Both governments and corporations routinely surveil computer-mediated communication (CMC). Technologists often suggest widespread encryption as a defense mechanism, but CMC encryption schemes have historically faced significant usability and adoption problems. Here, we introduce a novel technique called Open Book designed to address these two problems. Inspired by how people deal with eavesdroppers offline, Open Book uses data mining and natural language processing to transform CMC messages into ones that are vaguer than the original. Specifically, we present: 1) a greedy Open Book algorithm that cloaks messages by transforming them to resemble the average Internet message; 2) an open-source, browser-based instantiation of it called Read Me, designed for Gmail; and, 3) a set of experiments showing that intended recipients can decode Open Book messages, but that unintended human- and machine-recipients cannot. Finally, we reflect on some open questions raised by this approach, such as recognizability and future side-channel attacks.