The big problem here is that what we’re dealing with is not risk, in which the probabilities can be reliably quantified, allowing an expected value to be computed, but uncertainty, in which they cannot.

As an example, a thirty percent chance of rain represents risk. “It might rain, or it might not, but we have no idea what the probability is” constitutes uncertainty. It’s much easier to decide whether or not to take an umbrella in the first circumstance than the second.

For this reason, economists have come up with a more sophisticated technique for decision making in the absence of probabilities of outcomes. Rather than simply looking for the lowest maximum cost, they instead try to minimize how bad you’ll feel if you make the wrong decision — they minimize “regret.”

It’s based on the notion that when you make a decision, you shouldn’t compare it to some unattainable ideal of zero cost; you should compare it to the best decision you could have possibly made under the circumstances, whatever they turn out to be. This eliminates the oversimplicity of the one-sided Pascal’s Wager.

Take a simple case — do you take an umbrella when it rains, or not?

Consider a classical game-theory cost matrix. The center columns are two potential states of the world, and the rows are the actions one can take. I’ve put in notional cost numbers simply to mathematically demonstrate the concept. For instance, there might be a higher cost of carrying an umbrella on a non-rainy day because of the increased risk of leaving it somewhere because you don’t need it. Note that we are not restricted to only two of either states or actions — there could be many more of each — I simply chose the simplest case for the purpose of illustration.

 State 1 (It Will Rain) State 2 (It Won’t) Maximum Cost Action 1(Take Umbrella) 3 4 4 Action 2 (Don’t) 5 0 5

It looks like we can minimize our maximum cost by choosing Action 1, since four is less than five. That is the so-called “minimax” solution. But is that really the right decision?

Let’s derive a “regret” matrix from it. This is done by finding the minimum cost for any state, and subtracting each cell of that state from it. The minimum cost for State 1 is 3, so the column would be three minus three for the first row (0) and five minus three (2) for the second row. That makes intuitive sense, since if you made the right decision for that state, you’ll have no regrets. The regret matrix for the example cost matrix is shown below:

 State 1 State 2 Maximum Regret Action 1 0 4 4 Action 2 2 0 2

Note now that if we want to minimize regret, we should actually choose Action 2. Note also that this is independent of the relative probabilities of the two states. The regret analysis clarifies the choices. It also, at least in this case, shows why we don’t carry umbrellas everywhere and when, unless we live in Seattle.

Assuming, of course, that we have the right numbers to put into the matrix. The problem is that, with the heretofore monomaniacal devotion to the flawed precautionary principle by the warm mongers, we haven’t even defined the rows and columns, let alone attempted to come up with the numbers.

Doing so would obviously be far beyond the scope of this brief essay, but I would suggest that there are at least four columns: the world is warming, the world is warming as a result of anthropogenic activities, the world is cooling, and the climate is varying up and down.

There are also at least four potential actions: slamming the brakes on carbon emissions, letting the market determine our energy choices, making plans for damage mitigation and remediation, and developing geoengineering means of global temperature control. Of course, there is a fifth choice: doing nothing (or rather, continuing on with our terrestrial affairs without regard to the future of the planetary climate).

That may be the best option, but there’s no way to know until we actually compare it to the others in an economically sensible way, which is to attempt to minimize how much regret we’ll feel if we end up, panicked, doing the wrong (some)thing. That should be the biggest precaution we want to take.