Seth's Blog

The best argument I have ever seen against the idea that humans are dangerously warming the earth — that is, against the view of Al Gore, Elizabeth Kolbert, and thousands of other people who claim to understand what they are talking about — comes, strangely enough, from a supporter of this view.

Steve Connor is the Science Editor of The Independent, a highbrow London newspaper. He interviewed Freeman Dyson — who, like me, thinks the conventional certainty on this issue is far too strong — on the subject. The headline of the interview labels Dyson a “heretic”. Connor wants to know how Dyson reacts to what seems to Connor to be overwhelming evidence.

The interview is by email. Dyson says he has no faith in the models. Connor writes:

I was only trying to find out where your problem lies with respect to the scientific consensus on global warming. As you know these models [that Dyson doesn't believe] are used by large, prestigious science organizations such as NASA, NOAA and the Met Office, which use them to make pretty accurate predictions about the weather every day. The scientists who handle these models point out that they can accurately match up the computer predictions to real climatic trends in the past, and that it is only when they add CO2 influences to the models that they can explain recent global warming.

There it is. The scientists who use the weather models every day, who know them better than anyone else say that we should believe them because 1. They can fit “real climatic trends in the past”. This is meaningless. The models have lots of adjustable parameters. Perhaps they could have fit any plausible past trends. 2. They “make pretty accurate predictions about the weather every day” — that is, predictions of the weather of the next week or so.

This is admission of defeat. It’s as if you say you can throw a ball a mile and, when someone asks how you know this, you say, “I’ve thrown a ball 10 yards quite often.” If you had thrown a ball more than 10 yards you would have said so. If the models had predicted accurately more than a week in advance their boosters would have said so.

It isn’t just Steve Connor who unintentionally makes a really good case for the opposite of what he believes. Sir Paul Nurse, a Nobel Prize winner in Biology and President of the Royal Society, hosted a recent BBC show called Science Under Attack in which we were supposed to believe predictions of global catastrophe because weather models can predict the weather for the next few days. A NASA weather expert said that! Nurse took him seriously.

My goodness. If the President of the Royal Society is this credulous, what are the ordinary members like?

In a comment on my last post, Sean Estey described a study of Baltimore shipyard workers, some of whom handled radioactive materials. The ones exposed to more radiation were healthier than those exposed to less. The difference in death rate was huge: 25%. This is so large and consistent with other data I doubt it is due to a confounding.

You can read more about this study here and here. If one quarter of all deaths are due to suboptimal stimulation of repair systems, that’s extraordinary news. The study was finished around 1990. The plausibility of such a large benefit should have led to experiments. The observation that people in mountain states (such as Colorado) have less cancer than those in gulf states (such as Alabama) as well as greater radiation exposure suggested to John Cameron, a professor of toxicology, an experiment in which some gulf state residents are exposed to enough radiation to bring their total exposure up to what mountain state residents receive. This has yet to be done.

In a paper about the effects of low-dose radiation, the authors say we should ignore the Baltimore study because of “the healthy worker” effect — the possibility that persons in one exposure group were healthier than those in another exposure group because workers are healthier than non-workers (and fitness for work may have differed between the exposure groups in the Baltimore study). They give three examples to illustrate the healthy worker effect. In these examples, a group in which everyone has a particular job were healthier than the general public, which includes many people without a job. In their examples, the median effect of being in the  full-employment group (in which everyone has a job) is a 10% decrease in mortality compared to the general-public group (in which some people don’t have a job because of disability). That should give a good idea of the maximum size of the healthy worker effect — when something is explicitly varied, that’s what happens. The Baltimore study compares person with job to person with job, not person with job to person without job. This suggests that in the Baltimore study, the healthy worker effect was smaller than the effect in the examples, meaning smaller than a 10% reduction. Such an effect cannot explain a 25% reduction.

A comment by Alrenous on my earlier post linked to a 2007 study of people in Taiwan whose apartment building was accidentally contaminated with radioactive materials. By the time of data collection, they had gotten far less cancer (3% of what would have been expected) than the general Taiwan population. A healthy worker effect cannot explain this. Again, the reduction is so great it is unlikely to be due to confounding.
If I could buy something to put under my bed that would expose me to the level of radiation received by people in Colorado, I would.

Yesterday I learned that you can get your gmail email automatically translated. As a professor at a Chinese university, I get a lot of email in Chinese. This gmail feature — which you can find under Labs — is wonderful!

He studied umami tastes, most of them having to do with aging or fermentation . . .

From this article. As regular readers of this blog know, I believe we like umami flavors — and sour flavors and complex flavors — so that we will eat microbe-laden food, which is essential for health.

Thanks to Tom George.

In this excellent article, Joshua Foer describes how he got really good at competitive memory tests, such as remembering the order of a deck of cards. He competed in the national championships.

Foer writes a lot about using “memory palaces” to remember stuff. You take a familiar building or neighborhood and vividly imagine what you want to remember at different places within it. To retrieve the memories, you mentally visit each place.

This is an ancient and famous method. I knew about it but had not realized until I read the article that it sheds light on my discovery that treadmill walking makes learning Chinese pleasant. (A commenter named Tom also noticed the connection.) Foer gives the obvious evolutionary explanation for why the memory palace method works so well: long ago, we needed to remember where to find important stuff (water, food, special plants, useful materials). So we evolved a memory system well-suited for doing so.

Less obvious is another evolutionary idea: why stop there? It’s a system. When you design a car for a certain sort of driving, you don’t stop with the engine. You adjust the drive train, the tires, and so on. If evolution shaped our brains for a certain sort of data (things in places), surely it also shaped our brains to collect that data. Pointless to design a car no one drives.

Two more changes would help make use of the system:

1. Hedonic. Make it pleasant to fill the system with data. This is what I noticed — dry knowledge (such as the order of cards in a deck) became pleasant to learn. Long ago, the hedonic change I noticed would have pushed people to walk in new places rather than old ones.

2. Efficiency.  Make learning more efficient (= more learning per unit time). Several confounded comparisons point in this direction. For example, I found that 15 minutes studying flashcards while riding the subway was a lot less help than spending 15 minutes while walking on my treadmill. Of course there are many differences between the two situations. Likewise, using Anki is working much better now than in the past, when I used it sitting down. I will try to study this more carefully.

Years ago, evolutionary explanations such as these were mocked as “just so stories” by prominent scientists, such as Stephen Jay Gould, Noam Chomsky, and Richard Lewontin. It’s now clear they were wrong.