A recent paper by the Department of Computer Science of Cornell University introduces a novel unsupervised method, titled Vec2Vec, that allows embeddings from different models to be mapped with high similarities despite variations in their architecture, size, or training data. This article discusses how this development challenges present notions of consent and data pseudonymization in…