By "pseudo-randomness" I mean the usage of deterministic algorithms which are thought, on the short term anyway, to produce a stream of output that's indistinguishable from truly #random noise generated by some physical process. There are numerous methods in #programming for generating what looks like uniformly distributed "random" numbers, but which are in fact generating a predictable sequence with an extremely long period, such that using the pseudo-random numbers generated by such a technique is thought to be indistinguishable from physically generated randomness.

Does that all sound just a bit uncertain and hand-wavy? It should. The question of what "randomness" really is, and how one can gauge the quality of pseudo-randomness vs. the real thing generated by a physical process—these are not settled questions, and thus one should immediately be on guard against any claims made by overeager #computing people who want to act as though this is all a boring settled problem, something out of a textbook. That sort of easily bored computer geek just wants to throw prefab algorithms together on a server bank and hopefully make money thereby.

One can at least say with tolerable certainty that there are exceptionally bad methods of pseudo-random number generation, methods so bad that the resulting numbers, while still looking "random" at a naïve glance or passing basic frequency tests, are actually very specifically distributed throughout the space of all possible values. "Pseudo-randomness" can in fact conceal a great deal of predictability.

I'd very much like to know how big of a problem this is, in #programming. And here's where I'll be blunt: thanks to capitalism and broken methods of U.S. #education, I do not trust the average computer programmer to have thought about such problems at all. Corporation and corporate #tech companies generally don't want computer professionals who worry over fundamental weaknesses and pitfalls of their field; they want people whom they can plug into a management hierarchy, people programmed to do a limited range of expected duties.

Programmers have been acculturated in such as a way as to encourage a kind of slack-jawed amazement at the purported limitlessness of what their machines can achieve, and thus they have fled from acknowledging that modern #computers actually have some serious issues when it comes to representing numbers and doing #mathematics. There's been such a massive overemphasis on pure speed and bulk of computation that issues with accuracy and cumulative error in calculations have been swept aside, assumed to be taken care of with the proper #software—and yet all our software and its development is in the custody of people who are culturally disinclined to want to think about such problems.

Let's be honest here: today's top-flight #programming people have been schooled to fret over some very strange non-issues. They have a very poor sense of priority, which is partly why they've gotten so political lately: the #technology elite seem to think that their machines are already so perfect and wonderful and amazeballs that the real problem with computers is that humanity is too stupid to use them.