The first really good image generators for faces (see for example https://this-person-does-not-exist.com ) used GANs, which were trained by having one model generate faces and another model saying bullshit, that isn't a face.

I'm not worried about using approaches like this to converge on truth (model A generates an answer to a question, model B attempts to refute model A). Perhaps we could train model A to generate lies that model B can't detect.