“la formule qui décrypte le monde”
“It is only in the 1980s that the American mathematician Judea Pearl has shown that, by aligning hundreds of Bayes formulas, it was possible to take into account the multiple causes of a complex phenomenon.” (my translation)
As a curious coincidence, the latest issue of Science & Vie appeared on the day I was posting about Peter Coles’s warnings on scientific communication. The cover title of the magazine is the title of this post, The formula decrypting the World, and it is of course about… Bayes’ formula, no-one else’s!!! The major section (16 pages) in this French scientific vulgarization magazine is indeed dedicated to Bayesian statistics and even more Bayesian networks, with the usual stylistic excesses of journalism. As it happens, one of the journalists in charge of this issue came to discuss the topic with me a long while ago in Paris-Dauphine and I remember the experience as being not particularly pleasant since I had trouble communicating the ideas of Bayesian statistics in layman terms. In the end, this rather lengthy interview produced two quotes from me, one that could be mine (in connection with some sentences from Henri Poincaré) and another that is definitely apocryphal (yes, indeed, the one above! I am adamant I could not have mentioned Judea Pearl, whose work I am not familiar with, and even less this bizarre image of hundreds of Bayes’ theorems… Presumably, this got mixed up with a quote from another interviewed Bayesian. The same misquoting occurred for my friend Jean-Michel Marin!).
Among the illustrations selected in the journal as vignettes, the Monty Hall paradox—which is an exercise in conditioning, not in statistical reasoning!—, signal processing for microscope images, Bayesian networks for robots, population genetics (and the return of the musk ox!), stellar cloud formation, tsunami prediction, microarray analysis, climate meta-analysis (with a quote from Noel Cressie), post-Higgs particle physics, ESP studies invalidation by Wagenmakers (missing the fact that the reply by Bern, Utts, and Johnson is equally Bayesian), quantum physics. From a more remote perspective, those are scientific studies using Bayesian statistics to establish important and novel results. However, it would have been easy to come up with equally important and novel results demonstrated via classical non-Bayesian approaches, such as exhibiting the Higgs boson. Now, I understand the difficulty in conveying to the layman the difference resulting from using a Bayesian reasoning to support a scientific argument, however this accumulation of superlatives opens the door to suspicions of bias and truncated perspectives… The second half of the report is less about statistics and more about psychology and learning, expanding on the notion that the brain operates in ways similar to Bayesian learning and networks.
“Bayes’ little formula went a long way from the dusty statistical chapter where it had been relegated. By unveiling the sesame of the way our thought process operates, it promises nothing less than to reveal the secret that defines humanity.” (my translation)
What somehow annoys me with this kind of coverage is that it is excessive and therefore a-scientific in this excess: “revolution”, “harvest of discoveries and inventions”, “the formula that decrypts every mystery of Nature”, “the formula of thinking in action”, “a staggering efficiency”, “a miraculous tool”, “a magic formula”, “the Bayesian tsunami”, &tc. While I do think that a Bayesian approach to statistical issues is both more efficient and more coherent, I would certainly not engage in this kind of discourse, simply because it sounds sectarian rather than rational (and furthermore because Bayesians have been charged quite a lot with indulging in this kind of behaviour!). Now, some of the arguments reported in the text are quite convincing for me, like the inclusion of subjective beliefs and the ability to weight models and theories. Overall, it provides an entry to newbies into a field and stresses the appeal of a statistical tool in scientific induction, a tool so often missing from the toolbox of many scientists. Still, I feel uneasy about the global message transmitted by the journal. making Bayes’ formula sounding too much like a formula from Harry Potter!!!