Climate Change and “Too Big” Polluters
Taleb argues that uncertainty about ecological harm supports precaution. He also proposes a pollution thought experiment in which dividing exposure can reduce harm, provided the dose-response curves are suitably convex and the substances do not interact harmfully.
THE IDEA
I have been asked frequently on how to deal with climate change in connection with the Black Swan idea and my work on decision making under opacity. The position I suggest should be based both on ignorance and on deference to the wisdom of Mother Nature, since it is older than us, hence wiser than us, and has been proven much smarter than scientists. We do not understand enough about Mother Nature to mess with her—and I do not trust the models used to forecast climate change. Simply, we are facing nonlinearities and magnifications of errors coming from the so-called butterfly effects we saw in Chapter 11, actually discovered by Lorenz using weather-forecasting models. Small changes in input, coming from measurement error, can lead to massively divergent projections—and that generously assumes that we have the right equations.
We have polluted for years, causing much damage to the environment, while the scientists currently making these complicated forecasting models were not sticking their necks out and trying to stop us from building these risks (they resemble those “risk experts” in the economic domain who fight the previous war)—these are the scientists now trying to impose the solutions on us. But the skepticism about models that I propose does not lead to the conclusions endorsed by anti-environmentalists and pro-market fundamentalists. Quite the contrary: we need to be hyper-conservationists ecologically, since we do not know what we are harming with now. That’s the sound policy under conditions of ignorance and epistemic opacity. To those who say “We have no proof that we are harming nature,” a sound response is “We have no proof that we are not harming nature, either;” the burden of the proof is not on the ecological conservationist, but on someone disrupting an old system. Furthermore we should not “try to correct” the harm done, as we may be creating another problem we do not know much about currently.
One practical solution I have come up with, based on the nonlinearities in the damage (under the assumption that harm increases disproportionately with the quantities released), and using the same mathematical reasoning that led to my opposing the “too big” concept, is to spread the damage across pollutants—should we need to pollute, of course. Let us carry on a thought experiment.
Case 1: You give the patient a dose of cyanide, hemlock, or some poisonous substance, assuming they are equally harmful—and assuming, for the case of this experiment, the absence of super-additivity (that is, no synergetic effects).
Case 2: You give the patient a tenth of a dose of each of ten such substances, for the same total amount of poison.
In this simplified model, Case 2 can cause less harm if each substance has a comparable convex dose-response curve over the relevant range and the substances have no harmful interactions. The reduction depends on those assumptions; spreading exposure alone does not establish that a mixture is safe or close to harmless.
When to use it
Examining whether an emissions policy accounts for the harm caused by each substance, its concentration and interactions.
Comparing industrial processes using evidence about the hazards of their wastes, rather than assuming a more varied mixture is safer.
Applying the precautionary principle to new technologies with unknown ecological impacts.
Debating climate policy by acknowledging model uncertainty and advocating for robust, conservative actions.
FROM THEORY TO EVERYDAY LIFE
In practice
Poison Spreading Thought Experiment
Case 1: A patient receives a full dose of one poisonous substance. Case 2: The same total amount is divided among ten substances, each at a tenth of the dose. Under the thought experiment’s assumptions of comparable convex harm curves and no harmful interactions, dividing the dose can reduce total harm. The example does not establish a general rule for chemical mixtures.
A MOMENT TO REFLECT
Put it to work.
What would you need to know about dose-response curves and interactions before applying this thought experiment to an environmental problem?
In what areas of your life do you assume models are accurate, and how might nonlinearities and unknown unknowns affect those assumptions?
Why might the burden of proof be placed on those who disrupt an old system rather than on those who wish to preserve it?
CONTINUE THE CONVERSATION
Source texts
- The Black Swan The Impact of the Highly Improbable With a new section On Robustness and Fragility (Nassim Nicholas Taleb)