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What is generative art?
Abstract
There are various forms of what's sometimes called generative art, or computer art. This paper distinguishes the major categories and asks whether the appropriate aesthetic criteria—and the locus of creativity—are the same in each case.
... Historically, artists have always been at the forefront of engagement with new technologies (Candy et al. 2018;Ellul and Hofstadter 1979;Girão and Céu Santos, 2019), utilising advanced tools, systems and platforms. Artistic engagement with new technologies has led to the birth of significant cultural movements and genres within the world of art including electronic art; mechanical art; computer art; digital art; computer-aided art; generative art; computer generated art; evolutionary art; robot art; interactive art; NFT-art, VR art, and AI art (Boden and Edmonds, 2009;Thomson-Jones and Moser, 2021;Wang and Wang, 2021). ...
The advancement of AI-tools for musical performance has inspired exciting opportunities for interaction with musical-AI-agents. Interactions between humans and AI-agents in musical settings entail dynamic exchanges of control and power, and framings of AI-agents’ roles by human performers. We probe these framings and power-control exchanges through qualitative thematic lenses, drawing from post-phenomenology, matters of fact and concern and feminist science and technology studies. We contribute with a novel interdisciplinary analytical method as a tool for developers and designers of AI systems to help visibilise and examine the implicit, the wider connections and entangled filaments in Human–AI musical interactions.
... Artists have also extensively used computer technology for generating artworks, first leveraging hardware technologies and later software to create objects driven by computational materiality (Arreola et al 2024;Bergstrom and Lotto 2015;Brown et al 2009;Franke 1971;Paul 2015). Furthermore, experiments with AI and generative algorithms have taken place for almost as long as the technology has existed (Boden and Edmonds 2009;Galanter 2003;Smite et al 2015). What has changed recently is the release of consumer-applications have now supported a new kind of public accessibility. ...
This text interrogates the theory and practice of AI as an artistic material through close analysis of an exhibition themed around human health and disability. Highlighting the project Art Beyond Humanity: AI x Human Collaborations (2023), this analysis explores three key questions regarding the (1) social and ethical impact of GenAI tools on artistic labor, (2) the relational process of co-creation between humans and algorithms, and (3) the aesthetic potential of AI as a creative medium. Led by curator Melanie Wilmink, mathematician Eric Dolores Cuenca, and artist/health advocate Justus Harris, alongside students from Yonsei and Woosong Universities in South Korea, the project used research-creation methodologies to provoke ethical questions about copyright, access to corporately controlled systems, and artistic tactics for production. In this paper, concerns about GenAI impacts on artistic labor are contextualized by art historical precedent and discussion about the limitations of algorithmic creativity. Subsequent sections articulate GenAI images as an assemblage of human and machine perception that embed bias but also hold the potential to draw attention to social issues, while outlining the techniques that artists can use to manipulate GenAI outputs. This can occur through code and database training, but also through the shaping of text prompts since GenAI images are imbricated with language. By exploring how GenAI produces images—as both material and conceptual—artists have the power to generate critical discourse about the social and the ethical impacts of these new technologies in the world.
... However, regarding AI as one of the film artists is against the origin of art (Heidegger, 2017). Films which use AI as an alterity partner belongs to generative art, but not film itself (Boden & Edmonds, 2009). In order to insure human auteurship and the ontology of cinema, AI should be used as an embodiment tool, but be considered as an independent "alterity partner". ...
The integration of Artificial Intelligence(AI) into film production has revolutionized efficiency and creativity, yet it simultaneously raises critical ethical and practical challenges. This study explores the dual impact of AI on modern cinema through three objectives: defining the optimal human-AI relationship, balancing creativity with automation, and developing ethical guidelines. By employing a mixed-method approach combining theoretical frameworks (auteur theory, human-technology relations) and case studies (The Safe Zone, Fast & Furious 7, The Brutalist), the research reveals that positioning AI as an "embodiment tool" rather than an independent "alterity partner" preserves human authorship and artistic integrity. Key findings highlight the risks of surveillance capitalism in AI-driven markets and the ethical dilemmas of deepfake technology. The study concludes with actionable recommendations, including international regulatory frameworks and a Human Control Index (HCI) to quantify AI involvement. These insights aim to guide filmmakers, policymakers, and scholars in navigating the evolving AI-cinema landscape while safeguarding cultural diversity and ethical standards.
AI in Society provides an interdisciplinary corpus for understanding artificial intelligence (AI) as a global phenomenon that transcends geographical and disciplinary boundaries. Edited by a consortium of experts hailing from diverse academic traditions and regions, the 11 edited and curated sections provide a holistic view of AI’s societal impact. Critically, the work goes beyond the often Eurocentric or U.S.-centric perspectives that dominate the discourse, offering nuanced analyses that encompass the implications of AI for a range of regions of the world. Taken together, the sections of this work seek to move beyond the state of the art in three specific respects. First, they venture decisively beyond existing research efforts to develop a comprehensive account and framework for the rapidly growing importance of AI in virtually all sectors of society. Going beyond a mere mapping exercise, the curated sections assess opportunities, critically discuss risks, and offer solutions to the manifold challenges AI harbors in various societal contexts, from individual labor to global business, law and governance, and interpersonal relationships. Second, the work tackles specific societal and regulatory challenges triggered by the advent of AI and, more specifically, large generative AI models and foundation models, such as ChatGPT or GPT-4, which have so far received limited attention in the literature, particularly in monographs or edited volumes. Third, the novelty of the project is underscored by its decidedly interdisciplinary perspective: each section, whether covering Conflict; Culture, Art, and Knowledge Work; Relationships; or Personhood—among others—will draw on various strands of knowledge and research, crossing disciplinary boundaries and uniting perspectives most appropriate for the context at hand.
Artificial intelligence (AI) has made significant advancements in creative fields such as art, music, and literature, transforming the way we create and interact with artistic content. By leveraging machine learning, deep learning, and generative models, AI can generate novel pieces of art, compose music, and even write literature that mimics human creativity. This paper explores the intersection of AI and creative expression, examining the potential and challenges of AI-generated art, music, and literature. We focus on key developments before 2012, with a discussion on the impact of AI on traditional notions of creativity and authorship.
This article explores the vivid field of generative media, focusing on the production and semiotic analysis of texts. It uses the broad definition of “text,” which encompasses written, visual, and interactive forms, and examines how generative media redefines the roles of content creators and tools. Utilizing Roman Jakobson’s communication model, the article highlights the dynamic decision-making process in text production, whether by human or AI. The paper offers a historical review which traces generative media from early computer art in the 1960s, through the advent of digital design tools in the 1980s and 1990s, to contemporary AI techniques like GANs and diffusion models. It identifies the key properties of generative media: synthetic, dynamic, digital, combinatorial, and agentic. The discussion also addresses the shift from unnoticed AI assistance in early tools to the inadvertently AI-generated content in today’s media landscape. The last part of the paper categorizes generative media interfaces into three types: conversational, web UI, and visual programming interfaces, analyzing their semiotic implications. It suggests that understanding these tools requires recognizing their layered technical components and the evolving user experience from magic-like simplicity to complex customization. In conclusion, the articles advocates for a multidisciplinary, process-oriented approach to fully grasp the cultural and communicative transformations driven by generative media, emphasizing the importance of transparency and user agency in AI interactions.
This collection of essays examines the philosophical and cultural aspects of technology. The issues range widely - from quantum technology to problems of technology and culture in a developing country and contributors approach the issues from a variety of perspectives. The volume includes case-studies, and also more theoretical pieces which consider the fundamental question of whether technology should be perceived as a force for liberation or enslavement. The volume aims to stimulate debate about the relation between technology and philosophy and society in general, and to open a field of enquiry that has been relatively neglected. Written in an accessible style, the contributions are intended equally for philosophers exploring the novel problems arising in the twentieth and twenty-first centuries, but also for technologists interested in the philosophical implications of their work.
Rule-Based Programming is a broad presentation of the rule-based programming method with many example programs showing the strengths of the rule-based approach. The rule-based approach has been used extensively in the development of artificial intelligence systems, such as expert systems and machine learning. This rule-based programming technique has been applied in such diverse fields as medical diagnostic systems, insurance and banking systems, as well as automated design and configuration systems.
Rule-based programming is also helpful in bridging the semantic gap between an application and a program, allowing domain specialists to understand programs and participate more closely in their development.
Over sixty programs are presented and all programs are available from an ftp site. Many of these programs are presented in several versions allowing the reader to see how realistic programs are elaborated from `back of envelope' models. Metaprogramming is also presented as a technique for bridging the `semantic gap'.
Rule-Based Programming will be of interest to programmers, systems analysts and other developers of expert systems as well as to researchers and practitioners in artificial intelligence, computer science professionals and educators.
A client visited my studio recently to see what new work I had. But instead of buying a painting, she invested about a quarter of what a painting would have cost on a new computer, a data projector and a license to run my computer program, AARON, from the output of which the paintings had been made. If you were to visit her apartment in New York now, you would find one wall of her living room serving as a screen on which you would catch AARON busily generating original images, a new one every two minutes or so.
How is it possible to think new thoughts? What is creativity and can science explain it? And just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover the nature of human creativity in the arts. The second edition of The Creative Mind has been updated to include recent developments in artificial intelligence, with a new preface, introduction and conclusion by the author. It is an essential work for anyone interested in the creativity of the human mind.