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.

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.

This study presents a sonification tool – SonifyFOLK –designed for intuitive access by musicians and dancers in their sonic explorations of movements in dance performances. It is implemented as a web-based application to facilitate accessible audio parameter mapping of movement data for non-experts, and applied and evaluated with Swedish folk musicians and dancers in their exploration of sonifying dance. SonifyFOLK is based on the WebAudioXML Sonification Toolkit and is designed within a group of artists and engineers using artistic goals as drivers for the sound design. The design addresses challenges of providing an accessible interface for mapping movement data to audio parameters, managing multi-dimensional data and creating audio mapping templates for a contextually grounded sound design. The evaluation documents a diversity of sonification outcomes, reflections by participants that imply curiosity for further work on sonification, as well as the importance of the immediacy of the both visual and acoustic feedback of parameter choices. 

Musical worlds, not unlike our lived realities, are fundamentally fragmented and diverse, a fact often seen as a challenge or even a threat to the validity of research in Music Information Research (MIR). In this article, we propose to treat this characteristic of our musical universe(s) as an opportunity to fundamentally enrich and re-orient MIR. We propose that the time has arrived for MIR to reflect on its ethical and cultural turns (if they have been initiated at all) and take them a step further, with the goal of profoundly diversifying the discipline beyond the diversification of datasets. Such diversification, we argue, is likely to remain superficial if it is not accompanied by a simultaneous auto-critique of the discipline’s raison d’être. Indeed, this move to diversify touches on the philosophical underpinnings of what MIR is and should become as a field of research: What is music (ontology)? What are the nature and limits of knowledge concerning music (epistemology)? How do we obtain such knowledge (methodology)? And what about music and our own research endeavor do we consider “good” and “valuable” (axiology)? This path involves sincere inter- and intra-disciplinary struggles that underlie MIR, and we point to “agonistic interdisciplinarity” — that we have practiced ourselves via the writing of this article — as a future worth reaching for. The two featured case studies, about possible philosophical re-orientations in approaching ethics of music AI and about responsible engineering when AI meets traditional music, indicate a glimpse of what is possible.

This paper describes the development of three digital sound prototypes based on three sounding objects selected from those in use at the Swedish Radio Sound Studio. Knowledge about historical and current creative practice was gathered through an in-depth interview with the Swedish Radio sound engineer and sound maker Michael Johansson and the observation of his Foley practice. A design workshop was carried out with music composers and interaction designers to ideate how these historical sound design concepts could be developed in the digital domain. On the basis of the workshop results, we built three prototypes that were exhibited at Tekniska Museet in Stockholm where we gathered feedback from 126 people. Finally, we discuss what we have learnt from utilising an approach rooted in historical creative practice, emphasizing benefits for contemporary digital sound design.