First, in scientific coding, one of the big challenges is in reproducing the results of a program that uses random numbers. A classic solution is to use a deterministic pseudo-random number generator that can be seeded, such that if it's seeded with the same number on two different runs, it will always generate the same output. This could be a great replacement for that, since you could write a rand() routine that accepts a start point in the chain and traverses forward to output random values on demand.
Second, you could use this as a source of future randomness -- for example, I will award you $x if the next eight bits out of the random generator represent 0-127, and will award the $x to me if they represent 128 or greater. We can both check the value, and we don't have to trust each other.
The caveat with the last example is that we both have to trust that NIST has not been compromised ...
The anti-use would be in any sort of cryptographic implementation, since any "entropy" you'd be gaining by using this data as a source of randomness is completely counteracted by the fact that the source is known. Randomness becomes deterministic once the source of the randomness is disclosed and broadcast ...