Napping on the railroad tracks sounds risky on its face. But it may not feel that way if you don’t know you’re napping on the tracks.

Humans seem programmed to believe that the future will look pretty much like the past. But the narrative of history is the narrative of unexpected events. And, so it is surprising that when it comes to resource depletion, cornucopian thinkers love to refer to history. Daniel Yergin, chairman of Cambridge Energy Research Associates, likes to say, “This is not the first time the world has run out of oil. It is more like the fifth.” But even though Yergin admits that oil is a finite resource (and that therefore its total quantity is declining), he invites us to snooze with him on the railroad tracks because history has shown that so far that it’s been safe to do so.

Yergin’s faith (and that of many others) is founded on the forecasts of his own firm and that of the U. S. Energy Information Administration (which takes its data from the U. S. Geological Survey’s World Petroleum Assessment). But what drives us to make such forecasts? Even create a whole forecasting industry? In his latest book, The Black Swan: The Impact of the Highly Improbable, Nassim Nicholas Taleb believes that we do so because we are planning animals. This behavior may be a successful evolutionary adaptation. We are able to imagine situations that might risk injury or death rather than simply experiment and see what happens. “Used correctly and in place of more visceral reactions, the ability to project effectively frees us from immediate, first-order natural selection….,” he writes.

But, imagining the future is not the same as correctly predicting it. Taleb outlines the problems with forecasts as follows. First, variability matters. Most forecasts don’t include an error rate, often indicated as a range of possibilities. In other words, how wide of the mark might a forecast be? (The U. S. EIA forecast is an exception, but it is not clear how the error rate is calculated and whether the data upon which it is based can be justified.) Very often, the “error rate is so large that it is far more significant than the projection itself!” (The EIA doesn’t seem to understand this point.) Taleb gives this example: If you knew the place you are flying to is expected to be 70 degrees, you would pack much differently if you also knew that the range was plus or minus 40 degrees rather than plus or minus 5 degrees.

Second, forecasts degrade quickly as the forecast period lengthens. There are so many imponderables including technological developments; individual, corporate and government decisions; and unforeseen events such as wars, revolutions, and economic busts and booms, each essentially unknowable and each compounding upon the others with every passing year. “Our forecast errors have traditionally been enormous, and there may be no reasons for us to believe that we are suddenly in a more privileged position to see into the future compared to our blind predecessors,” Taleb writes.

Third, there is often a failure to grasp “the random character of the variables being forecast.” Taleb doesn’t address resource depletion in his book. But, when it comes to oil supplies, those confidently making optimistic forecasts assume substantial new discoveries. However, discoveries can in no way be determined ahead of time; otherwise, they would be classed as reserves and not discoveries. Future consumption rates for oil depend on the economy which depends on so many individual and collective decisions that one cannot tally them all. And, even if we could, how would we know what numbers to use for 2017 or 2026?

When it comes to technology, it has always seemed to be a one-way street, ever improving. There can be no dispute that technology has put into the hands of human societies great power to learn about the world and to manipulate it. But, even here there have been long stretches of only small, incremental improvements in, for example, our ground transportation system which relies on the same basic internal combustion engine technology first produced more than 100 years ago. There have also been notable failures–no commercially feasible fusion energy and no miracle cures for genetic diseases. Technological development moves unevenly through various sectors, sometimes by fits and starts and sometimes not at all.

All of this implies that we have no way of determining whether we should prefer pessimistic or optimistic forecasts for world oil production. What is more perplexing is that both forecasts depend on certain kinds of extrapolations from the past. The pessimists focus on the peak in world oil discovery back in the 1960s and the optimists point to reserve growth through additions to existing fields and to advancing technology for both exploration and extraction. While the pessimists and optimists emphasize certain data, both accept the historical data, but then draw vastly different conclusions, i.e., an imminent peak in world oil supplies versus a distant peak followed in some cases by a long plateau. When it comes to technology, for example, the pessimists argue that technology has done pretty much all it is going to do for oil recovery while the optimists believe that vast increases in the percentage of the oil recovered from existing and undiscovered reservoirs lie ahead.

Taleb suggests a way to look at the problem as follows: “Even if you agree with a given forecast, you have to worry about the real possibility of significant divergence from it,” he writes. How might he apply this to the peak oil issue? He gives us a pretty clear idea. “[I]t is the lower bound of estimates (i.e., the worst case) that matters when engaging in a policy–the worst case is far more consequential than the forecast itself. This is particularly true if the bad scenario is not acceptable.”

While it’s possible that Daniel Yergin and other cornucopians may continue to nap on the railroad tracks without any harm for many years to come, it is faulty logic that leads them to believe that there is very little risk in doing so. And, because of their influence, they are doing a great disservice to society by pretending that their oracular pronouncements are somehow based on something other than conjecture. (Such an admission might cut into demand for their forecasts, but it would be better for policymakers and society as a whole if they admit to uncertainty.)

On the other side of the argument, the pessimists would be wise to attach wide error bars to their forecasts as well. They can do this without abandoning their basic premise, namely, that preparing for a decline in oil supplies will be a monumental task that is better begun early rather than late precisely because we cannot predict when the decline will begin. Moreover, the use of generous error bars will have the added benefit of removing the “Chicken Little” aura which now surrounds so many peak oil theorists.

Taleb has strong words for the unctuous forecaster who won’t admit the uncertainty in his or her work:

Anyone who causes harm by forecasting should be treated as either a fool or a liar. Some forecasters cause more damage to society than criminals. Please, don’t drive the school bus blindfolded.