The simple reason is because a pseudorandom number generator is a complexity theoretic thing, but an information theoretic thing. In order for it to be robust,

The simple reason is because a pseudorandom number generator is a complexity theoretic thing, but an information theoretic thing. In order for it to be robust, it must be indistinguishable from true random for any polynomial time algorithm. Since we have algorithms which can calculate Pi in polynomial time, as long as the computer recognized the sequence (or the deterministic seed of the sequence as Pi), it could with certainty predict the next digit of the sequence. As for why converting digits in this way matters - a lot of randomness is expressed by the entropy. It's harder for you to correctly guess the sequence {1,7,9,3,6,8,2,4} than it is to guess the sequence {1,1,1,1,0,0,0,0}. If I ask you to guess a decimal digit I've chosen "randomly", you have a 1/10 chance of being correct. If I ask you to do the same for binary digits, you have a 1/2 chance of being correct. Basically you want to think of these as subsequences, not individual numbers. If Pi is normal (which is a big if), then Pi is normal in every single base, including decimal or binary. But it's not generally true that a normal number generates another normal number by mapping each digit to the digit's parity.