Studies in Translation, Vol. 5, No.1 , 2019 - 151 - Will the Machine Understand Literary Translation? A Glimpse into the Future of literary Machine Translation through the Lenses of Artificial Intelligence Mohammed Al-Batineh Yarmouk University m_bataineh@yu.edu.jo Reem Ibrahim Rabadi German Jordanian University Reem.rabadi@giu.edu.jo Abstract Studies on Machine Translation (MT) development have focused on producing MT systems that can translate general texts, news reports or government documents, and little attention has been paid to literary MT. The present paper reports the results of two experiments in an ongoing project aiming at developing a literary MT system. The first phase of the project, reported here, focuses on solving machine understanding problem. This phase attempts to reveal the extent to which the computer can understand translated literature, using Latent Semantic Analysis (LSA), an information retrieval technique that is applied to Natural Language (NL) understanding problems. LSA is used in the experiment as an automated method to conduct categorization and thematic similarity analysis of three hundred translated short stories from Arabic into English. The initial results show that the machine can understand the themes and concepts included in the translated short stories and can categorize the stories into groups depending on their shared themes or topics. Keywords: Machine Translation, Artificial Intelligence, Rule- based Machine Translation, Statistical Machine translation, Latent Semantic Analysis.