Machines don’t read works or data. Machines need to first abstract and then format data for learning and then apply tagging and other metadata to model the data into something the machine can “understand.” Legal protections aren’t purpose-built to allow machines to abstract data from a work, process it, model it, and then re-present it. Most licenses aren’t purpose-built for that either. This document walks the reader through all the known protections and licenses as to whether they cover machine learning practices. It then postulates a proposed license structure for that purpose.