Also the cognitive gap between a AI and a human brain has to grow and transform unpredictably in the next decades. We may be puzzled to understand how it "thinks" the same way we still don't get exactly how DNA operates.
It definitely will get harder for us to reason about what AI software is doing over time, but it's way too early to start comparing ML algorithms to the complexity of DNA. We may not understand exactly why a NN is using certain values to get the result, but we can reverse that logic through the use of debugging and logging.
The only "source code" are the learned network weights. These are the only parameters that describe the encryption function. You can still run the model forwards or backwards.
We already don't understand neural network weights on an intuitive level. No need to encrypt them. :-)