Can Machines Mourn? A Functional and Thematic Analysis of Grief in AI-Generated and Human Fiction - Mamona Yasmin Khan; Maryam (Indus Journal of Social Sciences, 2025)
The present study offers a stylistic and function-oriented comparison of grief representation in human-authored and AI literature, focusing specifically on Cormac McCarthy’s The Road and Ross Goodwin’s 1 the Road. Based on Roman Jakobson’s functions of language and Alan Turing’s imitation framework, the work seeks to determine whether artificial narratives are capable of imitating emotionally affective mourning or grief expressions with similar functional and poetic depth to those in human literature. Adopting a corpus-based approach, the researchers have applied software tools e.g. spaCy, AntConc, and Voyant Tools for the analysis of affective vocabulary, sentence constructions, poetic modus operandi, and repeated phrase patterns. The analysis shows that, despite a superficial command of poetic techniques (e.g., metaphor, personification, and repetition), features of narrative coherence, psychical continuity, and symbolic characteristic of McCarthy’s human-authored novel are absent from the AI-generated text. The result is an instance of AI grief that is mimetically present, but structurally and emotionally empty, it meets Turing’s imitation requirement but does not express Jakobson’s emotive function. This outcome also points to the inability of AI as it currently stands to produce depth of experience and suggests larger conversations in post human literary theory, authorship, and computational aesthetics. The work provides important perspective on the emerging itineraries of artificial creativity and literary effect.