Ever-improving quality in MT makes it increasingly difficult for users to identify errors, sometimes obvious and other times subtle but treacherous, such as in patents and IP. Linguists, developers, and other “humans in the loop” should be ready to adapt their approaches to checking technical translations for accuracy. In this talk, real-world Chinese-to-English patent translations will be used in side-by-side comparisons of raw MT output and courtroom-ready products. The types of issues that can make or break a post-edited translation will be illustrated, with discussion of the principles underlying the error types. Certain nuances that challenge both humans and machines must be revealed in order to create a translation product that withstands the scrutiny of the attorneys, scientists, and inventors who might procure it. This talk will explore the nature of error detection and classification when reviewing patent texts translated by humans, computers, or a combination thereof.