That paper is about the RNG and it sounds like the method that the 3D dice use is different (even if the RNG is involved to randomize starting parameters). That said, I'm pretty confident that they are 'fair dice'. I'm simply addressing the relevancy of the post about the RNG. Randomness is 'clumpy'. It doesn't ensure a smooth distribution. If it did than every roll of 6d6 should produce a total of 21 (because you have 1 1, 1 2, 1 3, etc...). Further more humans are pattern matching machines. We are hardwired to recognize patterns even when there are things in the way to break up that pattern. It's a feature of evolution as the monkeys that could see the tiger in the tall grass ran away and those that couldn't got et. That evolutionary pressure has led to lots of false positives, however. Basically it would be better for a monkey to run away from a tiger that wasn't there then it would be for a monkey to stick around when one was there. That's why you can see faces in the front of cars or the boles of trees and why when a person looks at clouds they can see different animals. So when the clumpiness of random numbers meets up with the human ability to see patterns you will get of these false identifications of patterns. This is where a fair number of things like 'lucky t-shirts' and the like come from. Probably a lot of lucky dice are similar, although it is possible for a die to be strongly biased as well. Which brings us to the last point that people often miss about PRNGs (pseudo-random number generators, which is probably what the RNG actually is). While it is possible for a die to be strongly biased it is impossible for a die to be totally unbiased. There will always be imperfections in the mixing and density of the resins, the precision of the shape, the carving of the numbers, etc. Any die subjected to enough rolls that are analyzed through statistical methods such as a Chi-squared test will eventually fail, even the dice used in Atlantic City casinos (which are a very simple shape and fairly rigidly controlled) will eventually fail because of micro-imperfections. What this means is that a PRNG doesn't have to be completely random. It just has to be 'random enough', and although nobody has done a statistical analysis of the 3D dice I am fairly comfortable in saying that the methods Kristin describes should produce dice that are probably more than 'random enough', especially with shapes such as D12's and D20's.