The study contributes a cautious comparative framework for distinguishing prompt-induced structural conformity from analytically emergent features in AI-generated narrative.
Abstract
Generative artificial intelligence has renewed debates about creativity, authorship, and artistic meaning, but structural similarity alone does not establish autonomous creativity. This exploratory study compares three human-authored feature films – Parasite (2019), John & Marsha sa Amerika (Part Two) (1975), and City Lights (1931) – with three ChatGPT narratives elicited through prompts that explicitly specified a mythic form and one of three preselected binary oppositions: wealth versus poverty, aspiration versus rejection, and appearance versus reality. Drawing on Saussure, Lévi-Strauss, a Propp-inspired analysis of spheres of action, and Barthes, the study examines oppositional organisation, mediation, character roles, symbolic signification, cultural-historical embedding, ideological ambivalence, and narrative closure. Under the documented prompt conditions, all three AI outputs instantiated several structuralist categories. Because both the binary opposition and the mythic genre were built into the prompts, however, these features are treated as prompt-conditioned rather than independently emergent. Relative to the selected films, the AI outputs exhibited stronger moralisation and narrative closure and weaker cultural-historical specificity. The findings are limited to a small, researcher-prompted corpus and do not establish a general capacity for autonomous AI creativity. The study contributes a cautious comparative framework for distinguishing prompt-induced structural conformity from analytically emergent features in AI-generated narrative.
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.
This study examines how generative artificial intelligence reshapes creative work in advertising agencies and considers its implications for professional capability development and continuous improvement. Attention centers on everyday routines, redistribution of expertise and organizational conditions that convert AI-enabled iteration into learning or, conversely, efficiency without capability growth.
An exploratory qualitative design draws on open-ended questionnaire responses from 18 advertising professionals, including copywriters, art directors and video designers/makers. Researcher-led thematic analysis was supported by InfraNodus Lab. Text-network outputs served as sensitizing maps of recurrent concepts and semantic connections; final themes resulted from repeated comparison with complete responses.
Four themes organize reported experience: generative AI as everyday creative practice, reconfiguration of creative process, time compression and process optimization and skill reconfiguration with deskilling risk. Participants associated AI with ideation, drafting, visual exploration and alternative generation. Their accounts also relocated professional value toward prompting, selection, evaluation, refinement and strategic interpretation. Metalinguistic competence appears as a capability for translating strategic intent into machine-readable instructions.
Advertising agencies should integrate generative AI through reflective routines that preserve human judgment, professional learning and junior skill development. Training should combine prompt literacy with brand interpretation, output evaluation and shared review practices, while performance systems should assess capability growth alongside speed and productivity.
Context-specific evidence from advertising agencies clarifies how metalinguistic competence links AI-mediated creation with professional judgment. A PDSA-informed model distinguishes reflective AI use, where generated alternatives are studied and converted into organizational learning, from transactional use, where output speed may rise without sustained skill development. Contribution rests on specifying a quality-management mechanism through which AI-supported iteration can become human-centered continuous improvement.
Mario D’Arco, Orlando Troisi, G. Maione· The TQM Journal· 0 citations
This study theorises artistic collaboration with generative artificial intelligence through the concept of generative liminality, understood as a transitional and unstable zone in which human intention, cultural memory, and algorithmic inference enter into negotiation. Grounded in a case study of Rafani’s exhibition Everyone Has the Right to Everything (Gallery 8smička, 2025), the analysis examines how AI-assisted creation operates within a small-language, post-socialist context shaped by ideological ambivalence, satire, and distrust of universalist promises. Developed in Czech and structured around locally specific political references, the project exposed the frictions that emerge when globally trained AI models engage regional realities. Rather than functioning as neutral tools, these systems selectively translate, flatten, and recompose local imaginaries, design vocabularies, and rhetorical forms. Such distortions are approached here not simply as technical limitations, but as epistemic symptoms of the asymmetries embedded in contemporary generative infrastructures. A central component of the exhibition was an AI-generated audiovisual layer. Four satirical short films, styled as “Pixar-like” animations, presented a tardigrade interviewing four “successful” Czech women, while three additional videos featured fictional male influencers performing polarised monologues on migration, left politics, and the pre-election climate. Produced entirely through AI-based image, animation, voice, sound, and script generation, these works mobilised speculative fiction as a mode of cultural diagnosis. The chapter argues that generative systems participate in the reconfiguration of political and cultural representation, reshaping not only aesthetic production but also the conditions under which locality becomes legible.
Generative text systems challenge established accounts of literary authorship, creative agency, and communicative intentionality. This qualitative comparative case study examines selected passages from George Orwell’s Nineteen Eighty-Four (2003) and Ross Goodwin’s 1 the Road (2018), an early sensor-driven LSTM experiment. Informed by computational creativity and posthumanist accounts of distributed cognition, the study compares the texts in relation to local cohesion, global narrative continuity, temporal and causal organisation, metaphorical patterning, and the distribution of creative agency across human and computational actors. The selected passages suggest that 1 the Road can produce locally fluent and occasionally striking combinations, but that its longer-range referential and narrative continuity differs substantially from the sustained plotting and thematic organisation of Orwell’s novel. At the same time, the production history of 1 the Road complicates any simple opposition between human and machine authorship: the system, training data, sensors, route, programmer, and decision not to post-edit all contribute to the published work. The comparison therefore does not establish a universal boundary between human and AI creativity. Rather, it offers a historically bounded account of how genre, editorial practice, model architecture, and production conditions shape literary coherence and authorship.
This article examines the entanglement of artificial intelligence (AI) and popular digital culture through a case study of the music video “Preman Anggaran” by the band Parikesit. The video features an AI generated female figure, modestly veiled yet styled in casual, tomboyish attire, performing socially charged rap-punk lyrics that critique political corruption and class inequality. Employing Norman Fairclough’s model of Critical Discourse Analysis (CDA) in conjunction with theoretical insights from Cultural Studies, this study interrogates the ideological, representational, and resistant dimensions embedded in both the textual and visual content. The analysis reveals how confrontational lexical choices, oppositional semantics, and direct narrative structures function as linguistic strategies of symbolic resistance. The production process, which relies on AI generated aesthetics, subverts conventional norms of visual representation and enables alternative forms of cultural expression. The video’s dissemination via digital platforms such as YouTube and TikTok exemplifies a non-institutional mode of circulation, while its reception demonstrates participatory engagement and affective resonance among politically conscious audiences. Ultimately, this study foregrounds the methodological relevance of CDA and cultural studies in navigating the cultural politics of algorithmically mediated expression, highlighting how AI can be mobilized as a vehicle for symbolic intervention and alternative articulation in contemporary popular culture.
Eka Dian Savitri· JURNAL SOSIAL HUMANIORA· 0 citations
Creative writing pedagogy has often privileged imagination as the defining characteristic of storytelling. Yet many young writers struggle not because they lack imagination, but because they believe they have nothing worth writing about. This paper proposes a pedagogical model that repositions observation, critical thinking, empathy, and structured inquiry as the true foundations of world-building. Drawing on a story-building workshop designed for middle-school students, and grounding its design in narrative psychology, structuralist and post-structuralist narrative theory, cognitive research on attention and creativity, and sociocultural learning theory, it argues that effective storytelling begins with learning to notice the world before attempting to invent new ones. The workshop integrates literary theory, cognitive observation, narrative analysis, collaborative exercises, and current discussions on artificial intelligence to demonstrate that stories emerge from attentive engagement with reality rather than unrestricted fantasy. Rather than teaching creative writing as a collection of technical skills, this approach frames telling stories as a human act of meaning-making, ethical reflection, and imaginative reconstruction, and it proposes a theoretically informed alternative to imagination-first models of creative writing instruction.
Suhaile Azavedo· International Journal of Eng...· 0 citations
