| > They find, time and time again, in all sorts of fields, that extremely parsimonious models like equal-weighted linear regression of one or two predictors outperform expert judgment. I came across this in Thinking Fast and Slow. Kahneman was a big fan of Meehl and restates the point: The important conclusion from this research is that an algorithm that is constructed on the back of an envelope is often good enough to compete with an optimally weighted formula, and certainly good enough to outdo expert judgment. https://www.goodreads.com/quotes/9574537-the-important-concl... I too agree with the premise of this article. On this topic of expert judgment vs data, however, I found the counterpoint in this HN comment thought-provoking enough to bookmark and refer back to now and again: I started at MS during Vista and I've been involved (sometimes tangentially) with Windows ever since. This is all my opinion, but It's been very interesting seeing the decision making process change over time. If I had to summarize the change, I'd say that it's evolved from an expertise-based system to a data based system. The reason why eight people were present at every planning meeting is because their expert opinion was the primary tool used in decision making. In addition to poor decisions, this had two very negative outcomes: 1) reputation was fiercely fought for. Individuals feared that if they were ever incorrect, the damage to their reputation would limit their ability to impact future decisions and eventually lead to career death. Whether this actually happened or not is irrelevant; the fear itself caused overt caution and consensus seeking. 2) In the absence of data, an eloquent negotiator is often able to obtain their desired outcome, no matter how sub-optimal that outcome might be. https://news.ycombinator.com/item?id=15174737#15176957 Even more provocative, it ends up being a (qualified, as I read it) defense of telemetry. |