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.

Feverish narratives of artistic AI-revolution obscure the fact that empirical documentation of the actual impacts of artificial intelligence on artistic practices is still sparse. This paper focuses on the frictions of working with AI artistically. Based on interviews with 20 AI-artists, we 1) demonstrate that frictions experienced with the technological elements of the work processes with AI are inseparably intertwined with the artists’ socio-material realities and the inherent asymmetries of access, and 2) show how frictional ambivalence and unpredictability in artistic interactions with AI tools function both as restrictive and productive elements of the art-making processes, presenting opportunities to reframe the core notions of artistic agency, authorship, and the ontology of art.We discuss these findings in the context of HCI and critical data studies and provide three invitations for designing with and for frictions. Our empirical work contributes to a deeper understanding of the emerging community of AI-artists and invites new mindful perspectives for the design and development of Creative AI applications.

The environmental footprint of Generative AI and other Deep Learning (DL) technologies is increasing. To understand the scale of the problem and to identify solutions for avoiding excessive energy use in DL research at communities such as ISMIR, more knowledge is needed of the current energy cost of the undertaken research. In this paper, we provide a scoping inquiry of how the ISMIR research concerning automatic music generation (AMG) and computing-heavy music analysis currently discloses information related to environmental impact. We present a study based on two corpora that document 1) ISMIR papers published in the years 2017–2023 that introduce an AMG model, and 2) ISMIR papers from the years 2022–2023 that propose music analysis models and include heavy computations with GPUs. Our study demonstrates a lack of transparency in model training documentation. It provides the first estimates of energy consumption related to model training at ISMIR, as a baseline for making more systematic estimates about the energy footprint of the ISMIR conference in relation to other machine learning events. Furthermore, we map the geographical distribution of generative model contributions and discuss the corporate role in the funding and model choices in this body of work.

Artistic uses of AI technologies are fast gaining prominence in a number of creative domains. In this paper, we describe our preliminary research exploring the challenges and changes that working with AI poses to artists based on interviews with N=20 artists. We present preliminary themes relating to challenges and changes that artists are encountering and highlight the importance of studying AI further in situated artistic practices.

In this exploratory paper, we focus on intersecting design political and visual processes of gendering and racializing in online AI image generators, in particular ArtBreeder and Midjourney. While AI image generators are becoming an integrated part of our contemporary society, they draw on cultural and historical imaging conventions of sorting and ordering the world and the people in it. These tools' powerful visual rhetoric can potentially aggravate existing discrimination, if not critically reflected upon. We argue that these design-facilitated representations position the ‘user’ into cultural imagery of representations with political implications. With an intersectional perspective from the feminist visual analysis, we critique and uncover how gender and ethnicity are represented and built into the systems, both in terms of visual culture and in designed interactions. We problematize these design strategies, and urge the HCI community to engage in further design political inquiries regarding the visual culture mediated by AI image generators.