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I don't think I'm reading that post wrong! The original poster said " But I wonder if a die that large is even fair." Then the response said it's "fair enough

I don't think I'm reading that post wrong! The original poster said " But I wonder if a die that large is even fair." Then the response said it's "fair enough" because even if it only spins part of the way, you'll still get one of a group of dissimilar numbers. but that's not fair by the definition of what a fair die is. (it has a definition, if you search google you get "In mathematics we say 'fair dice' when we mean that there is an equally likely chance of landing on any face.") You're basically arguing that dice don't need to be fair. also you completely missed my jab at the NSA breaking RNG's while making them seem "random enough", i.e. getting to quite dissimilar next states while in fact having only a few possible next states.

Dylan16807 11y ago
It's "fair enough" because it gets the important parts right of having a large number of states. Just like your coin flip would get the important parts right if it was used in specific ways. A coin in the real world isn't fair, because it could land on its side. But it's fair enough. Statistical sampling doesn't give you guaranteed-accurate results. But the biases cancel out across the metrics you're measuring, so it's good enough. I didn't ignore your jab at the NSA, but it's pretty weak. The backdoored CSPRNG doesn't give numbers that are worse than any non-backdoored CSPRNG. Depending on your perspective, it can give you uniformly any number, or it can give you only a single number, and the same is true of good algorithms too.
- logicallee 11y ago
  I enjoyed this perspective and it changed my thinking, you've convinced me. It's also unlikely that humans can keep track of the distribution of 120 numbers on a die (in any distribution) so even if the game the cheater is playing is "Pick 20 numbers, then roll. If you roll any of the 20 you win" it is unlikely that they can remember what the die looks like well enough to cheat - except perhaps after massive effort. Fair enough :)

Dylan16807 11y ago

It's "fair enough" because it gets the important parts right of having a large number of states. Just like your coin flip would get the important parts right if it was used in specific ways. A coin in the real world isn't fair, because it could land on its side. But it's fair enough. Statistical sampling doesn't give you guaranteed-accurate results. But the biases cancel out across the metrics you're measuring, so it's good enough. I didn't ignore your jab at the NSA, but it's pretty weak. The backdoored CSPRNG doesn't give numbers that are worse than any non-backdoored CSPRNG. Depending on your perspective, it can give you uniformly any number, or it can give you only a single number, and the same is true of good algorithms too.

logicallee 11y ago
I enjoyed this perspective and it changed my thinking, you've convinced me. It's also unlikely that humans can keep track of the distribution of 120 numbers on a die (in any distribution) so even if the game the cheater is playing is "Pick 20 numbers, then roll. If you roll any of the 20 you win" it is unlikely that they can remember what the die looks like well enough to cheat - except perhaps after massive effort. Fair enough :)