Source: SiliconANGLE
As AI systems train on user data with minimal transparency, companies are deliberately exploiting the gap between what consumers think is happening and what actually is—a calculable business model rather than a bug. This asymmetry holds until the first major lawsuit or regulatory intervention forces disclosure, at which point companies will scramble to either encrypt their training data or reframe consent language. The current moment is a narrow window for extracting maximum value from undisclosed data use. Profitable AI depends on users remaining confused about their role as unwitting training datasets.