The paper discusses the dual-use concerns of natural language generation technology, highlighting how it can be exploited to create neural fake news that closely mimics real news. It introduces Grover, a model designed to both generate and detect such disinformation, demonstrating that the best defense against neural fake news might be strong public generators like Grover itself. The paper also explores the need for robust verification techniques and addresses ethical considerations in the public release of such technology.