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The Modeling Problem: Garbage In, Gospel Out

Jan 8

2007

Planners by definition deal with complicated problems, and the only way to handle complicated problems is with models. Some models are computer programs. Others are simply in the heads of the people doing the planning. Either way, they are simplifications of reality.

For some purposes, simplifications can be useful. But when planning something as complicated as a national forest, urban area, or regional transportation system, planners fun up against what I call the Law of Modeling Limits:

Before a model becomes complicated enough to be useful for planning, it becomes too complicated for anyone to understand.”

National forest planners ran into this problem in the 1980s. Each national forest averages nearly two million acres that often range from lush wetlands to tundra. Competing uses for the forests include timber, livestock grazing, mining, recreation, wildlife, fisheries, and numerous (often incompatible) forms of recreation. Each use had positive or negative effects on the other uses.

Computer models allowed planners to divide their forests into just a few hundred kinds of land. This meant such important factors as soil productivity and erodability were usually left out. Models usually allowed planners to include only a handful of resources and the modeled relationships between those resources were crude.

The oversimplified models often produced results that were inane, such as the model that assumed that grizzly bear numbers in a roadless area would increase if the Forest Service decided to keep the area roadless; or the model that assumed that trees could grow 650-feet tall, nearly twice as tall as the tallest trees in the world. As one forest modeler told me, their motto was, “garbage in, gospel out.”

Despite these oversimplifications, the resulting models were so complicated that only a handful of people in the country really understood them. Certainly, the officials who based their decisions on the models did not understand them.

For example, most of the models allowed the computer to “high grade” the forest, cutting the most valuable timber first and leaving the crummy timber for future generations. No national forest manager would consider this a respectable practice, they they endorsed plans based on models that did exactly this.

“In urban planning,” warns Yale political scientist James Scott in his book, Seeing Like a State, “it is a short step from parsimonious assumptions to the practice of shaping the environment so that it satisfies the simplifications required by the formula.” In other words, planners who rely on oversimplified models are more likely to try to impose the model’s results on reality than to build more accurate models.

As absurd as this sounds, some planning advocates actually endorse such a policy. “If economic reality is so complex that it can only be described by complicated mathematical models,” says planning guru Herman Daly, “then the reality should be simplified.” Under this ideal, planners should regulate choice and complexity out of existence and require everyone to adopt the lifestyle choices that planners think best.

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Reprinted from The Antiplanner