Over at Karmatics, Rob Brown thinks the counter-intuitiveness of natural selection is a big reason why people find evolution difficult to comprehend. In that way, natural selection is similar to prediction markets, where people bet on the chances of future events, such as the outcomes of sports events or political elections:
Prediction markets turn out to be remarkably accurate, typically more accurate than any individual expert can predict, as non-intuitive as it may seem. Like Wikipedia, prediction markets also tap into the power of selection, but the most dramatic similarity they share with evolution is their equilibrium seeking behavior.
Imagine that lots of random people come in and make bad guesses at who will win the election. The price of the contracts will then vary significantly from what the best expert would predict, resulting in an unstable (i.e. non-equilibrium) situation. Now all it takes to make some easy money is to consult with such an expert and buy the contracts whose prices are the furthest from the experts’ estimates. If it is indeed this easy to make money, the market will attract lots of people, including institutional investors who have the ability to invest enough to quickly move the price back to where the experts predict. Meanwhile, those experts who consistently predict badly will tend to eventually pick another line of work which they are better at, while those who are best at picking will make lots of money doing so, and will therefore tend to be there with cash in hand whenever the prices stray far from their predictions. Each expert tends to gravitate toward the specific things that they might have special expertise (or inside information!) on and therefore has the best chance of out-predicting the other experts. Over time, it becomes harder and harder to consistently outguess the market, no matter how good you are.
As much as this may make logical sense, this sort of equilibrium-seeking process is exceptionally difficult to directly observe. All we can look at is the individual transactions, but we can’t see all the people who might have been attracted to a particular contract had they thought that it would be relatively easy to make money. And we can’t directly see the statistical pressures that are constantly keeping the prices at a stable equilibrium.
Evolution, of course, has similar equilibrium-seeking behavior. Imagine an animal that, were its earlobes shaped slightly differently, would be ever so slightly better able to hear the sounds made by potential prey. No matter how long you watch such animals, you would be hard pressed to find an actual situation where that subtle change would mean the difference between life and death. But as long as there is a statistical difference, a suboptimal earlobe is an unstable situation, waiting to be corrected. And, typically it will be, in surprisingly short order. The cumulative effect, of course, is what we see around us in nature: an absolutely breathtaking degree of adaptation in planet Earth’s life forms.
Such equilibrium-seeking behavior, whether in markets or in evolution, seems to defy intuition. The problem is that when you look closely, at the level that human observation works the best, all that is visible is a whole lot of slop. It is only when you step back far enough to see things from a statistical point of view does the true precision of the process come into view. Clearly, this is very, very hard for many — if not most — people to do.
Rob is right in that part of the problem is that a mathematical perspective is needed: in its most reductionist form, evolution is the change in gene frequencies through time. Any time you read “the change in [x] through time” that means you’ve entered the Dreaded Land of Math That Uses Letters: dx/dt. While I’ve never bought into the idea that a discipline ‘teaches students how to think’, in this case, mathematics is very helpful. Through in a couple of natural logarithms and you can basically understand much of population genetics theory–never mind natural selection.
On the other hand, there is another issue I’ve encountered. A fair number of people do ‘get’ the change in gene frequencies–how dark snails replace light ones. What is far more difficult for some people is visualizing how very different forms can have a common ancestor. The problem isn’t mathematical, but based on a lack of natural history. The irony is it can be easier to explain natural history in the abstract as opposed to explaining an actual evolutionary sequence. In other words, how do the structures in a mousey-looking mammal ultimately lead to the staggering diversity of modern day mammals?
It’s not that there aren’t many examples that could be used–despite the creationists claims to the contrary, there are plenty of intermediate forms in the fossil record. As the evo-devo field becomes more explored, I think we’ll also have better models to explain the genetic basis of evolution of macroevolutionary pattern. But the ‘natural history deficit’ is not trivial. While many people freak out when expected to think mathematically, biologists, including Mad ones, sometimes forget that introductory biology requires learning more new words than introductory French. The natural history can be just as intimidating, so we need a couple of really examples of evolutionary change of form that are easy to grasp (got any suggestions? Particularly if you’re not a biologist).
Granted this won’t change any creationists’ minds, but for those on the fence, it might be useful.