When anyone wishes to support – or defeat – a given position, the sturdiest method is to generate data to predict its consequences. Advocates generate reams of numbers to substantiate their preferred outcome.

I would be an idiot to argue against numbers as part of the toolbox to help us understand difficult challenges. But numbers can be misleading, especially if you don’t know how they were derived. Bear in mind these are numbers that purport to predict the future.

This is especially true when it comes to climate change, where numbers paper over a lot of philosophy and assumptions. We are wading in to an uncertain climate future, yet many experts are happy to offer fascinatingly precise-looking numbers telling us exactly what to expect and how to act.

On the one hand, the numbers from opponents of climate action show, say, how the House of Representative’s 2009 Waxman-Markey bill or the EPA’s Clean Power Plan regulation will kill jobs. Whatever their accuracy, their immediacy feeds the election-to-election perspective of most elected officials despite longer-term evidence that the earth is warming, and that this warming will have dire consequences.

But even those who support climate change action and have the numbers to prove it aren’t necessarily doing us a favor. Their elaborate cost-benefit models calculate the “real” costs imposed by warming to decide what warrants action – and by definition, what does not. They come up with specific figures that can be spent without running the economy into the ground, where the benefits of action exceed the costs.

The sheer impossibility of writing a model that can capture every potential impact of climate change means that modelers decide what to quantify – and what not to. Among their choices are damage to agriculture, forestry, water resources, energy consumption, sea level, ocean acidification, ecosystems and health. On top of that, the model should – but often does not – account for a dynamic unfolding process including the possibility of abrupt, catastrophic changes. Each decision requires an assigned number.

There is a tendency to steer away from parts that are really hard. These are often, as risk-perception researcher Paul Slovic says, the indirect consequences of unexpected events.

Some models assume that agriculture can tolerate temperature swings of 30.6F above and below historical levels, or that it is easy for farmers to adjust to warming by modifying tilling, irrigation, planting and harvesting decisions.

The result is a neat-looking package on what is reasonable to spend to control emissions. One used by the US government gave its blessing to spending $42 in 2020 to eliminate a metric ton of carbon dioxide and $69 for 2050. Meanwhile, the last time carbon emissions were as high as they are now, dinosaurs roamed the Earth. There are actually economists whose math advises us not to worry about climate change because the US will benefit (in part because most people prefer warm to cold weather). Or that ocean acidification is OK because a massive extinction of marine life will likely occur over many generations of people who will increasingly grow up without experiencing what has been lost.

When models steer the climate conversation, it inverts priorities in two ways: it allows the modelers to decide which climate damages are important and which are not – and how to value them. And it diverts attention from the real issue – what level of risk we are willing to tolerate. But there are other ways to formulate policy.

One was offered by 11 retired admirals and generals who advise that climate change “should be addressed now because [it] will almost certainly get worse if we delay.” Policy rooted in risk would balance math with unfiltered science, arguing for acting now and spending more. It would front-load the response rather than leave it to future generations. After all, it is hard to see how anyone down the road might replace the Greenland ice sheet once it’s melted.

We think about risk every day when we consider crossing a busy street or purchasing insurance against the outside chance of being hit by disease or a devastating fire – all risks we can easily imagine. A risk approach for climate policy would put front and center the science telling us that humans are releasing carbon at a rate unprecedented during the past 66m years with “unforeseeable” changes to the earth on the horizon rather than instant-gratification-based policymaking.

Another, better approach to climate change is to recognize that there is no single answer. Numbers provide clues, but it is critical to understand where they came from. Facing the existential threat of climate change, humanity and policymakers cannot afford simplistic answers, developed in defiance of scientific truths. We must always question the numbers before us.