AI and Authorship
AI and Authorship investigates how artificial intelligence is reshaping the concept of authorship. As AI tools like advanced language models contribute to writing, this project explores questions of creative agency and intellectual ownership. It looks at the blending of human and machine contributions in texts, challenging traditional ideas of a single author’s voice. Broadly, the goal is to understand how the rise of AI co-writers influences our definitions of author, originality, and literary value in the digital age.
The advent of artificial intelligence (AI), particularly Large Language Models (LLMs), is poised to bring about profound societal changes. Despite the risks associated with AI, such as the production of inaccurate information, labor market shifts, and the potential for AI to escape human control, ongoing regulatory efforts may not sufficiently curb its pervasive spread. The US federal government, in collaboration with key figures in the AI industry, has focused on the long-term risks of AI, without intending to stifle the industry’s growth. AI’s potential to automate aspects of writing implies that its inevitable introduction into educational settings will have immediate impacts on composition courses. Instances of students using AI tools like ChatGPT to write and submit assignments have been reported. Despite these concerns, universities are positioned to adapt to the changing environment and explore the potential benefits of AI in education. The relevance of AI writing technologies in language classes could be likened to the relevance of calculators in math classes 50 years ago, assisting humans with laborious aspects of writing. As Ted Underwood argues, AI demonstrates that writing takes place in “a multi-dimensional space in which a variety of writings, none of them original, blend and clash.” Over 50 years after Barthes’s “The Death of the Author,” we are confronted with “Death of an Author,” a work largely written by AI. Shakespeare’s work conveys the notion of artiginality, or ‘the workly character of the work,’ and after LLMs, it is compelling to understand artiginality in all forms of writings.
The relationship between Shakespeare’s First Folio and early printings, published in his lifetime, has been a matter of dispute for centuries. A computer program that I have developed visualizes the fluctuating quality of textual correspondences between Folio texts, Henry the Sixth, Part Two and Three, and texts that have been suspected as memorial reconstructions of the Folio, The First Part of the Contention and The True Tragedy of Richard Duke of York. The memorial reconstruction hypothesis assumes increased similarity between the two texts when an alleged actor–reporter is on the stage or speaking and vice versa. The visualization of similarity between two texts, based on the Dice similarity metric, does not show a strong association between the fluctuation of similarity and actor–reporter factors, which challenges the memorial reconstruction hypothesis on statistical grounds. In addition, the distribution of line-by-line similarity scores suggests scene division is a considerable explanatory factor for fluctuating similarity, which is not inexplicable, considering the practice of collaborative writing in the early modern playhouse.
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