I agree it is not exactly the same as a human, but the content it produces is based on its specific training data, how it was fed the training data, how long it was trained, the size and shape of the network, etc. These are unique characteristics of a model that directly impact what it produces. A model could have a unique proclivity for using specific groups of words, for example.

But yes, you could break the discriminator model, in the same way people disguise their own writing patterns by using synonyms, making different grammar/syntax choices, etc. Building a better evader and building a better detector is an eternal cat and mouse game, but it doesn't reduce the need to participate in this game.