Adoption of AI technologies in the arts has faced a divided reception and raised controversies—while some artists critique them, others embrace the opportunities they provide. In this paper, we contribute empirical insights into what motivates artists’ adoption of AI art technologies, as well as what kind of worldviews these motivations for AI adoption in artistic contexts embody. We shed light on these questions by presenting results from a qualitative interview study (N = 19) of AI artists practicing in Nordic countries. Five key themes emerged that describe artists’ motivations for using AI in their work, which we analyse in reflection with Kerschner and Ehlers' Attitudes Towards Technology (ATT) framework in terms of underlying attitudes of AI-Enthusiasm, Pragmatism, Romanticism, and Scepticism. Our analysis diversifies the understanding of why artists use AI, surfacing cultural and political tensions inherent in adoption of AI technologies for artistic and creative use.

From issues of intellectual property rights, environmental impact,and the question of creativity in itself, Creative AI  (AI applied to arts and design) presents many pressing ethical challenges. At thes ame time, AI ethics guidelines have been criticised for their rationalist inactionability, highlighting the need for finding ground-up approaches for exploring situated ethics and anticipatory – rather than reactive – ethics in AI technology design. In this paper, we present the results of organising two workshops with Creative AI practitioners in writing fictional research abstracts (FRAs). The participants wrote future-oriented research scenarios for Creative AI and engaged in discussion about them, with the aim to critically reflect on Creative AI ethics and futures in an anticipatory manner. In this paper, we provide an analysis of the imaginaries within the abstracts (e.g. stakeholders, technology framing, and scientific study framing in the abstract), as well as a thematic analysis of topics evoked in and by the abstracts. We observe that the FRAs facilitated five different kinds of thematic discussions, of which nature of creativity and role on AI in the society were particularly prevalent. We also witnessed socio-technical continuity that brought current and past conditions as constraints into the future scenarios. We subsequently reflect on how the FRAs engaged with ethical questions using the Anticipatory Technology Ethics perspectives of technology, artefact, and application. Our work contributes to the empirical understanding of the ethical concerns of future Creative AI technologies and their role in society, while extending the empirical insights of applying the FRA method into a situated case of anticipatory ethics reflection.

In this third installment of our GenAI workshop series at DIS, we focus on ‘stopsigns’—the blockages that impede progress in design research with GenAI. These stopsigns manifest as both semantic barriers (political, social, or mental frameworks) and pragmatic hurdles (technical limitations or implementation challenges) that persist despite the rapid advancements since the GenAI boom. Such stopsigns present a productive tension—they often contain partial truths worthy of consideration while simultaneously being shortsighted in ways that prevent progression. From blanket rejection to uncritical acceptance, these barriers affect how meaningfully we engage with GenAI’s potential. Our workshop welcomes both returning and first-time participants to share their experiences with these persistent challenges and work together to develop practical solutions. Through analysis of real cases and hands-on activities, we’ll build strategies for moving beyond these obstacles while acknowledging their legitimate concerns. Our goal is to foster more thoughtful integration of GenAI in design research and practice.

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.

Since 2022, Visual Generative AI (vGenAI) tools have experienced rapid adoption and garnered widespread acclaim for their ability to produce high-quality images with convincing photorealistic representations. These technologies mirror society’s prevailing visual politics in a mediated form, and actively contribute to the perpetuation of deeply ingrained assumptions, categories, values, and aesthetic representations. In this paper, we critically analyze Stable Diffusion (SD), a widely used open-source vGenAI tool, through visual and intersectional analysis. Our analysis covers; (1) the aesthetics of the AI-generated visual material, (2) the institutional contexts in which these images are situated and produced, and (3) the intersections between power systems such as racism, colonialism, and capitalism—which are both reflected and perpetuated through the visual aesthetics. Our visual analysis of 180 SD-generated images deliberately sought to produce representations along different lines of privilege and disadvantage—such as wealth/poverty or citizen/immigrant—drawing from feminist science and technology studies, visual media studies, and intersectional critical theory. We demonstrate how imagery produced through SD perpetuates pre-existing power systems such as sexism, racism, heteronormativity, and ableism, and assumes a default individual as white, able-bodied, and masculine-presenting. Furthermore, we problematize the hegemonic cultural values in the imagery that can be traced to the institutional context of these tools, particularly in the tendency towards Euro- and North America-centric cultural representations. Finally, we find that the power systems around SD result in the continual reproduction of harmful and violent imagery through technology, challenging the oft-underlying notion that vGenAI is culturally and aesthetically neutral. Based on the harms identified through our qualitative, interpretative analysis, we bring forth a reparative and social justice-oriented approach to vGenAI—including the need for acknowledging and rendering visible the cultural-aesthetic politics of this technology and engaging in reparative approaches that aim to symbolically and materially mend injustices enacted against social groups.

The design justice of AI technologies is infuenced by value tensions, by which values get embedded and excluded in design processes. In this study, we investigate Euro-Western artists’ expressed values for the design of Creative AI technologies. We conducted four workshops, in which artists engaged in value sketching and critical discussion around Creative AI, and analyzed emerging values. In the sketches, the artists predominantly expressed values of self-interest, while when encouraged for a critical discussion artists expressed values aligned with interest of others. We discuss the challenge of aligning Creative AI with design justice, when values of common good are not inherently part of the technological imaginaries, but rather need to be explicitly evoked. We open up these value tensions, discussing values’ actionability, and the implications for design futures of Creative AI. With this paper, we extend the empirical studies in value sketching and socio-technical landscape of Creative AI.

As music generated using artificial intelligence (AI music) becomes more prevalent — originating not only from individuals but also commercial services — the need to study it and its impacts becomes important. How can this material and its sources be meaningfully studied and critically engaged with, especially considering the unprecedented scales possible with generative AI? The paper begins to answer this question by considering AI music along seven aspects: 1) the company providing an AI music service; 2) its founders and employees; 3) the use of the service; 4) the users; 5) the algorithms; 6) the music; and 7) the sustainability. We make our discussion more concrete by considering the contemporary AI music service Boomy. While our investigations are preliminary and focused on a single AI music service, we argue that they open several interesting avenues of exploration for many disciplines and their intersections to help prepare for the coming flood of AI music. This paper asks many more questions than it answers, which is a feature (not a bug) of it advocating for a new domain of study: AI Music Studies.

While the use of AI technologies for artistic and creative practices (Creative AI) has become commonplace in recent years, more-than-human perspectives are slowly making their way into design research. However, the development of Creative AI technologies (and AI in general) is currently often human-centred, and there are significant efforts in both AI ethics research and the industry to guide it in such a direction. In this light, in my work, I examine Creative AI technologies from the critical perspective of more-than-human design, focusing specifically on aesthetics and cultural imaginaries that are prioritised in their design, and questioning the current assumptions that underlie their design and development approaches. The question of prioritising human versus non-human (and particularly natural non-humans, such as the environment and animals) viewpoints is largely an environmental ethical question, and a question of design ethics of ‘who gets to matter’ in the design of Creative AI technologies. Thus, I discuss how humans and non-humans get to matter when it comes to Creative AI entanglements, looking at relevant examples from the existing technologies and cultures around designing them. The main takeaways of this chapter include questioning and broadening the human-centred framing of Creative AI toward a more-than-human framing, with a specific focus on imaginaries and the aesthetics of Creative AI technologies. More specifically, I will be covering these themes by presenting examples of AI-generated images and visual culture, as well as by covering critical and speculative case studies that focus on artefacts and imaginaries of Creative AI.

Sustainability in and through digital technology has up until very recently been framed in modernist terms, focused on quantification and optimization of resource use. This framing has been frequently criticized for being limited in scope and impact, and has been framed as shallow sustainability in environmental ethics literature. Sustainability within computational creativity (CC) research is an emerging topic. To avoid the pitfalls of shallow sustainability, we conceptualise and propose a ’deep sustainability’ perspective in computational creativity research. This enables a relational approach to the predicament of the climate crisis by critically examining the values and assumptions that underpin CC research. Building on this, we reflect on and discuss what deep sustain-ability would mean for the future of sustainability research within the CC community, and raise critical questions with the particular aim of sparking discussions around how sustainability research is and ought to be approached within the community.

Human-nonhuman sound interaction and technologies aim to bridge the gap of inter-species communication. While they emerge from attempts to understand and communicate with nonhumans, they also raise questions on the ethics of nonhuman data use, for example regarding the unintended consequences such data extraction can have to nonhumans. In this paper, we discuss power relations and aspects of representation in nonhuman data practices, and their potential critical implications to nonhumans. Drawing from prior research on data ethics and posthumanities, we conceptualize two challenges of nonhuman data ethics for the design of Human-Nonhuman Interaction (HNI) and technologies in sound ecologies. We provide takeaways for how sensitivities toward nonhuman stakeholders can be considered in the design of HNI in the context of sound ecologies.