impact and importance to the overall decision. Putting each of these considerations into a convenient pigeonhole, examining each of the facts and assumptions which must be considered, and using some form of data mediation to reach as much consensus as possible, are all first steps in seeking to manage complexity. Unlike our mail sorting room analogy, however, we now need a more sophisticated aid to keep track of the interrelationships of these various considerations, and to help us explore how changes in the components of one pigeonhole will alter what happens in all the others. At this point we must avoid the danger of an overload of information, keeping in mind that our objective is to 662
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handle complexity, not to increase it. One way of doing this is to avoid trying to be too precise or complete in filling the pigeonholes with unnecessary facts and figures. The objective of the data is to help in predicting impacts and assessments of the action contemplated. It is unnecessary, and would probably be counterproductive, to store masses of data. What is more important than precise data is the precise definition of the problem, the logic that will be used in helping determine the impacts, and a conscious effort to make explicit the unconscious experience and attitudes which most people bring to a problem at the outset.
Quick and dirty By building what computer scientists call a “quick and dirty” model, you can begin to make some gross decisions with respect to available alternatives. Decisionmakers will not be persuaded to change their minds with models that have been constructed by others, but if they have participated in constructing the model then changes of opinion may occur. One example of this was cited by C . R. Hollings (see additional reading) at a workshop conducted at the University of British Columbia. The case involved the management of salmon off the shores of British Columbia. The problem was how to permit fishermen a fair annual catch and, at the same time, safeguard the salmon stock against depletion. I n the first model that was built, the group felt intuitively that the correct approach would be to
Counterintuitive result
prohibit the retention of all salmon under 5 1 Ib. But in running the model, it was discovered that this would probably increase the catch of salmon over 51 Ib to such an extent that it would have an even larger adverse impact on the total stock of salmon than was then occurring. Once this outcome was made clear by working the model, the group next collaborated on the search for a different strategy. The solution developed and accepted by the fishermen’s representatives was to restrict the total catch per fisherman to a limit of pounds of salmon per annum, rather than to put limitations on any category or size of the fish. This solution safeguarded the total stock of fish and treated all fishermen fairly. Several key features of this approach are illustrated in the above example. First, no overload of specific facts was required for this model to operate. Rather, simple intuitive logic was put into the model with regard to the actions and impacts that could be expected under different strategies. Such a model can be developed relatively quickly. Since all decisionmakers and actors were involved i n constructing the model, the lessons developed by the model, even those which were at first counterintuitive, were accepted as valid. It, in effect, was a rough approximation of reality, a synthetic rendition of the real world which was credible because it was constructed by those who were participating in the decision. I n the course of constructing and
running these models, increasingly sharper definitions can be written concerning the objectives of the group, and the factors which must be considered in achieving these objectives. At the same time, extraneous factors and, of course, their accompanying data and facts, can be discarded as irrelevant. Even though each succeeding generation of the model becomes more detailed in some respects and. therefore, a closer mirror of reality, an accompanying process of simplification also occurs. I n practice, the only way to determine the optimal number of variables and the amount of detail that is required is by trial and error. Such trial and error, or playing the game of “what if,” not only improves the model for decisionmaking, but is also a process of collaborative decisionmaking itself. This process also permits the early recognition of disputed facts and assumptions. Those that appear to have little or no bearing on the outcome of the decision can be eliminated. Other disputes can be resolved at this early stage, or else the differences can be narrowed by the use of old-fashioned mediation techniques applied to this new tool for the management of complex decisionmaking.
Avoiding an overload An overload of information can smother logical thinking and interfere with creative problem-solving just as effectively as insufficient information can create vacuums for prejudices and irrationally held benefits. But to avoid an overload, some considerations must be left out. And the very act of leaving out certain information for the purpose of simplification can be controversial. The scientific community is the source to which we must look for the available objective facts about environmental issues. But scientists, too, a r e forced to deal with humanly understandable chunks of information, and the more specialized the scientist is, the narrower is his focus and the more selective must be the facts that he can give us. So when a scientist gives an opinion, it is important to ask exactly what simplifications he has made-in other words, what he has left out. The most important question to be asked is what certainty there is in the facts and predictions given by the scientists: what are the probabilities of error, and what are the consequences if there is an error? If the decisionmakers have an inventory of carefully gathered, well-
understood facts, this makes more explicit the foundations upon which judgments are based and reduces prejudice and increases logic in the consideration of alternative solutions. But not all judgments are rooted in facts. There still remain values which are not subject to scientific inquiry.
Human-sized chunks The human mind can handle only from five to nine variables simultaneously. To resolve a complex problem, we must therefore arrange the task in such a way that we can look a t the problem, and discuss it in chunks containing approximately seven components. We, of course, do sequential scanning of any large problem continuously throughout our waking hours. But as the task gets more complex, it becomes increasingly difficult to retrieve the particular combination of components we wish to consider, to make interim decisions and reach intermin agreements about pieces of the entire problem, and then to understand the impact of these on the problem as a whole. We are presented here with a dilemma. I f we try to solve the problem as a whole, without going through the simplification processes we have discussed above, we are forced by the limitations of our mental capacity to reach conclusions based on only a small fraction of the variables that require consideration. On the other hand, if we do consider pieces of the problem in human-sized chunks, we are then faced with a new set of problems: making as certain as possible that we have not left unattended any important components of the whole problem, and ,also finding some way of piecing together our interim conclusions and agreements into the matrix of the problem as a whole. Unless we can avoid these twin dangers, we will reach irrational conclusions. Dealing with intangibles We must, however, temper our zeal in searching for rationality and logic w i t h the recognition that uncertainty and unknown risks always accompany every environmental. decision. One basic cause for this uncertainty is the difficulty, sometimes the impossibility, of obtaining hard, undisputed facts. Never was this better expressed than in the report of the Licensing Board (in the matter of Consolidated Edison Co.) that heard one phase of the Indian Point No. 2 plant dispute on the Hudson River. Another element in the complexity of environmental decisions is the need to weigh present and easily computable
costs and benefits against future costs and benefits which are less tangible and less easily computable. Because of the difficulty of weighing present tangibles against future intangibles, it is correspondingly easy to attack any attempt to “get agreement on the facts,” or to construct a model which will help weigh costs against benefits by playing the game of “what if” with various solutions. Those of us who advocate data mediation and model building uill not prevail if we t r y to argue the accuracy of predictability of the models that can be built. If we have a prevailing argument, it is this: The very act of trying to seek agreement on the data, and to build the model, will in itself help us understand the complexity of the problem with which we are dealing. It will force us to better understand the viewpoint of our opponents and, conversely, help our opponents understand our viewpoint and, if performed with integrity and intelligence, it should improve predictability and accuracy over that available without these aids.
Accepting risks But even greater than the difficulties imposed by the uncertainties of the data is that of trying to reconcile different thresholds for accepting risks. A benchmark that is often quoted in the debate over risks is that, in the U.S., the chance of being killed in an automobile accident in any given year is one-in-five thousand. On one side of such debates are those who fear that exaggerated concern with risks will foreclose the technological options of future generations. and destroy political democracy in the West. At the other extreme are those environmentalists who believe that any risk to environmental degradation tnust be avoided. The acceptability of risks is a highly Volume 13, Number 6, June 1979
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individual value judgment. With risks far into the future, it becomes even more difficult to grapple with any tangible quantitative analysis of the trade-offs of present benefits for future risks. Of course, even if we were able, with whatever aids we may devise, to examine every factor, would there be any assurance that the decisions made would be rational? I n this, as in most human endeavors, we must seek approximation, not absolutes. What we are looking for is the closest approximation to a holistic examination of the problem, and the closest approximation to a rational decision. In the end, hunches and intuitions, political clout and self-interest will continue to influence decisions. But to accept these realities of the political process does not deny the role of rationality and structured problemsolving. Decisionmakers, whether they be individual citizens at the polls or top government officials, must base their decisions on a set of value judgments. As the quality of information and information transfer are improved, so will be the quality of the judgments of the decisionmakers.
Managing value judgments Because values are difficult to quantify, there is danger that the more easily quantifiable factors will “overpower” values if models are used. The best way to guard against this danger is to recognize the problem early in the process, and then continue to emphasize it. One approach to considering values is to start with the most quantifiable, and then move toward those more difficult to quantify. For example, a piece of land can have: market value; utility value; aesthetic value; and symbolic value. Symbolic value, the least quantifiable of all, may still have the highest value of all in terms of an individual’s willingness to sacrifice everything up to and including his own life. Another approach to identifying values is to understand the degree of awareness an individual or a community has concerning the issue under discussion. The degree of awareness might be ranked as follows: unaware; intellectually aware, but unmotivated; and emotionally aware and prepared to take action. For example, before Rachel Carson wrote Silent Spring, only a few scientists were aware of the dangers of DDT. Miss Carson’s book sounded the alert and a much wider segment of the public became “intellectually” aware of the problem. Then others took up the “cause” and dramatized the dan664
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ger in ways that some considered sensational and irresponsible, but which motivated a large segment of public opinion from simple intellectual awareness to being emotionally aroused. As a result, enough political pressure was created to produce action-the widespread banning of DDT-and a whole new era of emotional awareness about the dangers to the environment of chemical intervention. This points up both a moral and practical dilemma. Without such dramatic consciousness raising, it is doubtful whether the barrier between intellectual awareness (which is likely to lead to action) and emotional awareness (which will produce political action) can be overcome. On the other hand, emotionalism can produce overreaction in some cases, and in other cases can even produce action in the “wrong” direction. Of course, when we speak of “wrong direction,” a new value judgment is injected into the discussion. In the Rachel Carson case, most would agree that an awareness of the dangers of DDT was an action in the right direction, even though some may feel that it was carried too far. But there are many other issues where right from wrong is not so clear. One contemporary example of this is in the “Right To Life” campaign of those who oppose abortion as distinguished from those who feel that the right to abortion is both a human right as well as a social benefit. Fortunately, however, most of the hotly contested environmental disputes, while displaying some of the outer symbolisms of irreconcilable beliefs, are, in fact, capable of a more rational approach. We spoke of value judgments as an “output” of the human brain. Now let us refine this definition. Value judgments are those which bubble up from our past experience and general information, but which have not been dissected into their separate components. For example, many people today have a value reaction to experimentation with recombinant DNA (experiments that combine the genetic material from separate species). Some of these reactions are a simplistic abhorrence to the notion of human intervention in the creation of life. Some others react with an equally simplistic desire to protect the freedom of scientific inquiry. Either one of these simplistic beliefs can be strongly held, even to the point of emotional readiness to take action, without very much basic understanding of the many complex ingredients in the problem itself.
These same observations could be made about many of the currently “hot” environmental problems of the day: whether it be offshore oil exploration, the use of atomic energy for power, surface mining, or the building of dams. And yet today, when the public-informed by the mass media-demands to be consulted before political decisions are made, it is important (perhaps even our survival depends upon it) that the public be informed with as much detail and hard data as possible. But this is easier said than done.
Informed participation Thus far we have spoken at considerable length about the complexity of the many variables in making environmental decisions. There are the variables of data, the interaction of different components in the decision matrix, and the equally important but less quantifiable beliefs and values of the participants. This complexity is compounded further because of the large number of participants who demand a voice in the decision and its implementation. “ l fsou study the histor.) o f political decisions about the enrironment, or, for that matter, decisions about some other social issues. JOU find that there are no new Jerusa/ems at the end o f the road; goals for society are redefined b j the process o f choice ererj time a choice is made. This is notahlj true for the politics of eniironmental protection. Each political decision implants a choice into our system o f social values; this imgerceptibl! changes the system o f ralues, and this in turn effect9 the next choice. ” Eric 4 shhj Decisions which our politicians and government officials are making today have never before been so complex and so dependent upon sophisticated, scientific judgments. At the same time, ordinary citizens have lost confidence i n the traditional decisionmaking processes of representative government, and have insisted increasingly on direct participation in making, or at least i n ratifying, these decisions. At the same time, a large and apparently increasing number of citizens are “dropping out” by remaining absent from the polls on election day. This leaves the situation as follows: elected politicians and appointed government administrators having to share the decisionmaking process with
an electorate composed of a minority of citizens, many of whom have organized themselves into “single-issue” lobbies, and who pursue their particular goals with determination, political skill, and narrow focus. This condition imposes a number of new burdens on the democratic system which must be managed if it is to survive. We must find improved methods for simplifying and handling the complex decision matrix. We must learn how to engage a number of participants; larger, for example, than can sit around a single negotiating table. We must learn how to extend the decisionmaking process, and make it seem “relevant” to the near majority of eligible voters who seem to have dropped out of self-government. And finally, we must reexamine the jurisdictions of the various bodies of our formal government structure in light of increasing direct citizen participation in making specific decisions. For example, what are the roles of the elected legislatures, the executive branch, the regulatory agencies, and the courts with respect to direct citizen participation? It is traditional, when thinking of citizens exercising their democratic rights, to t h i n k also of the vote. The vote is one of the sacraments of democracy. But as a means for involving citizens i n the intricacies of modern self-government, it has become almost obsolete. It is still admirably suited for deciding between two candidates for office-a yes-no choice. In the technical language of decision theory, this is a “zero sum” choice, with one candidate clearly winning and the other clearly losing. But for reaching decisions of a more complex nature, the simple yes-no vote is as inappropriate as a hammer in the surgical kit of a cardiologist. I f these complex dccisions are to be determined by citizens, then citizens must be provided with an earlier opportunity to participate in the decision process to produce :i reasoned and balanced public opinion at the polls. The process itself provides the opport u n i t y for growth and the accumulation of wisdom. Unless we learn to manage this process under the changing conditions of a democratic society, we will have to put the entire system itself i n jeopardy by permitting an unplanned drift into ever wider citizen participation without providing for the learning process that these decisions require.
Summing up In conclusion, what I have been pointing to is more attention to process
If citizens are to make final decisions they must participate in earlier decisions
What alternativ to consider?atom, water, coal, solar.
atomic and coal plants?-Safetycosts-benefits
solar, do we want to accept the risks and benefits of the atom?
Zero-sum vote
w
2
Atomic plants?
n
Yes
and procedure for handling complexities. The process of decisionmaking in large-scale, complex problems proceeds in a cycle that starts with the recognition of a problem, the gathering of facts and assumptions about the problem, the determination of different alternatives for its solution, the identification of interested persons and groups who will be concerned with the decision, the resolution of disputes over the making of interim decisions toward a final solution, the making of a final decision; and then the cycle is apt to repeat itself again since, a single “final” decision rarely results in a final solution. The Drocess proceeds like a perpetual game of trial ‘and error as the decision-dispute-decision cycle moves along. I n short, environmental decisionmaking in a democracy should seek to: reduce advocacy make room for more collaborative problem-solving involve participants early in the process establish i n c ~ m e n t a l decision points rather than a single yes-no vote at the end of the process.
o
No
Additional reading Simon, H . A., A S t u d y of Decision-Making Processes in Administrative Organizations. 3rd edition, Free Press, New York,
Collier-McMillan, 1976. Hollings, C. S., Adaptice Encironmental Assessment and Managetnents, Institute of Resource Ecology, University of British Columbia, Vancouver, B.C. Ashby, E., Reconciling Man with the Environment, the Leon Sloss Junior Memorial Lectures, Stanford University Press, 1978, B.C. Miller, G., The Magical Number 7, Plus or Minus 2: Some Limits on Our’CaDacitv for Processing Information, P.sychol.‘Rec..: 63, 81 (1956).
Donald B. Straus is president of the Research Institute of ihe American Arbitration Association, h,hich is administering a number of projects in environmental mediation. He sits as a member or trustee on seceral commissions and institutions of learning. Coordinated by L R E Volume 13, Number 6, June 1979
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