Ted Bunn’s Blog

Here’s the opening of an article in the New York Times:

In 2002 Responsible Travel became one of the first travel companies to offer customers the option of buying so-called carbon offsets to counter the planet-warming emissions generated by their airline flights.

But last month Responsible Travel canceled the program, saying that while it might help travelers feel virtuous, it was not helping to reduce global emissions. In fact, company officials said, it might even encourage some people to travel or consume more.

A bit later, we find

For Mr. Francis of Responsible Travel, the final straw came when he noticed that carbon offsets were being offered by private jet companies and helicopter tour operators, which generate very high emissions per passenger. “The message was, ‘Don’t worry, you can offset the emissions,’ ” he said. “But you don’t really need to see Sydney from the air, do you? And you can travel in a commercial airliner.”

Skepticism about carbon offsets is certainly warranted, mostly because it’s hard to verify whether the emission reduction being paid for is actually occurring.  But that’s not the objection being raised here: what the above seems to be saying is that regardless of whether the offsets work, they’re bad if they don’t cause people to fly less.  That’s nonsense.  If buying the offsets really does offset the carbon emission of flying, then it’s OK (from a carbon emission point of view) to buy the offsets and fly. In fact, not flying would then be no more “virtuous” than flying.

Let me be 100% clear about one thing: the “If” in that last paragraph is a big “If.”  It’s quite possible that offsets don’t work, in which case people shouldn’t use them.   In fact, that possibility seems quite likely to me.

What I’m objecting to (again) is the very common notion that even if things like offsets do work there’s something morally unsavory about them.  In fact, people quite often make the comparison with virtue and sin explicit, derisively referring to things like carbon offsets as “buying indulgences.”  Personally, I think that this attitude is unhelpful. When it comes to figuring out what to do about carbon emissions and climate change, all that matters is what works; there is no separate notion of “virtue” to be considered.

To be fair, the rest of the article does raise the real issues, suggesting doubt that the offsets currently on offer really do sufficiently reduce carbon emissions by the claimed amount, and claiming that ones that did do so would be priced much higher than those on offer.  I just wish we could have this discussion without mixing it all up with ill-considered moralizing.  For one thing, figuring out what works is a hard enough problem without that distraction.  For another thing, you may have noticed that people really don’t like being lectured to about their morals.  Casting the debate in simplistic moralizing terms is not likely to be politically effective, it seems to me.

My brother Andy pointed me to this climate science blog.  I don’t know much about climate science, but I do know about probability and data modeling, and I like the way this guy writes about them.  For instance, he has a really nice piece illustrating how you can model the climate at a variety of levels of complexity from very simple up to  massively complex simulations.  The point of this post is to debunk the notion, which seems to be widespread, that the only reason scientists believe in climate change is because of complicated black-box simulation codes.  He illustrates how  you can see the big picture very easily from much simpler models.

His most recent post is about his born-again Bayesianism.   It’s generally very sensible and worth reading, although I want to point out one important distinction that I think he blurs a bit.  The word Bayesian can describe two different (but overlapping) kinds of people:it can refer to

1. People who use a specific set of statistical techniques, or
2. People who have a certain philosophical stance about the meaning of probability.

Personally, I think that you absolutely have to be a Bayesian in the second sense of the term: the frequentist notion of probability strikes me as utterly incoherent.  But I think you should be completely agnostic as far as the first point is concerned.  Bayesian and frequentist statistical techniques are just tools.  They’re both perfectly sensible, and you should use whichever tool is more convenient for the problem you’re trying to solve at the moment.

I think that some people think that being a Bayesian in sense 2 means that you have to be a strict Bayesian in sense 1 — that is, that you can never calculate a confidence interval again.  Fortunately, it just isn’t so. For instance, I cowrote a paper quite a while ago in which we analyzed the same data set from both Bayesian and frequentist points of view to illustrate the relation between the two.

Governor Schwarzenegger sent a letter to the California assembly along with his veto of a recent bill.  The first letters of each line of the message spell out a certain vulgar phrase.  The Governor’s office says it’s a coincidence, but apparently lots of people don’t believe them.

This has a lot in common with the subject of a colloquium I gave here at the Université Paris last week.  (If you really want to, you can see the slides for this talk.)  My talk was about several unexpected patterns that have been observed in maps of the microwave background: there are a number of things that should, according to the standard theory, be random but that look non-random.  There’s a lot of controversy over whether these patterns are significant.  The problem is that after you’ve noticed a pattern, it’s very hard to quantify just how unlikely that pattern is, and hence whether it demands an explanation.

Human beings are really good at pattern-finding.  Maybe what we’re seeing is a chance fluctuation, and we’re just fooling ourselves into thinking it’s a pattern with an underlying cause.

The probability of this particular phrase being spelled out in this particular way in Schwarzenegger’s letter are something like one in a trillion.  But if you want to decide whether you think an explanation is required (i.e., that someone did it on purpose), that one-in-a-trillion number isn’t the right one to use: you should  try to figure the probability of something like this happening, rather than the probability of this particular thing happening.

Suppose that you read in the paper that Mary Jones won the lottery.  You’re not likely to be astonished by that fact, even though the probability of this particular person winning the lottery is very small. The reason is simple: the probability of someone winning the lottery is quite large.

So in the cases of both the microwave background and the vulgar acrostic, we should ask how unlikely is it that some similarly unusual pattern would show up.  The problem is that it’s very hard to phrase that question precisely enough that it has a meaningful answer.

So what should we do?  In Schwarzenegger’s case, we should get whatever juvenile amusement we can out of the situation, then decide that it just doesn’t matter and move on.  In the case of the microwave background, things are a bit different: if these patterns are real, then they may be telling us something scientifically very important.  So we should try to figure out new data sets that will shed light on the question.  Unfortunately, that’s hard to do.