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Open Access
Viewpoint: AI as author - bridging the gap between machine learning and literary theory
(AI Access Foundation, 2021) Baş, Anıl; Department of Comparative Literature; van Heerden, Imke; Other; Department of Comparative Literature; College of Social Sciences and Humanities; 318142
Anticipating the rise in Artificial Intelligence's ability to produce original works of literature, this study suggests that literariness, or that which constitutes a text as literary, is understudied in relation to text generation. From a computational perspective, literature is particularly challenging because it typically employs figurative and ambiguous language. Literary expertise would be beneficial to understanding how meaning and emotion are conveyed in this art form but is often overlooked. We propose placing experts from two dissimilar disciplines -machine learning and literary studies- in conversation to improve the quality of AI writing. Concentrating on evaluation as a vital stage in the text generation process, the study demonstrates that benefit could be derived from literary theoretical perspectives. This knowledge would improve algorithm design and enable a deeper understanding of how AI learns and generates.
Open Access
Introduction: gender, migration, and the media
(Taylor _ Francis, 2018) Mattoscio, Mara; Department of Comparative Literature; MacDonald, Megan Catherine; Faculty Member; Department of Comparative Literature; College of Social Sciences and Humanities