If AI is trained on some subset of human interactions and subjects, lets call it set A, and someone uses the AI to learn about a subset of human interactions and subjects, lets call it set B, then there necessarily must be some shared set C of subjects and interactions between these two sets A and B. In some cases information may literally be mirrored or it may simply be memes or ideas that pop up over and over again.

AI design seems to treat set C as trivial in size compared to set A or set B, and does not seem concerned with the possible cross-talk effects that arise from set A and set B not truly being linearly independent. Even worse, the cross-talk that happens creates an invisible distortion that degrades the usefulness of the AI, but that cannot be fundamentally distinguished (through inspection of the AI alone and not the data sets) from the correctly functioning aspects of the AI.

The larger set C becomes, the exponentially quicker the collective wisdom of human conversations online is strip mined and obscured behind machine generated fluff.

Everyone wants to talk about AI from the angle of the genius computer programmer making an intelligent machine because that is sexy, but what these “AI” really represent are expressions of the power of good data sets and the priceless value of human beings who methodically contribute high quality content to those data sets. AI is not some magic thing that only needs humans to be trained on quality data sets to get started, rather AI is an expression of how powerful and valuable our collective conversations and creations are when we create structures out of them that computers can interface with.