Monday, January 26, 2009

Development: A Basic Human Right?

The University of Ottawa's International Development Week is February 2nd to the 7th. Scheduled speakers are:
  • Feb.2: Alex Neve, Secretary General, Amnesty International Canada
  • Feb.3: Maude Barlow, Senior Advisor to the UN on questions of water
  • Feb.4: The Honorable Lloyd Axworthy, former Minister of Foreign Affairs
  • Feb.5: His Excellency S.M. Gavai, High Commissioner of India
  • Feb.6: Alexandre Trudeau, Journalist
  • Feb.7: Peter Levesque, Knowledge Mobilization Specialist
Contact or visit for more information.

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Sunday, January 11, 2009

Absence of evidence ...

In a valid deductive argument, the conclusions follow necessarily from the premises. This is a proof in the mathematical sense of the word. Provided we know that the premises are true, we can establish with complete certainty that the conclusions are true. For example, identifying a single unicorn would establish without a doubt that unicorns exist.

Unfortunately much of the time this type of certainty isn't possible. Consider another example from the realm of mythology: weapons of mass destruction (WMD) in Iraq. Here's what Donald Rumsfeld had to say on the subject in 2002 (the boldface is my addition):
There's another way to phrase that and that is that the absence of evidence is not evidence of absence. ... Simply because you do not have evidence that something exists does not mean that you have evidence that it doesn't exist.
But surely hunting high and low for WMD month after month and not finding any (absence of evidence) supports the inference that there aren't any there (evidence of absence). Indeed, it turns out that the popular maxim cited by Rumsfeld is simply incorrect.

But didn't he have a point? Absolutely: failing to prove that something exists does not prove that it does not exist. Or, in the words of the English writer William Cowper (1731-1800):
Absence of proof is not proof of absence
Compare this with the version invoked by Rumsfeld:
Absence of evidence is not evidence of absence
The originator of this maxim seems to be the cosmologist Martin Rees, although it has been attributed to many others, including Carl Sagan. By substituting the word evidence for proof it makes a much stronger (and invalid) claim. Evidence, after all, is often uncertain. If I look outside and see that the ground is wet, that is evidence that it has been raining. But perhaps my neighbour was watering her flowers. Seeing someone walk by with an umbrella folded under their arm might strengthen my evidence for the rain hypothesis, but perhaps they are anticipating rain later on. In general, evidence can support an inference, but it won't necessarily prove it. And that's where Rees's formulation of the maxim falls down.

Black and white thinking about evidence

When evidence is construed as being certainty, we get into all kinds of trouble. This is how Rumsfeld turned a simple truism (no WMDs have been found, but they might still be) into a puzzle of obfuscation (absence of evidence is not evidence of absence).

But Rumsfeld is not the only one. As I noted recently, the term "no evidence" is commonly used to describe situations where an effect is not found to be statistically significant. Now statisticians are wary of people concluding that a lack of statistical significance implies that there is "no effect". (It might be, for example, that the sample size was inadequate.) Hence, it is not at all uncommon for statisticians to declare that absence of evidence is not evidence of absence! As Kim Øyhus has pointed out, even the American Statistical Association buys into it, as the t-shirt they sell attests.

Of course statisticians know well that uncertainty isn't easy to think about or communicate to others. So why have we fallen into this trap?

Well, part of the reason may be philosophical. Statistical reasoning is inescapably inductive—it does not guarantee certainty. Philosophers have been worrying about what is called the problem of induction for a very long time. David Hume (1711-1776) challenged the logical foundations of induction, and ever since, philosophers have sought a way around the problem. The reigning "solution" is known as the hypothetico-deductive method, developed by philosopher of science Karl Popper (1902-1994). Popper argued that induction in science could be avoided by proposing a hypothesis and then seeking evidence that would either prove the hypothesis wrong ("falsify" it) or fail to do so. This is very similar to the frequentist statistical hypothesis testing framework that developed from the work of Fisher, Neyman, and Pearson. Unfortunately, it lends itself to black-and-white thinking. A hypothesis is either proven wrong or it isn't. There's no grey zone.

Popper's formulation, in particular, buries the uncertainty completely, construing the reasoning as entirely deductive. Suppose, for example, that a new biochemical theory predicts that a certain drug will shorten the duration of an illness, whereas the older theory does not. Now duration of illness depends on numerous factors, including differences in patients' immune systems, and we expect to see variation above and beyond any differences due to the drug. A clinical trial may demonstrate that the average duration of illness for patients who are randomly assigned the drug is shorter than that for patients who receive placebo, and that this difference is statistically significant at the 0.05 level. Has the older theory been proven incorrect? Not with absolute certainty. The evidence against it may be strong but it is possible that this is a "type-I" error—rejecting the null hypothesis even though it is true. Indeed, because of the way the statistical test has been designed, when the null hypothesis is true we expect to see such errors 5% of the time. The companion to the type-I error is the type-II error—failing to reject the null hypothesis even though it is false.

Pretending that type-I and -II errors don't exist is wishful thinking. Just as diagnostic tests produce false positives and false negatives, statistical hypothesis tests can give the wrong answer. The point is that we can study and control the error rates and make inferences while acknowledging their limitations.

It suited Donald Rumsfeld's purposes to be fuzzy about the distinction between evidence and proof. It doesn't suit ours.

Update 03-Jun-2009: I had originally attributed the maxim "Absence of evidence is not evidence of absence" to Carl Sagan in his 1995 book The Demon-Haunted World." Apparently however, the originator was cosmologist Martin Rees. There is reference to it in the proceedings of a 1972 symposium titled Life Beyond Earth & The Mind of Man [pdf], jointly sponsored by Boston University and NASA. In his introductory remarks, the chair, Richard Berendzen stated:
A generation ago almost all scientists would have argued, often "ex cathedra," that there probably is no other life in the universe beside what we know here on Earth. But as Martin Rees, the cosmologist, has succinctly put it, "absence of evidence is not evidence of absence." Beyond that, in the last decade or so the evidence, albeit circumstantial, has become large indeed, so large, in fact, that today many scientists, probably the majority, are convinced that extraterrestrial life surely must exist and possibly in enormous abdundance.
(The boldface is mine.) Note that Carl Sagan was one of the panelists at the symposium.

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