Science and the Limits of Causation
In 2006, after a sudden shift in the outcomes of a promising drug, Pfizer’s market cap plummeted by $21 billion in a week. Stories like this are common in the pharmaceutical industry, only this one was different – this was not supposed to be a risky bet.
Science, claims Jonah Lehrer in a fascinating essay for Wired magazine, is failing us. Every year, nearly $100 billion is invested in biomedical research in the US. And increasingly, these dollars are yielding less and less useful returns. Lehrer believes that our reliance on the basic scientific principle of correlation — that this drug can effect that condition — may be entering a new phase:
“The reliance on correlations has entered an age of diminishing returns. At least two major factors contribute to this trend. First, all of the easy causes have been found, which means that scientists are now forced to search for ever-subtler correlations, mining that mountain of facts for the tiniest of associations. […] Second—and this is the biggy—searching for correlations is a terrible way of dealing with the primary subject of much modern research: those complex networks at the center of life.”
It’s a worthwhile essay for anyone interested in health research, big data and complex systems. We have, Lehrer says, constructed our $2.5 trillion dollar health care system around the belief that we can identify the underlying cause of illness. But causality has its limitations, and we may have found them.