Good article. I liked the points made, especially the comparison to continuous variables. The argument about "true" randomness versus psuedo-randomness is very

Good article. I liked the points made, especially the comparison to continuous variables. The argument about "true" randomness versus psuedo-randomness is very interesting. As the dilbert comment posted elsewhere points out, it's impossible to really know how "random" something is, because if it matches your expectations, then it isn't. So it's hard even to compare "true" random number generators and psuedo-ones. You might even argue that PRNGs are better in some cases because you can make provable statements about the distribution of their output. (Of course, those statements might depend on the seed being "random"....) Anyway, I guess the takeaway is that, as the author says, randomness is poorly understood; instead, we can only make statements about random numbers and probabilities and do our best to reconcile those with what we have to work with in real life. This seems like poor comfort to academics who rely on some formal notion of randomness that is unachievable, but on the other hand randomness seems to always work "well enough" in practice.....