I have written before (here) about the influence prior beliefs have on how people act. Two recent events (one lecture, one book) have led me to further contemplate this.
Daniella Witten, a biostatistician at UW, gave a bioethics lecture today on the Duke saga (her words) regarding genomics research and related clinical trials, and the consequent scandal when it turned out that the genomics science was not correct. Although statisticians led the discovery, they themselves did not use any Bayesian arguments–what follows are my own ramblings. One of the points that I got from Witten’s talk was that the very persistent reluctance for authorities at Duke (and elsewhere) to realize that the published papers were wrong came, at least partly, from their belief that it had to be correct. There had been such hype about the potential of genomics to guide cancer therapies, and the PI was a good scientist, and good journals accepted the papers. It took a lot of evidence before their prior probabilities were modified by data to the more correct posteriors.
This tale seems to me to be a good example of the type of thinking described by Jonathan Haidt in “The Righteous Mind: Why Good People are divided by Politics and Religion.” He uses the metaphor of an elephant with a rider on its back. The rider is the rationale mind whereas the elephant is everything else about us. More often than not, the rider doesn’t guide the elephant, but rather spends a lot of time justifying the direction the elephant is going in on its own volition. To stretch the analogy, I think that part of the elephant’s momentum (in the vector sense) has to do with prior beliefs, without saying where they came from. The rider is new data, and the inability of our rationale mind to change the elephant’s course reflects the difficulty we have in overcoming prior beliefs. One way of thinking of it is that the processes that guide our “elephant” multiply the importance or frequency of a few early data so that once that prior has been established, it takes an awful lot to influence it later.