CONCEPT
Quality Assurance for AI-Mediated Work
The institutional challenge of evaluating substance rather than surface in a production environment where polished output is structurally independent of underlying comprehension.
Quality assurance for AI-mediated work names the institutional design problem of building evaluation systems that penetrate the smooth surface of machine-generated output to assess the comprehension beneath. The historical precedent is the editorial function in publishing, which evaluated manuscripts for substantive quality rather than surface polish. An editor at a reputable press in the seventeenth century did not merely check that the text was legible; she evaluated the argument, assessed evidence, identified weaknesses, and determined whether the manuscript met a standard of quality that the press's reputation required. The AI equivalent must operate at scales orders of magnitude larger than its historical antecedent.
In The You On AI Field Guide
The most dangerous feature of AI-generated work is the independence of its surface quality from its substantive quality. The code compiles regardless of whether its author understands the architecture. The legal brief cites relevant precedent regardless of whether its author has read the cases. The medical recommendation follows clinical logic regardless of whether the requester can evaluate