I want to ruminate on a subject that has been of great interest to me for a number of years. To begin with, I will remind my readers about the difference between causation and association. I talked about this in the past. While this subject might not help you have an engaging conversation at your neighbor’s barbeque, it is absolutely central that we get this distinction right when analyzing data of any type – in chemistry, astronomy, medicine, etc.
Now let’s say we all got this distinction under our belts. In other words, we are really interested in causation more than anything else. Here comes the conundrum. The science of logic warns us of the following scenario:
In it, B is only an intermediate cause of the final outcome C, whereas A is the ultimate, all-important cause. A causes B and B causes C. I would bet that close to 99% of our failings in science must come from wild goose chases, in which we try to fix a given system by concentrating on the wrong variable. Here is a simple life example I read in a great book “Being Logical “ by D. Q. McInerny (http://www.amazon.ca/Being-Logical-Guide-Good-Thinking/dp/0812971159). Let’s say you notice that your kitchen stinks and the smell emanates from water accumulating underneath your sink. You are desperately trying to fix it by frequently emptying buckets of water, the problem seems to temporarily go away, but it always comes back… The reason? The flaw in your logic: the ultimate cause is the leaky pipe and you have not thought about it. Once you replace it, life goes back to normal.
Here is a chemistry example: you run a solution phase reaction on some peptide. Let’s say that your goal is to modify its N-terminus. Nothing works… You change a ton of coupling reagents and you get nowhere. This is frustrating, because you think that the issue lies in the low nucleophilicity of the N-terminus. But then, after some time, you find out that the real trouble is that that particular sequence is prone to aggregation, which of course affects reactivity. There is nothing that you can fix with a different coupling reagent, but a simple change of solvent miraculously solves the problem.
This is a simple example and, as you might imagine, there are substantially more complex cases out there. However, I think that the mistake in focusing on an intermediate cause is a clear and present danger in our research endeavors.