iAuthor

Abstract

This case study explores how large language models (LLMs), particularly GPT-3 and GPT-4, are transforming the nature of authorship, creativity, and the economics of writing. Drawing parallels with the revolutionary impact of the printing press, the text examines AI-generated outputs—from poetry to screenplay monologues—that rival traditional creative writing. It highlights growing concerns about authorship legitimacy, creative labor displacement, and ethical use of copyrighted material in AI training datasets. LLMs challenge notions of human uniqueness by simulating creativity through predictive recombination of vast textual corpora. Yet, unlike human writers, these models lack context, intention, and emotional experience. Their rise poses questions about inequality in data representation, inequity in knowledge access, and the dehumanization of writing labor. As AI-generated content proliferates across news, entertainment, and education, this case asks: Can machines create meaning—or only mimic it? And what do we lose when writing is decoupled from human voice and vulnerability? The case compels us to reckon with the socio-technical and moral implications of outsourcing intellectual labor to machines.