Espen sez, "This is an excellent essay by Jonah Lehrer on the increasing difficulty of finding direct causation in medical (or, indeed, all) research. Highly readable, though I would have liked to see a little more about how to address this problem (i.e., with network analysis tools)."
David Hume referred to causality as “the cement of the universe.” He was being ironic, since he knew that this so-called cement was a hallucination, a tale we tell ourselves to make sense of events and observations. No matter how precisely we knew a given system, Hume realized, its underlying causes would always remain mysterious, shadowed by error bars and uncertainty. Although the scientific process tries to makes sense of problems by isolating every variable—imagining a blood vessel, say, if HDL alone were raised—reality doesn’t work like that. Instead, we live in a world in which everything is knotted together, an impregnable tangle of causes and effects. Even when a system is dissected into its basic parts, those parts are still influenced by a whirligig of forces we can’t understand or haven’t considered or don’t think matter. Hamlet was right: There really are more things in heaven and Earth than are dreamt of in our philosophy.
This doesn’t mean that nothing can be known or that every causal story is equally problematic. Some explanations clearly work better than others, which is why, thanks largely to improvements in public health, the average lifespan in the developed world continues to increase. (According to the Centers for Disease Control and Prevention, things like clean water and improved sanitation—and not necessarily advances in medical technology—accounted for at least 25 of the more than 30 years added to the lifespan of Americans during the 20th century.) Although our reliance on statistical correlations has strict constraints—which limit modern research—those correlations have still managed to identify many essential risk factors, such as smoking and bad diets.
Trials and Errors: Why Science Is Failing Us
