Jul 2026· International Journal of Creative and Open Research in Engineering and Management· 0 citations
TL;DR
This paper argues that AI-generated literature does not so much destroy literary authenticity as force a reconfiguration of what the term has always meant, and concludes that a more defensible, procedural model of authenticity is emerging one grounded in disclosed, traceable human judgment rather than the simple fact of a byline.
Abstract
For most of literary history, the question of who wrote a text carried an assumption so obvious it rarely needed stating: a person did. The fluency of contemporary large language models has unsettled that assumption, producing sonnets, short stories, and novel chapters that readers in controlled studies frequently cannot distinguish from human-authored work. This paper argues that AI-generated literature does not so much destroy literary authenticity as force a reconfiguration of what the term has always meant. Synthesizing literary theory, empirical reception research, copyright law, and consumer psychology, the paper traces four converging lines of evidence: readers judged blind often cannot detect machine authorship and sometimes rate it more favorably, yet the same readers penalize a text emotionally once its AI origin is disclosed; structural analyses show AI-generated fiction and poetry remain measurably less inventive than the best human work even when formally polished; and copyright authorities have sidestepped the detection problem entirely by anchoring protection to traceable human decision-making rather than textual quality. Revisiting Roland Barthes's "death of the author" alongside a 2016 case in which an AI-assisted novella nearly won a Japanese literary prize, the paper argues that authenticity was never a property readers detected inside a text but a social practice negotiated among readers, critics, publishers, and legal institutions. It concludes that a more defensible, procedural model of authenticity is emerging one grounded in disclosed, traceable human judgment rather than the simple fact of a byline.
Keywords : AI-generated literature; authorship; authenticity; large language models; Roland Barthes; computational creativity; copyright law; literary reception studies
The emergence of large language models and generative artificial intelligence has introduced a profound disruption to the literary ecosystem. This paper examines how AI-generated literature threatens to displace human authorship, suppress the creative voices of writers, and destabilise the ethical and commercial foundations of literary production. Drawing on contemporary research in cognitive psychology, digital humanities, and publishing industry data, the study investigates three core concerns, namely the erosion of the writer’s creative agency, the commodification of literary output, and the philosophical crisis of intentionality and authorship in the age of machine-generated text. The paper argues that while AI presents utilitarian value as an assistive tool, its unregulated deployment as an independent author constitutes a threat not only to individual writers but to the cultural and intellectual vitality of society at large.
Sri Takshara· International Journal For Mu...· 0 citations
The work argues that autoethnography functions not merely as a qualitative method but as a phenomenological mode of being and knowing that safeguards the primacy of anthropic subjectivity against machinic imitation.
The study contributes a cautious comparative framework for distinguishing prompt-induced structural conformity from analytically emergent features in AI-generated narrative.
Artists and cultural theorists, although they use dif ferent means, share the task of problematizing culture. The urgent task now is to critically examine the ways we use AI text-to-image generators and create space for ref lection about engaging with these systems. I approach this through what I term the cultural logic of computational capitalism, drawing on Fredric Jameson and Bernard Stiegler. The paper addresses how arts and humanities can help overcome this logic and transform AI’s visual culture itself. Such an inquiry is essential given that AI text-to-image generators not only disrupt traditional art production but also concentrate creative power in the hands of a few dominant platforms. While these concerns are global, they require specific regional responses. Focusing on East-Central European countries, I argue that the underrepresentation of their visual cultures in AI models stems from their semi-peripheral status within global technological and economic systems. Rather than simply feeding existing AI models with better regional training data, I propose supporting dissident artistic practices that promote regional digital and digitally sustainable cultures.
This paper argues that generative artificial intelligence constitutes a media condition that cannot be reduced to technological reproduction or technological editing. Whereas reproduction distributed identical copies and editing dynamically rearranged existing data, technological generation organizes knowledge through an asymmetrical interaction between a human agent, who sets purposes and bears judgment and responsibility, and a generative system, which produces outputs conditionally from learned statistical distributions.
The paper examines this transformation through the categories of memory, impulse, and value. First, drawing on Bernard Stiegler’s theory of tertiary retention, it defines the dialogic reconfiguration of memory not as an exchange between two equivalent memories but as a relational transformation of human memory triggered by probabilistic machine output. Second, it reconstructs Friedrich Schiller’s play drive as an emergent impulse composed of a generative motive and a resonant motive. Third, it reworks Walter Benjamin’s aura into Artura, a relational and processual form of aesthetic presence grounded in relational originality rather than in the material presence of an original.
Artura is distinguished from digital aura, synthetic or postdigital aura, and the algorithmic sublime. Its distinctive explanatory power lies in identifying when traces of a generative process become legible, produce interpretive friction, and reorganize a viewer’s memory, sensation, and judgment. This distinction also clarifies the difference between participatory Artura, which may arise within the process of generation, and receptive Artura, which may arise for viewers who did not participate in that process. A limited analysis of Refik Anadol’s Unsupervised-Machine Hallucinations-MoMA demonstrates that immersive spectacle or algorithmic awe alone does not constitute Artura. Artura emerges only when generative conditions are critically apprehended and transformed into a new constellation of judgment.
The paper concludes that media aesthetics in the age of technological generation should analyze not only generated artifacts but also the asymmetrical relations, visible frictions, and human responsibilities through which those artifacts are produced and received.
Yong-wook Lee· The Korean Language and Lite...· 0 citations
Only several years after their introduction, generative AI-based image generation tools like Midjourney, DALL-E, or Stable Diffusion became an integral component in the routine design process of graphic designers, raising anew an age-old question: who authors a graphic work, and what is its originality? This paper is a conceptual and critical synthesis of relevant literature rather than an empirical study. No original data collection was conducted here; the paper synthesizes legal cases, guidelines, scholarship produced by practitioners and in design education, and experimental research on generative model biases in order to trace how GenAI is altering the understanding of authorship and originality in graphic design through copyright law, professional practices, visual aesthetics, and design education. GenAI does not render human authorship irrelevant, as was claimed by many in the early discussion of the topic. Rather, it becomes relative depending on how specific the human input in terms of creative direction is, how deep the post-generation editing is and how effectively a designer is able to justify the design choices. Copyright law authorities in the US, UK, and EU reach the consensus on the principle of protecting only works created with demonstrable human authorial input; however, each one uses its own criteria to measure this input. According to practitioner research, the function of designers changes from the creator of visuals to curators and editors of the machine output. On the other hand, experimental research of generative models demonstrates homogenization of styles and representational bias inherited from training data, but also improvements in efficiency and positive evaluation by audiences of GenAI-assisted graphics. The field where these issues are addressed is design education. The paper concludes by using the existing control-based legal scholarship to develop a multi-dimensional framework which can be used by practitioners, educators, and reviewers to describe GenAI-assisted works.
Bahaa Mustafa, Abeer Ibrahim· American Journal of Art and...· 0 citations