Textual Alchemy: AI, Authorship and the Shifting Paradigms of Interpretation

Artificial intelligence is overhauling the publication and textual production. Textual production with Large Language Models (LLMs) is more sophisticated and closer to human knowledge production thanks to its autoregressive nature. AI models by OpenAI such as the Generative Pre-trained Transformer 3 (GPT-3) and its iterations use deep learning to produce more human-like text. Such texts invite all kinds of problems that are not new to the human text-production system. Research shows that the output of such models tends to be biased towards a particular gender, race and ethnicity. This paper explores substantial texts produced by AI including articles, fiction, columns, opinion pieces etc. published in major journals and magazines to understand the nuances of such texts. Moreover, the paper will attempt to understand such features of AI-generated text by presenting the results of a particular set of instructions (prompt) to the LLM. These text outputs will be studied to demonstrate how AI-generated texts pave the way for a "postpost author" era, echoing Barthes' notion of the "Death of the Author". The scope, usability and limitations of the AI's textual production will also be investigated.