textAuthor is a data-driven, artificial-intelligence (AI)-based text-authorship classifier. When trained on user-supplied text/author pairs, the classifier attempts to identify the authors of user-supplied texts (whose authorship may be unknown). This paper describes the implementation of textAuthor and shows an example of its use. The example trains the classifier on the full texts of two works written by each of seven authors. textAuthor then assesses who wrote each of a set of anonymized test cases (works) that are not in the training set of the example. With one interesting exception, the example correctly identifies the author of each of eight anonymized test cases.