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This article aims to critically examine AI as both an active and innovative tool in artistic creation, investigating its evolving role in shaping artistic practices, expanding creative possibilities, and redefining the boundaries of human–machine collaboration. It traces the historical, conceptual, and technological integration of generative AI in art, particularly in relation to Modernism’s challenge to traditional norms. It also examines the ethical, social, and philosophical implications of AI art, focusing on issues such as authorship, legitimacy, and AI’s role in the cultural landscape. Through the analysis of two representative works—Refik Anadol’s Unsupervised and Anna Ridler’s Mosaic Virus—one mainstream and the other critically engaging with AI art’s social impact, the study examines the balance between technical innovation and conceptual depth, emphasizing transparency, originality, and human-centered approaches. Employing an extended literature review across chapters, the discussion synthesizes diverse sources to critically engage with ongoing debates. Ultimately, the article advocates for human–AI collaboration, emphasizing responsible integration to enhance creativity without losing the human essence of art. It offers highly valuable insights into the current debates surrounding AI in art and effectively guides the integration of AI into future creative practices.

This paper reimagines AI hallucinations, instances where large language models (LLMs) generate coherent yet factually ungrounded content, as posthuman hermeneutic practices, where human and machine agencies entangle to produce new modes of meaning-making. Moving beyond binary framings of hallucinations as flaws or features, the analysis situates them within Donna Haraway's sympoietic ethics and proposes sympoietic creativity between human and AI, arguing that these generative anomalies are not errors but provocations for rethinking creativity as a distributed and collaborative act. Through case studies of models like DeepSeek-R1 and artistic projects such as Pharmako-AI (2021), this article demonstrates how hallucinations act as hermeneutic knots, sites where algorithmic noise is curated into cultural critique and interspecies narratives. By contrasting human creativity that is rooted in intentionality and embodiment with AI's stochastic recombination, this paper exposes the ontological chasm between anthropocentric artistry and machine-generated “spectral pantomimes.” Ultimately, the article challenges stakeholders to embrace AI's disruptive potential, not as a tool for replication but as a mediator for posthuman futures, where creativity is redefined through justice, relationality, and the radical interdependence of human and non-human agents.

In recent years, artificial intelligence (AI) has experienced an unprecedented surge in research and development, manifesting in innovative methods, advanced hardware, and groundbreaking applications across varied domains. Particularly notable is AI’s foray into the realms of art and design, where it has ushered in a revolutionary paradigm, facilitating a more diverse and intellectually enriching experience for both designers and consumers. This burgeoning intersection between AI and artistry is not only recalibrating the creative process but also envisaging a future rife with boundless possibilities and fresh challenges in artistic design development. The present research meticulously reviews and discusses the mechanisms through which AI engenders art and design and rigorously explores the potential and inherent challenges presented when integrating AI into these traditionally human-centric fields. The research emphasizes that while AI indubitably holds the potential to amplify and enhance the creative process for artists and designers, it is of paramount importance to navigate this technological integration with prudence. It urges a careful contemplation of the potential repercussions of AI on the art and design industries, underscoring the necessity to harmonize the utilization of AI with the needs, rights, and ethical considerations pertinent to human artists and designers, thereby ensuring a future where technology and humanity coexist synergistically in the creative space.

This research delves into the perspectives of artificial intelligence (AI) artists within the advertising industry. Employing both quantitative and qualitative methodologies, the study utilizes survey data from 200 participants and conducts 10 in-depth interviews with professionals across various positions and companies in the advertising sector. The aim is to explore the effectiveness and satisfaction derived from AI-generated artwork, unveiling viewers' concerns regarding quality, emotional depth, and economic impact. While advertising experts express optimism about AI’s role in optimization, particularly in sparking innovative ideas, the research highlights a deficiency in AI's ability to convey emotional narratives. Additionally, concerns arise about the practical application of AI-created art in advertising, touching on ongoing debates about copyright and ownership laws. The study concludes by proposing suggestions to enhance the efficacy and practicality of AI-based creations in the advertising industry.

This paper introduces an innovative framework for visualisation design ideation, which includes a collection of terms for creative visualisation design, the five-step process, and an implementation called VisAlchemy. Throughout the visualisation ideation process, individuals engage in exploring various concepts, brainstorming, sketching ideas, prototyping, and experimenting with different methods to visually represent data or information. Sometimes, designers feel incapable of sketching, and the ideation process can be quite lengthy. In such cases, generative AI can provide assistance. However, even with AI, it can be difficult to know which vocabulary to use and how to strategically approach the design process. Our strategy prompts imaginative and structured narratives for generative AI use, facilitating the generation and refinement of visualisation design ideas. We aim to inspire fresh and innovative ideas, encouraging creativity and exploring unconventional concepts. VisAlchemy is a five-step framework: a methodical approach to defining, exploring, and refining prompts to enhance the generative AI process. The framework blends design elements and aesthetics with context and application. In addition, we present a vocabulary set of 300 words, underpinned from a corpus of visualisation design and art papers, along with a demonstration tool called VisAlchemy. The interactive interface of the VisAlchemy tool allows users to adhere to the framework and generate innovative visualisation design concepts. It is built using the SDXL Turbo language model. Finally, we demonstrate its use through case studies and examples and show the transformative power of the framework to create inspired and exciting design ideas through refinement, re-ordering, weighting of words and word rephrasing.

VisRep (Visualisation Report) is an AI-powered system for capturing and structuring the early stages of the visualisation design process. It addresses a critical gap in predesign: the lack of tools that can naturally record, organise, and transform raw ideation, spoken thoughts, sketches, and evolving concepts into polished, shareable outputs. Users engage in talk-aloud sessions through a terminal-style interface supported by intelligent transcription and eleven structured questions that frame intent, audience, and output goals. These inputs are then processed by a large language model (LLM) guided by markdown-based output templates for reports, posters, and slides. The system aligns free-form ideas with structured communication using prompt engineering to ensure clarity, coherence, and visual consistency. VisRep not only automates the generation of professional deliverables but also enhances reflective practice by bridging spontaneous ideation and structured documentation. This paper introduces VisRep’s methodology, interface design, and AI-driven workflow, demonstrating how it improves the fidelity and transparency of the visualisation design process across academic, professional, and creative domains.

This article examines emerging practices in large language model (LLM) integration within game writing, focusing on how these technologies reshape narrative design, creative workflows, and professional roles. Drawing on evolving industry experimentation and academic research, it outlines the relationship between traditional game writing and LLM-driven approaches, surveys new forms of interactive storytelling such as conversational NPCs, multi-agent simulations, adaptive commentators, and LLM-based text adventures, and identifies their narrative affordances and constraints. The article analyses core challenges, including hallucination, bias, narrative incoherence, and control, and discusses current strategies to address them, such as fine-tuning, prompt engineering, and new authoring tools that position writers as system-level narrative architects. It argues that LLM integration represents not automation but a reconfiguration of co-creative authorship between writers, machines, and players, and calls for further research into ethical design, player reception, and the evolving responsibilities of narrative professionals in LLM-augmented game development.

Abstract The transformative achievements of deep learning have led several scholars to raise the question of whether artificial intelligence (AI) can reach and then surpass the level of human thought. Here, after addressing methodological problems regarding the possible answer to this question, it is argued that the definition of intelligence proposed by proponents of the AI as “the ability to accomplish complex goals,” is appropriate for machines but does not capture the essence of human thought. After discussing the differences regarding understanding between machines and the brain, as well as the importance of subjective experiences, it is emphasized that most proponents of the eventual superiority of AI ignore the importance of the body proper on the brain, the laterization of the brain, and the vital role of the glia cells. By appealing to the incompleteness theorem of Gödel’s and to the analogous result of Turing regarding computations, it is noted that consciousness is much richer than both mathematics and computations. Finally, and perhaps most importantly, it is stressed that artificial algorithms attempt to mimic only the conscious function of parts of the cerebral cortex, ignoring the fact that, not only every conscious experience is preceded by an unconscious process but also that the passage from the unconscious to consciousness is accompanied by loss of information.

Dan Brown's Origin illustrates the transformative influence of artificial intelligence, technology, and design on the creative process through a captivating intersection. This paper examines Winston, the advanced artificial intelligence featured in the book, as a symbolic architect that influences artistic and architectural creativity. This study examines the ways in which Origin challenges traditional human-centred notions of authorship and creativity, thereby redefining AI as a co-creator rather than an instrument, within the context of post-humanism theory. Technological determinism provides a framework for analysing the transformation of architectural and artistic sensibilities by AI-driven design, emphasizing the inescapable impact of technology on creative expression. The philosophical implications of artificial intelligence-driven design are examined in this study through an examination of significant architectural references, particularly the works of Antoni Gaudí, and the futuristic technical vision of the book. This fiction highlights Brown's vision of a future in which artificial intelligence is a significant force that re-envisions art, architecture, and creativity by situating Origin within the broader discourse on technological determinism and posthumanism. The book prompts readers to rethink whether AI-generated design and art are legitimate forms of creative expression. In conclusion, this probation posits that Origin not only epitomises contemporary discourse regarding the application of artificial intelligence in artistic creation, but also foresees a future in which design and technology will be inextricably linked, thereby eliminating the distinctions between human and machine-generated creativity.

AI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to examine the affective, autonomic, and creative consequences of AI-assisted coding in early-stage learners. Fifty-eight undergraduate design students with no formal programming experience were randomly assigned to either an AI-assisted group or a control group and engaged in a two-day generative programming task. Emotional states (PANAS), creative self-efficacy (CSES), and subjective workload (NASA-TLX) were assessed, alongside continuous monitoring of heart rate variability (HRV; RMSSD and LF/HF). Compared to the controls, the AI-assisted group exhibited greater increases in negative affect (p = 0.006), reduced parasympathetic activity during the task (p = 0.001), and significant post-task declines in creative self-efficacy (p < 0.05). Expert evaluation of creative outputs revealed a significantly lower performance in the AI group (p = 0.040), corroborated by behavioral observations showing higher tool dependency, emotional volatility, and rigid problem-solving strategies. These findings indicate that, in novice users, the opacity and unpredictability of AI feedback may disrupt emotional regulation and autonomic balance, thereby undermining creative engagement. The results highlight the need to consider neurocognitive vulnerability and the learner’s developmental stage when integrating AI tools into cognitively demanding creative workflows.