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This article provides an overview of current AI-assisted tools used in music composition and production and demonstrate their application through research-based music production. By highlighting the diverse range of applications and levels of automation offered by AI tools, we nuance the discourse focused on AI-generated tracks and challenge the assumption that using AI necessarily equates to cheating. We demonstrate how musicians can harness AI to support their artistry without overshadowing human expression, ensuring that creativity and integrity remain at the forefront
This paper presents LightHearted, an open-source Python framework for mapping the heart’s electrical activity from electrocardiography (ECG) signals acquired from performers to stage lighting in a concert setting. The aim is to provide dynamic lighting coupled to the physiological processes occurring during performance. Drawing upon critical approaches towards using biosignals in interactive systems and live concert research, we outline the framework’s design and implementation and present a case study with the Aarhus Symphony Orchestra. This paper highlights both technical and conceptual challenges of integrating biosensor-based lighting into a large-scale orchestral context. Results from a post-concert audience survey (N = 324) suggest that while responses to the lighting were mixed, it was generally not perceived as distracting and would be welcomed for use in future concerts.
This paper presents a mixed-method approach to investigating the felt experience of a networked music–dance performance. Using this approach, we explore how a sense of togetherness emerges even when performers are distributed across distant spaces. Drawing on data from the Telematic@Popsenteret research concert, we propose a three-layered analytical framework that integrates computer-based audio-video analyses with qualitative observation, and post-performance interviews. By combining sound–motion synchrony and temporal coupling with performers’ and audience members’ experiential accounts, we examine how dancers and musicians negotiate coordination and shared presence in a telematic environment. Our findings suggest that togetherness in such settings is not merely a matter of temporal alignment, but a dynamically constructed, multimodal process involving perceptual adaptation, cross-modal attunement, and affective awareness.
RhyGlyph is a radial visualization system that represents rhythmic interaction as three pairwise spacetime trajectories within a compact three-wedge glyph, supporting both overview and detailed reading. Building on this representation, RhyDiff is a generative framework that learns aligned latent spaces for symbolic drum patterns and the encoded trajectory features through paired VQ-VAEs and FiLM-conditioned diffusion. Users edit relational trajectories and metadata to generate new drum patterns by treating visualization itself as a control surface.
This paper presents a live semi-autonomous system that co-improvises with a live musician using a model learned from the relationship observed in paired recordings of an improvising duo. This responsive system is based on a deep learning approach that models the relations between sequences of events produced by co-playing musicians in continuous time, using transformer models. We present the architecture for simultaneous sequences of sonic events and provide a quantitative evaluation on several representative tasks. Results are compared against a canonical transformer and a multichannel Factor Oracle, the latter being a widely used model for live sequence-based symbolic music generation. We detail a live implementation employing concatenative synthesis and introduce a customization procedure in which the generative model is iteratively retrained on curated, satisfactory sections from sound recordings of actual human-system co-improvisational interactions. This iterative fine-tuning enables the model’s stylistic output to diverge from the original training corpus. Two musical use cases demonstrate the application of this technique.
Pixasonics is a new Python library for interactive image analysis and exploration through image sonification. It uses real-time audio and visualization to help uncover patterns in image data. With Pixasonics, users can launch one or more small web applications (running in a Jupyter Notebook), probe image data using various feature extraction methods, and map those feature vectors to synthesis parameters. The target users are researchers interested in exploring image and volumetric data and creative users who want an intuitive tool for experimental sound design. Pixasonics’ design aims to strike a balance between an easy-to-use web application with minimal boilerplate code necessary and a library that can be integrated into more advanced workflows. Real-time exploration is at the heart, but it can also be used to script non-real-time sonifications of large datasets. This paper presents Pixasonics, its structure, interface, and advanced features, and discusses preliminary feedback from biology researchers and music technologists.
Kunstfagene spiller en viktig rolle i å utvide måten vi jobber med og forstår komplekse samfunnsproblemer. Likevel blir kunstfagene stadig oversett og nedprioritert i forskningspolitikken. Vi spør derfor: hva er, bør og kan kunstens rolle være i det norske forskningslandskapet?
In this chapter, the colonial intervention of the technologies of capture are examined in the Global South regions, especially in South Asia in the beginning of the twentieth century. I study the ramifications of this entry in the form of mutating everyday sounds and musical practices into commodified sound objects for industrialisation and sale. From a critical decolonial position, this introduction of the technologies of capture is read here as a precarious intrusion into the sounding and listening cultures of the Global Souths, and a moment of emergence of an extractive capitalism through the colonial routes that devastate the sonic symbiosis of the land.
This paper explores how musicking technologies—interactive systems with musical properties—can enhance everyday public environments. We are particularly interested in investigating the effects of musical interactions in non-musical settings, such as offices, meeting rooms, and social work areas. Traditional music technologies (such as instruments) are built for goal-directed, conscious, and voluntary interactions. We propose a new perspective on embodied AI through systems that utilize indirect, inverse, unconscious, and, at times, involuntary interactions. Four different sound/music systems are examined and discussed with regard to their activity level: a reactive “birdbox,” a reactive painting, active self-playing guitars, and interactive music balls. All these systems are multimodal, containing sensors that detect various physical inputs to produce sound and light, and having varying levels of perceived agency. The paper explores differences between direct/indirect and regular/inverse embodied AI paradigms. This study demonstrates how minimalistic interactions have the potential to yield complex and engaging musicking experiences, challenging the norms of overly intricate AI implementations.
Musicologists, psychologists, and computer scientists study relationships between auditory and visual stimuli from very different perspectives and using various terminologies and methodologies. This article aims to bridge the gap between phenomenological sound theory, auditory–visual theory, and audio–video processing and machine learning. We introduce the SoundActions dataset, a collection of 365 audio–video recordings of (primarily) short sound actions. Each recording has been human‑labeled and annotated according to Pierre Schaeffer’s theory of reduced listening, which describes the property of the sound itself (e.g., ‘an impulsive sound’) instead of the source (e.g., ‘a bird sound’). With these reduced‑type labels in the audio–video dataset, we conducted two experiments: (1) fine‑tuning the latest audio–video transformer model on the reduced‑type labels in the SoundActions dataset, proving that the model can recognize reduced‑type labels, and observing that the modality‑imbalance phenomenon is similar to the added value theory by Michel Chion and (2) proposing the Ensemble of Perception Mode Adapters method inspired by Pierre Schaeffer’s three listening modes, improving the audio–video model also on reduced‑type tasks.
Under-resourced languages (and musics) pose a challenge to machine translation (MT). The challenge is greater when the content of the collected dataset is a varied sample taken from a data population that is even more diverse and dynamic. This is the challenge of Arab music vocal improvisation (mawwal). Here, we present the development of AMICOR, a parallel dataset consisting of vocal improvisatory phrases and their corresponding instrumental responses (or tarjamat in Arabic, which literally means “translations”) in the mawwal tradition. These melodic phrases are handled as “sentences” from the viewpoint of natural language. When developing the dataset, we integrated musicological insights in order to evaluate music theoretical differences between sub-datasets, primarily regarding their size, sentence length, performance quality, and shared musical identity. We then experimented with MT to generate instrumental responses to new vocal sentences, comparing several translation modeling configurations that differ (1) in translation approach (Neural MT (NMT) versus Statistical MT (SMT)), and (2) in the dataset handling approach in respect to the maqam (an Arabic musical term referring roughly to a melodic mode), comparing an individual model for each maqam versus a unified model for all maqamat. We found that merging related sub-datasets does not necessarily lead to better results, and may even favor simpler and shorter sentences with lower performance quality and less sophisticated patterns. This issue applies to both NMT and SMT; however, it is greater for NMT. A comparison of confusion matrices of individual-maqam models suggested that, in such a small dataset, the gap between SMT and NMT performance increases further if the styles, or skills, of potential users differ from those who built the dataset used in the training. Our discussion asserts that key factors in system design are the musical background and performance decisions of vocalists who may use such responsive generative models, as well as dataset size and performance quality.
In his recent critique of well-established simplified comparisons between the human mind and AI, Alva Noë encourages us to 'rage against the machine' (Noë, 2024). In this article, I build on Noë's timely encouragement, and sketch perspectives from both music studies and enactivist philosophy in order to interrogate what musicking might add to the debate. As a case study, I explore the recent public discourse surrounding the AI-band The Velvet Sundown and consider the implications — mental health related and ethical — of engaging with AI-generated music. I draw on current scholarship on musical creativity and AI to discuss the possibilities and limitations of creative agency in AI, laying the foundation for why human creative agency should be regarded more valuable than the artificial creativity that AI offers. I also discuss some ethical implications of sharing agency with AI, suggesting that we should continue to foster attunement to our creative agency and capabilities, as empowered but also vulnerable musicking human agents. I argue that musicking offers an enactive entanglement through which we are granted an opportunity to embrace risk, resist rules, and learn new modes of orientation and reorientation that serve as empowering tools for navigating our way through the resistant path to being human.
Studies on large language models (LLMs) have shown that these technologies can reproduce stereotype-based biases present in their training data. In this paper, we hypothesized that an OpenAI-based model would more frequently attribute first authorship to women in masculine-typed research fields than to men in feminine-typed fields, an asymmetry consistent with gender-role beliefs. Across three studies, we analyzed how the model’s generative outputs reflect gendered associations. Study 1 replicated Fulgu and Capraro’s phrase-association paradigm, replicating the study’s findings that feminine-stereotyped phrases were more consistently linked to female characters, whereas masculine-stereotyped phrases were less reliably linked to male characters. The results suggest that the training data contains a stronger and more stable association between femininity and communal traits than between masculinity and agency. Study 2 examined 4,585 randomly generated hypothetical studies and identified a substantial skew toward female first authors (>82%), with male authors overrepresented primarily in engineering, technology, and theoretical contexts. Study 3 extended these findings across nine specified research fields, where the results of the first stage were consistent with Study 2. When prompted to classify rather than generate the gender of the first author, the model produced a lower overall proportion of women, but retained the same relative distribution across fields observed at the first stage. Taken together, the results indicate that the model’s outputs correspond more to feminine than masculine gender-role beliefs. While this tendency may appear to increase women’s representation in masculine-typed domains, it does not afford men equivalent visibility in feminine-typed domains. These results underscore how LLMs, as statistical systems shaped by training corpora and reinforcement learning, can reflect and reproduce cultural and historical asymmetries in gender representation, challenging assumptions of epistemic neutrality.
This article examines how performative togetherness is constructed in a technologically mediated music–dance performance environment. While togetherness is often associated with co-presence and effortless flow, networked contexts introduce perceptual reconfiguration that makes it fragile and effortful. We present the research concert Telematic@PopSenteret, a networked performance involving dancers and musicians distributed across two floors in a museum, connected through audio–video transmission. Using interviews and audio-video recordings, we explore how latency, fractured perception, and the absence of bodily cues transformed the performers’ coordination and induced cognitive strain. We discuss how performative togetherness – defined as the sense of shared meaning-making that emerges through attentional, sensory, and adaptive negotiation – was maintained during the performance.
‘It isn’t real music!’ As I write this review there is an ongoing debate in Norwegian media about a band that has been booked to play in a festival next summer. The band is composed of human performers, but they are playing songs generated by AI. Or, more precisely, they have written the lyrics themselves and then fed them into a commercial AI-based music service that has created a melody and accompaniment. Is this ‘AI music’? Is it ‘real music’? Is it more or less ‘real’ whether they play acoustic instruments or laptops on stage? And, ultimately, does it matter who made what if people want to listen? To understand today’s disruptive introduction of AI-based commercial services better, it may help to look more closely at history. This is where Deirdre Loughridge’s book is a timely and valuable contribution. It reveals that human fascination with—and harsh scepticism of—machine-generated music is nothing new.
This article investigates the intersection of generative Artificial Intelligence (AI) and the book industry, focusing on the use of copyrighted literary works for training large language models (LLMs). As LLMs require enormous volumes of content for training, published books and other media have become valuable sources of data. Many training datasets appear to have been assembled without authorization or transparency, raising acute legal, ethical and cultural questions. In this article, we provide a detailed empirical analysis of the Scandinavian content within the Books3 dataset, used to train multiple major AI systems, characterizing it by publication year, publisher, authorship, genre, and language. As comparatively small language markets situated outside of the main hubs for AI development, the Scandinavian countries provide a relevant context for exploring the local implications of global AI deployment. The findings are discussed through a theoretical lens drawing on Michel Serres’s concept of the “parasite.” We argue that the inclusion of Scandinavian books in Books3 is part of a multidimensional ecology of parasitic exchange. This framework interprets the relationship between AI developers, shadow libraries, and publishers as a cascade of information appropriation, signifying a reconfiguration of cultural production and ownership in the age of generative AI.
Atomspheres is a series of performances on elemental listening engagement and meditative environmental attunement, leading to a participatory performance with the co-listeners. The performances attune to the macro-scale crises of the climate and ecology in a planetary context and bridges its intersection with micro-level coping strategies to the crises in a regenerative gathering. The performances resonate with the tradition of free improvisation as well as communal and participatory sonic gatherings for affective and discursive engagement with crises and conflict, practiced in many Global Souths cultures. These performance gatherings involve field recordings of climate variables like wind, water, and woods, comprovised by chance generative processes, accompanied by radio interferences transducing situated weather patterns, weaved together by meditative instrumental interventions of traditional instruments, as well as live electronics and algorithmic interpretation of data and assemblages embracing free improvisational techniques and ethos. As an invocation, the series invites the co-listeners into an exercise of slow listening and slow breathing that try to suspend time, control, ego, and individuality to tap into a humbler mode of fatalism and a distributed self-hood. This philosophical positioning stresses the subjugation of events or actions to fate or destiny and is commonly associated with an attitude of acceptance in the face of future events, which are thought to be inevitable. This approach manifests into yielding control by an emergent form of togetherness, intersubjectivity, and kinship when listening transcends an overt causality, and the psychosomatic condition embraces slow breathing to contemplate, and affective attunement. The project is inspired by the micro-level entanglements of human, more-than-human, and other life forms in a survival context, and explores sensory transduction of environmental conditions to figure how to make them post-immersive and attuning experiences in an openly circular, collaborative performance setting.
An improvisation with Muzziballs, ball-shaped musical instruments developed in collaboration between Muzziball AS and RITMO, in which sound is shaped by how each ball is moved and handled. Performed at the Department of Musicology's department concert in the ZEB building on 13 April 2026 by Bilge Serdar, Maham Riaz, Arthur Guo, Alexander Refsum Jensenius, Katerina Teleli and Margarida Leal.
The Great Human Filter er et KI-generert eksperimentelt funk- og nu-jazz-prosjekt. Prosjektet kombinerer generativ kunstig intelligens med menneskelig kuratering, og utforsker en tematiske kobling mellom teknologi, kreativitet og menneskelig dømmekraft.
The research exhibition Archival Intelligence examines the roles of today’s all-pervasive digital technologies, such as Artificial Intelligence, in extracting data from archives and museums for profit.
Dhvāni means “resonance” in Sanskrit. Resonances between sounding objects and between people are the starting point for this installation by Indian-born artist and thinker Budhaditya Chattopadhyay. In STUK’s courtyard, a web is stretched with hundreds of Indian ceremonial bells and other instruments, such as wind chimes and ghungroos. By means of a self-built artificial intelligence system, this resounding network responds to human presence: footsteps, voices, hand clapping. Through machine learning, the interconnected system improves its performance over the six weeks of Hear Here, creating a beyond-human resonant organism. In this way, Chattopadhyay links ancient musical traditions with contemporary technologies, inviting visitors to listen empathetically and step outside their judgmental “ego”.
This study explores the accuracy and usefulness of OpenAI’s large language models (LLMs), particularly focusing on a customized GPT model trained on a specific dataset of musicology research. The research compares the performance of the custom model against the general ChatGPT-4.o model in an academic setting. The customized GPT, tailored to retrieve information from a controlled set of scholarly articles, was tested by a group of musicology experts, including authors whose works were part of the dataset. Results indicate that the custom GPT generally provides more precise and research-based responses compared to the general model. However, issues such as hallucinations, inconsistent performance, and ethical concerns regarding copyright and the use of LLMs in academic work were observed. The study concludes that while customized GPTs can enhance academic research, their use should be approached with caution due to ongoing challenges in accuracy and ethical implications.
Innlegget presenterer forskningssenteret MishMash – Centre for AI & Creativity, et av Norges nasjonale forskningssentre for kunstig intelligens. Presentasjonen diskuterer hvordan KI kan forstås ikke bare som et verktøy, men som en aktiv medspiller i kreative prosesser. Med utgangspunkt i kunstnerisk praksis og forskning i skjæringspunktet mellom teknologi og kultur, belyses nye muligheter, utfordringer og etiske spørsmål som oppstår når KI inngår i kunstnerisk arbeid og kreative næringer.
First, I will present MishMash Centre for AI and Creativity, a new Norwegian research centre advancing AI to explore and shape human-machine creativity. Funded by the Research Council of Norway in 2025, the centre brings together artists, engineers, and scholars across disciplines to create, explore, and reflect on AI systems that augment creative practice while foregrounding agency, inclusion, and sustainability. Organized into seven work packages, the centre addresses technical challenges such as real-time multi-agent systems and hybrid symbolic learning methods, societal concerns including bias, copyright, and equitable value distribution, and applied domains spanning health, education, cultural heritage, and the creative industries.Second, I will present some of my own ongoing explorations into embodied AI, including inverse control, small language models, and distributed computing. This approach challenges current monolithic, generative models, suggesting an alternative future for creative AI.
Motion is at the core of how we experience and understand the world, express ourselves, and interact with others. At RITMO, we explore motion that is artistic, expressive, and interactive within a highly interdisciplinary research environment that integrates musicology, psychology, and technology. Increasingly, we are moving our research out of the lab and into the real world, where we can study people behaving as they normally do and capture unique occurrences that cannot be simulated in laboratory conditions. This transition is illustrated by the MusicLab and Bodies in Concert projects, which investigate bodily activity and experiences in performers and audience members during live concerts. From data collected during a series of symphony orchestra concerts, we are learning how musicians coordinate their expressive motion and how audiences synchronize in their bodily responses to the music. We are also learning how to adapt new technologies for real-world data capture, and exploring how captured data can be used for artistic purposes. In this talk, we will discuss some of the concepts, methods, and findings from this line of research.
When individuals use generative AI, idea diversity decreases sharply; when whole teams rely on the same tools, convergence compounds. No prior studies have examined how distributing different AI tools across team roles affects creative collaboration. This paper introduces the "AI as Fifth Team Member Model", which defines four roles: Research Coordinator, Visual Design Specialist, Space Planning Expert, and Presentation Coordinator. Each uses a different tool, through text-based analysis, image generation, 3D modelling and layout design, forcing heterogeneity into the team's creative process. A pilot showed that daily synchronisation protocols are essential for cross-role coordination. Future studies should test larger groups and measure diversity formally.
A frequently used perspective for theological analysis of AI is that of the Imago Dei, an application pioneered by Noreen Herzfeld. The Imago Dei concept highlights the “artificiality” so to speak (the very createdness), also of the human person. AI is then created in the imago hominis, while, in a third step, AI systems generate artificial objects: increasingly in the imago automati, as the Internet is taken over by agentic AI. To put AI into the context of creation theology and art, is, I think, a promising path to thematize also the aesthetically and religiously important aspects of the current worldwide project striving to simulate intelligence, but also life. In this paper presentation, I will investigate to what extent the thinking of Thomas Aquinas can be a resource for such an investigation into the dignity of artificial intelligence. Of course, Aquinas had no idea of digital technology and modern neurophysiology, but maybe his taxonomies and principles can still be of value for an intellectual engagement with the nature and worth of AI.iv
The rise of increasingly sophisticated simulations of human reasoning, creativity, and language presents many challenges to individuals, institutions, and societies. For religious and spiritual traditions navigating the tension between adoption and rejection, AI revitalizes long-standing debates on human nature, the relationship between science and faith, and the natural and supernatural. Simultaneously, it fuels both secular and religious radical forms of techno-criticism against the industrialization and rationalization of culture. Within the Catholic tradition specifically, AI is often met with skepticism, as computational processes are seen to lack human qualities such as consciousness, emotion, and understanding, a stance exemplified by the Vatican document Antiqua et Nova. While many current Christian responses to AI development focus on the ethical, environmental, and social risks of large-scale AI adoption, this paper investigates whether a Thomist framework can offer an alternative evaluation that avoids a binary antagonism between humanism and automation. In a discussion with Edward Feser's critique of AI in Immortal Souls (2024), the paper argues for understanding AI through the lens of art (ars) rather than mere mechanics. As biotechnology further blurs the boundary between the organic and the mechanical, a theology of creation and art may better balance human nature in relation to artificial simulations than a humanism based on the privilege of interiority. This paper suggests that Thomism provides intellectual resources helpful for developing such a perspective.
These days' almost manic attention to AI should also trigger a response in the field of art. Not necessarily a denial of AI, but an "celebration" of what it means to be human. Can reflecting AI through art lead us to 'rediscover' our human potential? Rediscover our unique abilities, what we take for granted: like being able to create community through music and dance, like dealing with complicated ethical and moral questions through theater and film, like understanding through the visual arts what we do not see in our daily reality?
These abilities are something we have cultivated over thousands of years, a process of formation that is both biology AND culture: Music is a human surplus phenomenon, most likely sprung from our language ability (Patel, A. 2010). Therefore, music learning has many common features with language learning (Solli, M., Aksdal, E. and Inderberg, J. P. 2021). Just as we learn a native language through being surrounded by it, and through participating in social communities where it is used, music has traditionally been learned through imitation and through participation in (musical) communities.
How will AI affect these uniquely human forms of forming community/common consciousness? Time as a prerequisite for process, process as a prerequisite for exploration, exploration as a prerequisite for reflexive judgment/creativity. We will share our artistic research from a studio recording session where we focused on the idea of 'Try and Fail' or 'Not knowing'
Special Focus: Modeling Life Systems: Art, Algorithms, Ecologies
Presentation of the National Library of Norway's collection of audiovisual materials, it's legal framework, provenance, availability, as well as it's possibilities for dissemination and computational analysis (MIR).
Legal interpretation has traditionally presupposed an interpreter: a situated subject
capable not only of giving meaning to legal texts but also of judgment, justification
and responsibility. Generative AI unsettles this assumption. Large language models
can now produce persuasive legal interpretations without intention, lived experience
or normative commitment. This paper asks what that capacity reveals about legal
interpretation itself. Drawing on more than a decade of research and teaching in
human rights and law and technology across the Global South and Global North, the
paper argues that generative AI is best understood not as the end of legal
hermeneutics, but as a test of its underlying assumptions. The ability of LLMs to
reproduce recognizable forms of legal argument does not establish that legal
reasoning is reducible to statistical prediction. It does, however, expose the extent to
which legal interpretation relies on inherited linguistic patterns, doctrinal conventions
and institutional practices. The argument becomes particularly consequential in
human rights law, where interpretation claims sensitivity to dignity, vulnerability and
lived experience. Because legal languages and traditions are unevenly represented
in computational systems, AI may also influence whose interpretations become
easier to reproduce and whose experiences remain difficult to render legally visible.
The paper ultimately distinguishes interpretive capacity from interpretive authority
and responsibility. Its central claim is that the legitimacy of legal interpretation lies not
simply in intelligence or persuasive reasoning, but in answerability: the possibility of
being called upon to justify, defend and bear responsibility for meanings that acquire
authority over human lives.
MishMash is one of the six national AI research centres funded by the Research Council of Norway from 2025, and the only one that joins technology with creativity. In this presentation, in the showcase of the national centres, I introduce the centre: seven work packages spanning music, visual art, literature, games, performance and human-centred AI; a consortium of more than 20 partners across Norway; and the argument that creative practice is both a testbed for AI systems and a driver of new AI research.
Music production and songwriting tools based on machine learning and artificial intelligence are part of every producer’s toolkit. Whether it is the use of stem splitters to clean up tracks, algorithms for mastering, or generative systems for sound creation and lyric manipulation, these tools have found a place in the modern music studio.
However, the rapid introduction of such tools raises many questions. Do they improve the creative process? Are algorithms trained with sufficient awareness of juridical and ethical challenges? Is the use of training data in accordance with existing laws and practices regarding copyright and patents? Do these tools affect artistic output, making music better—or less diverse? Is AI making music creation more accessible by lowering technical and artistic thresholds and enabling non-experts to perform tasks that previously required specialist skills?
Based on interviews, experimental work, and a literature review, this paper explores which AI-based tools are used in contemporary music production, how they are employed, and how they influence the creative process. Technical, juridical, and ethical aspects of different types of AI-driven tools are discussed.
The paper concludes with an analysis of how new workflows may affect revenue streams for music producers, songwriters, and artists.
Mixing in immersive formats, designed to place the listener inside a three-dimensional sound environment rather than in front of a left–right stereo image, allows for many creative opportunities beyond traditional stereo mixing. However, there are different immersive formats, each with its own strength and challenges.
This paper/performance/workshop explores the creative differences between mixing in Atmos, created by Dolby Laboratories and used in movie theatres and commercial 3D audio distribution, and ambisonics, a format that is used extensively in electro-acoustic music and VR.
The music used in the paper/performance/workshop is a sonification of Aurora Borealis/Northern Lights. With the use of positional signals from an antenna array positioned in Kilpisjärvi in Northern Finland, soundscapes and composed music are projected into an 3D audio dome and create a real-time sonic experience of the movement of the Aurora on the sky over the arctic parts of Norway, Sweden and Finland.
These compositions exist in both ambisonics and Atmos, and in the paper/performance/workshop the workflow and creative opportunities inherent in the formats are explored, along with a discussion of the challenges encountered when working in the different 3D arrays.
Participants are invited to explore the immersive mixes and remix the performances in real-time.
Aim / key questions: As generative AI becomes embedded in creative practice, the
speed of creation has never been higher and the temptation to skip the slow parts of
the work never greater. We ask: what does creativity actually require, and what is at
risk when AI is allowed to bypass those requirements? We approach this as an
empirical question about creative process — and as a starting point for a comparison
between human and machine modes of musical thinking.
Methods: This artistic research project documents a two-day recording session at
Grieghallen in Bergen, where we deliberately worked from a position of "try and fail"
and "not knowing" — refusing pre-planned outcomes, making sketches on the spot,
and staying with uncertainty long enough for something unexpected to emerge. We
treat the recording process as a case through which the preconditions of creative work
can be examined.
Results: The work surfaced a chain of preconditions: time enables process, process
enables exploration, exploration enables reflexive judgment — what we identify as
creativity itself. Each link depends on the one before. Generative AI tends to compress
this chain — offering averaged ideas, weakening ownership, and removing the
productive resistance the not-knowing depends on.
Implications: In a next phase, we will examine our findings in dialogue with the Robotic
Musicianship group at Georgia Tech (Weinberg et al.), whose improvising robots such
as Shimon raise the question from the opposite direction: what does machine
improvisation share with — and lack from — human musical thinking?
Value / originality: A practice-grounded contribution to MishMash, opening a
comparison between embodied, communal music-making and AI-driven musical
generation.
Globally, in the arena of everyday practices, AI systems have increasingly been causing a profound effect on contemporary everyday life across the globe. From surveillance to the Internet of Things and domestic consumption, from social media interactions to arts and culture, AI is taking over the processing of information to provide new perceptions and augmented experiences. At the core of this reconfiguration of technologically mediated everyday practice are datasets, used to drive and produce new narratives across wider ranges: consumer behavior and patterns, mobility, and immigration, post-human thinking, scientific in(ter)ventions, media production and propaganda, online and offline social formations, etc. In this context, the proposed panel presents the collective research of the newly formed Center for AI Ethics, Aesthetics and Creative Human Operations (CAIEAC) at The Art Academy – Department of Contemporary Art (KMD), University of Bergen, Norway. The centre aims to reimagine the integration of artificial intelligence in creative human operations and to challenge hegemonial AI tropes. By moving beyond the binary of utopian and dystopian paradigms, the centre embraces a “Prototopian" model that envisions continuous improvement in adjusting AI technologies to society. The centre fosters innovative and critical approaches to AI, focusing on computational aesthetics, the expansion of creativity through human-machine collaboration, and the development of new conceptual frameworks informed by art, media theory, and interdisciplinary research based on a reflective and inclusive AI landscape that integrates ethical considerations, addresses biases, and promotes decolonial and Indigenous knowledge into different AI infrastructures for a diverse society. The proposed panel will address the ethical lapses in AI with a regenerative approach to consciousness. Especially engaging with applied AI in the arts, the panel explores the creativity-induced resistance against a monolithic world of AI that populates contemporary everyday practices, as mentioned earlier. The panel will advocate for an ethical and inclusive AI system for the future that is emergent, self-reflective, and self-regulating, with an aesthetic inclination towards artistic experimentation and radical innovations by being susceptible to the questions of social justice and political agency.
This presentation explores the emergence of cloud-based sample platforms like Splice and Loopcloud and consider their potential decline in the age of AI-generated music. Sabrina Carpenter’s hit single “Espresso,” released on April 11th, 2024, put the spotlight on the ubiquitous use of online sample platforms in popular music. The songs’ main intrumental elements-guitars and drums-stem from two loops of producer Oliver’s popular pack “Power Tools Sample Pack III” on the sample platform Splice. This caused a surge of social media posts demonstrating how the instrumental track could be recreated in little under a minute. This form of sampling—both cheap and legal, fast and convenient—represents a distinctly different take on sampling than that commonly associated with “golden age hip hopproductions”, where samples are extracted from existing recordings (Brøvig 2023; McLeod and Dicola 2011; Schloss 2004). Besides being more efficient, these sample platforms’ royalty-free models allow producers to use samples freely without fear of legal action. Our presentation will begin by examining the factors leading to the emergence of cloudbased sample platforms. While the legal aspects might have contributed to the development of sampling platforms, we will also trace the platforms’ rootedness in less explored areas ranging from “library music,” to synthesizer preset cassettes and sample CDs bundled with music tech magazines (Cameron 2020). We will then discuss how these platforms, partly due to their mitigation of copyright issues, have contributed to transforming the sampling practices and aesthetics established by early hip-hop productions while also encouraging other forms of practices (Arrieta 2021). Lastly, we will discuss whether the advent of AIgenerated music technology has the potential to disrupt the sample industry altogether. This work will draw on research on sampling, copyright and musical platforms, and include insights gained from our interviews with producers of sample packs.
Generative AI is changing legal education in ways that are not confined to research,
writing or analytical efficiency. It also affects how students encounter the people and
experiences from which legal problems emerge. Drawing on work in law and
emotion, human rights pedagogy, clinical legal education and critical AI studies, this
chapter considers what these changes mean for legal empathy. Generative systems
may help students rehearse perspectives, question assumptions and reflect on
difficult material. At the same time, a fluent representation of another person’s
experience is not equivalent to understanding that experience, still less to assuming
responsibility for a professional judgment about it. The chapter uses the idea of
emotional anaesthesia to identify a particular educational risk: that technological
mediation may make ambiguity, vulnerability, cultural difference and narrative
difficulty easier to process by making them less demanding to encounter. It argues
for an approach in which AI remains supplementary to, rather than a substitute for,
the human encounters through which legal judgment is formed.
As a scholar of human rights and legal technologies with over a decade of teaching and research experience across the Global South and North, I have witnessed how digital tools both expand and constrain access to justice. Legal technologies-ranging from algorithmic decision-making to online courts and predictive analytics-promise efficiency, yet they often reproduce structural inequalities and silence marginalized voices. This paper explores the frontiers where Legal Tech intersects with legal anthropology. Focusing on the lived experiences of individuals and communities subject to digital legal systems, I examine how technology reshapes fundamental notions of fairness, authority, and accountability. Drawing on human rights frameworks and ethnographic insights, I highlight the tension between automation and dignity, standardization and contextual nuance. I argue that anthropology’s interpretive and human-cantered approaches are indispensable for understanding justice in the digital age. By tracing stories from diverse contexts across the Global South and North, this contribution shows how ethnography can illuminate what technical discourse obscures, ensuring that the future of digital justice remains grounded in human rights and lived realities.
As Legal Tech tools increasingly mediate intellectual property (IP) registration, enforcement,
and adjudication, the cultural biases embedded in these systems pose serious risks. Most AI-
driven IP tools are built on Western legal logics, linguistic norms, and data sources. This
limits their capacity to recognize, protect, or fairly evaluate culturally specific forms of
expression and innovation—particularly from the Global South or marginalized communities.
Drawing on my experience as a Legal Tech specialist and professor of human rights who has
taught for over a decade across both the Global South and North, this paper offers a grounded
critique of current AI applications in IP. I focus on how automated trademark classifiers,
copyright enforcement bots, and patent search engines can unintentionally reproduce
epistemic injustice, cultural erasure, and exclusion from national and global IP regimes. The
paper argues for the development of multicultural AI frameworks in IP Legal Tech that
integrate three core principles: localized and multilingual data training sets to ensure cultural
relevance; participatory co-design processes involving underrepresented creators to
incorporate diverse perspectives; and the incorporation of diverse legal traditions, including
indigenous and customary law, to broaden the epistemic foundations of AI tools in
intellectual property. This approach recognizes AI not merely as a tool for legal automation
but as a mechanism that shapes cultural legitimacy, national identity, and access to economic
empowerment. By embedding cultural competence and ethical pluralism into Legal Tech, we
can move toward IP systems that reflect the full fabric of global nations and narratives. By
embedding cultural competence and ethical pluralism into Legal Tech, we can move toward
IP systems that reflect the full fabric of global nations and narratives.
This paper develops the concept of “code-switching for survival” to explain how journalists adapt to contemporary forms of repression. Moving beyond its sociolinguistic meaning, the concept is used to capture linguistic, legal, digital, and strategic practices that help journalists navigate legal harassment, surveillance, censorship, and algorithmic suppression. Drawing on examples from the Global South, the paper examines the use of metaphor, satire, coded language, encryption, pseudonymous publishing, and legal strategies as forms of journalistic resilience. It also introduces the idea of “algorithmic code-switching,” whereby journalists adapt their content to opaque moderation and ranking systems. The paper proposes an integrated legal-tech-ethical framework linking these practices to international human rights standards and responsible AI governance. It argues that journalists should be understood not only as targets of repression, but also as active agents who design strategies of resilience in increasingly complex media environments.
AI literacy is becoming part of everyday legal education as students and teachers increasingly encounter generative AI in research, writing, and classroom work. This presentation looks at how law schools are responding to these changes across different educational settings, with particular attention to experiences from the Global South. Drawing on published work, institutional materials, course information, and student-led initiatives, it considers how local resources, languages, teaching cultures, and access to technology shape the way AI is introduced into legal education. The presentation highlights practical forms of engagement, including classroom experimentation, interdisciplinary projects, and uses of AI connected to access to justice. Rather than proposing a single model, it argues for approaches that are flexible enough to reflect different educational realities. Experiences from the Global South are especially valuable in this discussion, not as isolated examples, but as sources of ideas that can enrich wider conversations about responsible, practical, and socially aware AI literacy in legal education.
Across the Global South, migration governance is increasingly shaped by digital
infrastructures- from biometric identification and facial recognition to algorithmic profiling.
In these systems, the migrant body is transformed into a datafied entity: tracked, categorized,
and governed not only by law but by code. This paper examines the legal and conceptual
implications of this shift, where digital infrastructures fragment the migrant body into
dispersed data points subject to classification and control beyond traditional legal oversight.
Drawing on research in legal technology and human rights, the paper argues that datafication
produces a new mode of governance-embodied algorithmic control-that challenges
foundational legal notions of autonomy, privacy, and personhood. Existing rights
frameworks, premised on a coherent, rights-bearing subject, are ill-equipped to address the
opacity and transnational reach of algorithmic systems. In response, the paper proposes a
multidimensional approach: reframing the right to the body to include its digital dimension;
extending accountability to private and transnational actors; fostering South–South legal
collaboration; centering migrant voices in technological design; and rethinking legal
personhood in data-driven contexts. By confronting the digital fragmentation of the migrant
body, the paper calls for a rights-based and ethically grounded approach to migration
governance- one that recognizes data as part of human dignity and seeks a more just and
inclusive digital order.
Software. One implementation of quantity of motion — the average speed of a body part, band-limited to 0.2-5 Hz, in millimetres per second — for optical marker data, body-worn accelerometers and force-plate centre of pressure, together with the readers, resampling rules, scaling measures and alignment methods that surround it.
Foredraget handler om hvordan kunstig intelligens kan brukes i kreative prosesser, spesielt innen kunst og utdanning. KI utfordrer tradisjonelle forståelser av kreativitet, som tidligere har vært definert gjennom originalitet og verdi, og at nye perspektiver også inkluderer intensjon og autentisitet.
Foredraget understreker forskjellen mellom produktivitetsøkning og kreativitet: KI er svært effektiv til å effektivisere produksjon, men dette er ikke det samme som å styrke den kreative prosessen. Når kreative oppgaver automatiseres, kan også verdien og eksklusiviteten av resultatet reduseres.
KI kan brukes i flere deler av kreative prosesser, som idéutvikling, eksperimentering, produksjon og kuratering, og kan fungere både som verktøy, samarbeidspartner eller materiale. Samtidig vil KI ofte trekke mot det generelle og statistisk sannsynlige, noe som gjør menneskelig perspektiv og kunstnerisk intensjon fortsatt viktig. Foredraget fremhever også at virkelig kreativ bruk av KI ofte krever teknologisk kompetanse og programmering, og at uten dette blir bruken lett overfladisk. Hovedpoenget er at KI ikke bare bør brukes til effektivisering, men til å utvide det kreative handlingsrommet og muliggjøre nye kunstneriske prosesser og uttrykk.
In this presentation, Alexander Refsum Jensenius explores the practical and theoretical dimensions of running radically interdisciplinary research centres, focusing on his experiences with RITMO and the newly established MISHMASH Centre for AI and Creativity. He introduces the "coffee machine" philosophy, which advocates for physical colocation and social meeting points as essential tools to overcome institutional silos and bridge the diverse research motivations of fields like musicology, informatics, and psychology. Jensenius highlights the innovative potential of this approach through projects that translate artistic research into medical applications, such as using dance analysis software to screen infants for cerebral palsy and investigating the impact of musical stimuli on biological cells. He further details the MusicLab initiative, which scales data collection to full symphony orchestras to study embodied music cognition and human behaviour in real-life concert settings. The talk concludes by introducing MISHMASH, a national consortium dedicated to fostering human-centric AI that integrates artistic practice with technological development while navigating ethical challenges such as copyright and the preservation of cultural heritage.
Trenger vi egentlig musikere, forfattere og filmprodusenter nå som KI kan gjøre jobben? Vi tar diskusjonen om hvordan KI påvirker kreativ næring og kunstneriske prosesser.
Innlegget undersøker begrepet «kunstnerisk intelligens» i lys av dagens KI-utvikling, med utgangspunkt i forståelsen av kunstig intelligens som infrastrukturelle systemer heller enn autonome, intelligente aktører. Det drøfter hvordan kunstneriske praksiser kan synliggjøre og utfordre slike systemer gjennom eksperimentering, deltakelse og kritisk refleksjon. Med eksempler fra samtidskunst vises hvordan kunst kan åpne «den svarte boksen» og bidra til nye innsikter i forholdet mellom teknologi, samfunn og kunnskapsproduksjon. Innlegget posisjonerer kunstnerisk utviklingsarbeid som en form for kunnskapsutvikling med relevans for en KI-drevet offentlighet.
Panelsamtalen «Risiko og motstandskraft i kulturens infrastruktur – det neste tiåret» samlet Camara Lundestad Joof (Dramatikkens hus), Kirsti Mathiesen Hjemdahl (Cultiva), Sveinung Rudjord Unneland (Den uferdige institusjonen), Øystein Strand (Kulturdirektoratet) og Synne Tollerud Bull (Høyskolen Kristiania), moderert av Hild Borchgrevink. Samtalen tok utgangspunkt i hvordan kultur i økende grad formes av infrastrukturer, systemer og distribusjonslogikker, og drøftet risiko og handlingsrom i møte med plattformbaserte medieformer. Det ble særlig lagt vekt på behovet for å utvikle robuste og fleksible kulturinfrastrukturer, samt rollen til offentlig finansierte institusjoner og høyere kunstutdanning i å legge til rette for eksperimentering, kunnskapsutvikling og langsiktig motstandskraft.
Arrangementet Design Agentics: Creative R&D x AI undersøker kunstig intelligens som en integrert del av design- og kunstpraksis, ikke bare som verktøy, men som infrastrukturell og agentisk aktør. Gjennom en studentpresentasjon av egenutviklede AI-baserte verktøy og en påfølgende panel- og rundebordsdiskusjon med forskere og bransjeaktører, tematiserer arrangementet hvordan kreative praktikere kan forholde seg kritisk og operativt til eksisterende AI-systemer. Fokus ligger på spørsmål om handlingsrom, makt og design i møte med ferdigdefinerte teknologiske infrastrukturer, samt muligheter for å omforme, tilpasse eller motsette seg disse. Arrangementet avsluttes med lanseringen av forskningsgruppen CRAITR ved AHO.
Artist and researcher Budhaditya Chattopadhyay will discuss his body of work around sounding and listening to sculpt and give shape to two broad theoretical frameworks, namely Auditory Situationism and Unmedia, within which his works can be contextualised; both ideas are hinting at manifestations of decolonial thought intervening into existing sound studies canon, which Chattopadhyay enters with an outsider, nomadic, and polemical impulse.
Hva skjer med vår opplevelse av virkelighet, kropp, natur og kreativitet når grensene mellom det menneskelige og det syntetiske blir mer flytende?
Samtalen har ikke til hensikt å konkludere om kunstig intelligens er bra eller dårlig for kunsten. Sammen skal vi heller undersøke hva som skjer med oss som skapende mennesker, som publikum, og kanskje også som naturvesener, når teknologien begynner å produsere bilder, idéer og identiteter som tidligere bare kom fra menneskelig erfaring.
Fotografiens Hus ønsker velkommen til en samtale som trekker på kunst, økologi og filosofi for å undersøke hvordan kunstig intelligens påvirker hvordan vi skaper, sanser og møter verden rundt oss på.
Alexander Refsum Jensenius
;
Jesper Mardahl
;
Simon Kimmel
;
Martin Eyerer
;
Roland Sillmann
;
Philipp Grefer
Future-facing cultural ecosystems require new forms of collaboration across public, private, and civic actors. This panel examines best practices in building intersectional institutions and clusters that integrate diverse disciplines, and leaders from art, music, science, policy, to communities, and funding models.
This project explains how I got into biology-related research and the potential of using musical, artistic, and creative methods to get obtain both artistic and scientific results.
AI keeps faking it until it makes it as infrastructure. Vibing effortlessly with wearing language as interface for doomstyle hype, timewarping efficiency, subscription-based fate and a long generative etc.
So, let's talk about something else…
The roundtable moves between creative practice and research, speculation and error, embodiment and idiocy. Beyond ritual denunciation or loving embrace, we open a conversation about the pleasures, traps, politics, and odd possibilities of working with these tools to learn (and act on) how they set the terms. As the slogans dry out: how to resist, how to misuse, how to play inside systems built to smooth everything into an average slop(py) shape. After the refusal, after the fatigue, after the sales pitch and the creative ditch, what else?
Organized by AHO's CRAITR research group
Denne presentasjonen forteller om det nye norske KI-senteret Mishmash. Rundt 200 forskere vil i årene fremover jobbe med både utfordringer og muligheter ved bruk av KI i kunst og kultur, særlig knyttet til opphavsrett, personvern og fremtiden for kreative fag. Målet er å utforske og utvikle ansvarlig bruk av KI i blant annet musikk, utdanning, helse, kulturvern og kreativ næring.
On April 8, 2026, the University of Oslo (UiO) hosted a launch event in the University Aula for MishMash, one of Norway's six new national research centres for artificial intelligence. The primary objective of MishMash is to create, explore, and reflect on AI for, through, and in creative practices.
A presentation held at the annual NORA AI conference about MishMash. The centre will conduct research on how AI promotes and challenges creativity, including issues related to copyright and regulation. The research results are relevant for many actors, and especially for creative industries such as film, music, design and literature, and for public and private actors in health, education and cultural heritage.
Alexander Refsum Jensenius
;
Nils Petter Mørland
;
Ingjerd Egeberg
;
Christopher Pahle
;
Hans Ole Rian
;
Åsmund Færavaag
I likhet med en rekke bransjer, står kunst- og kulturfeltet overfor store endringer preget av digitalisering og fremveksten av kunstig intelligens (KI). Representanter fra statlige teaterinstitusjoner, selvstendige scenekunstnere og forskere møtes til samtale om hverdagen for scenekunstnere og framtida for vår bransje i lys av den teknologiske utviklingen.
The closing session of the SDG conference will also represent an opening – towards provoking thoughts and emotions, plural perspectives and anticipation of futures simultaneously too far and too near to grasp. The evening will bring exhilarating possibilities of ontological shifts, deep listening and embodied perception through collaborative human-technology movement and critical conversations. But let’s not forget, there will also be the comfort of food, laughter and relaxation after two full, invigorating conference days where we have aimed, and hopefully succeeded, to hold complexity without slipping into solutionism or despair.
Alexander Refsum Jensenius presenterer om sin forskning som omfatter blant annet kroppslige dimensjoner ved musikkopplevelse og -utøvelse, som kombinerer perspektiver fra musikkvitenskap, psykologi og teknologi. Hans arbeid har som mål å frembringe både vitenskapelige og kunstneriske resultater.
Fagdagen «KI og musikk» ved NLA Høgskolen i Oslo satte søkelys på hvordan kunstig intelligens påvirker musikkfeltet, med særlig vekt på kreativitet, kunstneriske prosesser, opphavsrett og musikkbransjens utvikling. Gjennom faglige innlegg, samtaler og musikalske eksempler ble blant annet bruk av generativ KI, eierskap og rettigheter, algoritmiske komposisjonsprosesser og forholdet mellom menneskelig og maskinell kreativitet diskutert. Fagdagen var primært rettet mot studenter på masterprogrammet i utøvende musikk, men var åpen for alle ansatte og studenter ved NLA i Oslo. Medvirkende var Ole Fredrik Norbye, Njål Ølnes, Torstein Slåen og Mathieu Lacroix.
Can AI be creative? The talk starts from Boden's definition, novel and meaningful, and shows why the first half is cheap for machines and the second is where the human work remains. It sorts AI into rules, learning, and evolution, traces seventy years of artists working with all three, and argues that the interesting questions concern co-creation rather than replacement: control, intention, and ownership. It presents MishMash, Norway's national centre for AI and creativity, with its seven challenges across performance, health, education, industry, and heritage, and closes with what creative practice teaches scientists: small models, embodied agents, reproducible workflows, and provenance.
Panelsamtale som undersøker hvilken rolle kunst og kunstnerisk forskning kan spille i utviklingen av framtidens kunstige intelligens. Med utgangspunkt i MishMash, nasjonalt forskningssenter for KI og kreativitet, diskuteres hvordan KI ikke bare påvirker kunst og kultur, men hvordan kunstneriske og humanistiske perspektiver kan bidra til å forme teknologien. Samtalen retter særlig oppmerksomhet mot kreativitet, menneskelig erfaring, demokratiske verdier, kunstnerisk frihet, opphavsrett og kulturelt mangfold. Kunstnere, forskere, teknologer og representanter fra kultur og arbeidsliv diskuterer hvordan kunstnerisk og tverrfaglig kunnskap kan bidra til mer ansvarlig, mangfoldig og menneskeorientert utvikling av KI.
Dette samsvarer godt med MishMash sitt uttalte mål om å undersøke KI for, gjennom og i kreative praksiser, og å bruke kunstnerisk utforskning som inngang til kritiske spørsmål om KI og samfunn.
NE #00: New Embeddings of/for Artistic Intelligence was a participatory workshop presented at Ars Electronica 2026 that explored how new forms of artistic intelligence might emerge when artists, institutions, scholars, scientists, and technologists organise around shared needs rather than disciplinary boundaries. The workshop asked how AI might support, rather than determine, such collaborations, and how alternative infrastructures for artistic and interdisciplinary practice might be developed.
Structured as an exchange rather than a conventional presentation, participants articulated what they need in relation to generative AI, what they can contribute, and what they refuse. These contributions included conceptual approaches, technical and institutional infrastructures, artistic methods, knowledge, and resources. Participants clustered around points of convergence and translated these into concrete offers, requests, and possible collaborations recorded in a shared ledger.
The workshop initiated the New Embeddings series as an experimental format for building interdisciplinary connections around artistic intelligence and generative AI through collective exchange and the formation of new “neighborhoods” of practice.
Synne Tollerud Bull
;
Jakob Margit Wirth
;
Gwen Rakotovao
;
Sarah Kordecki
;
Merel Visse
;
Ryan Woodring
;
Janine Davidson
This session invites contributors to share their artistic research approaches and strategies for navigating, resisting, or intervening in times of societal transition. Against a backdrop of rapid policy shifts, the impacts of AI and surveillance capitalism, the deprioritization of the climate crisis, rising authoritarianism, and threats to democracy, the discussion will explore: What can artistic research do in response to the challenges of our time?
Recent breakthroughs in AI—foundation models, ChatGPT, large language models, and vision and audio systems—are often framed as software revolutions. Yet they depend fundamentally on advances in nanofabrication: the extreme miniaturization of logic and memory enabled by EUV lithography and foundries such as TSMC. Large language models are economically and technically viable only because computation, memory, and energy efficiency have been radically reconfigured at the level of silicon. This lecture reframes recent advances in AI as an intensification of mineral memory within the archive. The demand for comprehensive, real‑time, AI‑mediated access to cultural heritage across all media and art forms increasingly binds the archive to mineral and infrastructural regimes of computation. It expands the archive’s material footprint—chips, energy, water, and carbon—posing new ethical, operational, and sustainability challenges for cultural institutions, researchers, and artists. New cross‑disciplinary research alliances—linking archival and humanities research with semiconductor engineering and life‑cycle sustainability modeling—are needed to understand the metallurgical and ecological consequences of contemporary memory systems.
Kunstig intelligens påvirker det meste om dagen, også musikklivet og musikkbransjen. Hva skjer når KI topper hitlistene og alle kan lage sin egen musikk? Vil KI ta over alt, eller blir vi lei og vil ha mer menneskeskapt musikk? Hva er mulighetene for at KI-generert musikk kan bidra positivt til å hjelpe folk med f.eks. ADHD til å konsentrere seg og Parkinson-pasienter til å bevege seg?
An update on the development of MishMash. The centre aims to create, explore, and reflect on AI for, through, and in creative practices. More than 200 researchers investigate AI’s impact on creative processes, develop innovative co-creative AI systems and educational strategies, and address AI’s ethical, cultural, legal, and societal implications in creative domains.
Hvordan ble MishMash-søknaden til, og hva kan konsortiet bak senteret bety for kunstnerisk utviklingsarbeid i Norge? I dette innlegget forteller jeg om arbeidet med søknaden til Forskningsrådets utlysning av nasjonale KI-sentre, om hvordan konsortiet med mer enn 20 partnere ble satt sammen, og om mulighetene for at kunstneriske institusjoner kan bruke senteret til å utvikle egne prosjekter og søknader videre.
I will talk about how developing AI systems over the last 25 years has helped me better understand how humans move, act, think, and feel. Now more than ever, we need to incorporate human perspectives into new AI developments, while also critically exploring new AI-based systems and reflecting on how they change humanity in different ways.
In this workshop, I will lead the participants into exploring their own micromotion through standstill and slow-movement exercises. The focus will be on both physical and mental stillness. In the end, we will explore how mobile phone-based apps can be used for sonic microinteraction.
Hva er forskjellen på en KI-assistent og en KI-agent, og hva betyr den for administrativ databehandling ved et universitet? Med utgangspunkt i egne erfaringer med agenter i forskning og administrasjon går jeg gjennom hva agentene trenger for å virke, hva som er god praksis, og hvordan samskaping med en agent ser ut i praksis, med eksempler fra reiseregninger, lederstøtte, CV-er, personaldata, styrepapirer, nett og arkiv. Innlegget ender i tre ønsker: tilgang til egne data gjennom API og nedlasting, systemer som kan føre dialog, og rom for agenter.
Hvordan kan KI-agenter brukes i undervisning, og hva bør vi holde fast ved? Med utgangspunkt i en åpen lærebok med web-apper, en wiki og et åpent verktøy for videoanalyse i emnet MUS2640 forteller jeg om drømmen fra 2003 om et åpent økosystem for læremidler, og hvordan agenter nå gjør den mulig. Prinsippet er KI utenfor timen og mennesker i timen: agentene forbereder, studentene og underviserne møtes.
South Korea is one of Norway's priority partner countries outside Europe, and few Norwegian research groups collaborate with Korean AI research. In this presentation for the Ministry of Education's special envoy at the Norwegian embassy in Seoul, HK-dir and the Research Council of Norway, I introduce RITMO, the Centre for Interdisciplinary Studies in Rhythm, Time and Motion, and MishMash, the national Centre for AI and Creativity, and outline the centre's plans for international collaboration and the existing contacts among MishMash partners with Korean institutions, research organisations and artists.
Hva kan kunstig intelligens bety for en musikkinstitusjon som setter klassisk musikk i sentrum? Med utgangspunkt i forskningen ved RITMO og MishMash-senteret går jeg gjennom muligheter i klassisk musikundervisning, fra forberedelse og samspill til vurdering: digitale akkompagnatører, analyse av øvingsvideo for skadeforebygging, transkripsjon og notasjon, og KI-modeller trent på komponister og utøvere. Mer maskin kan også bety mer menneske.
When AI enters a creative process, authorship does not disappear, it redistributes. Who is actually doing the creating? In this keynote I present MishMash, the Norwegian Centre for AI and Creativity, show examples of AI in creative work from our research, and argue that the risk is not that AI replaces human creativity but that organisations stop noticing whose judgement a tool encodes and whose is quietly displaced.
Panel discussion during the MusicLab research concert with the hip-hop group Sinsenfist, in which musicians and audience members were recorded with audio, video and motion sensors. Alexander Refsum Jensenius moderated the conversation with researchers Finn Upham and Kjell Andreas Oddekalv about what happens in the bodies of those who play and those who listen during a live performance, and what the concert measurements can tell us.
Is artistic research research? And if so, of what kind? In this short talk, I propose the Artistic Readiness Level (ARL), from an initial artistic impulse to a consolidated and reproducible artistic work with demonstrated impact, alongside the technology and societal readiness levels used in research funding, and ask whether music in a given project is a subject, object or method.
Kunstig intelligens er allerede i musikken, men hva gjør den med oss som lytter, spiller og lager? I dette innlegget viser jeg eksempler fra forskningen på RITMO og det nye MishMash-senteret: forskningskonsertene i MusicLab, små musikkapper som Tap Bloom, Pinch Bass og Firefly, og hva som skjer når KI blir noe mer enn et verktøy.
Ny teknologi har alltid hatt evnen til å forenkle og effektivisere etablerte arbeidsoppgaver, men med det følger også frykten for at funksjoner og individer blir overflødige. Hva skjer når teknologien strekker seg forbi det kjente og utfordrer oss til å utforske noe nytt?
Kunstig intelligens (KI) gir oss muligheten til å stille disse spørsmålene på en ny og spennende måte. Hvilke nye kreative uttrykksmuligheter kan KI åpne for? Hvordan kan kunsten utfordre og subvertere KI? Hvordan kan vi forstå lyd, bilde, video og litterær tekst generert av KI i forhold til autentiske kunstneriske uttrykk? Hvor overlapper og utfyller de hverandre, og hvor er de fundamentalt forskjellige?
Kunsten har et ansvar for å gå i kritisk dialog med KI, for å bidra til en dypere forståelse og debatt om KIs natur og samfunnspåvirkning. Hvordan skal kunstutdanningene ta dette ansvaret, gjennom kunstnerisk utviklingsarbeid, forskning og utdanning?
Vi inviterer til en debatt der vi sammen utforsker disse spørsmålene og mer. Bli med oss i en diskusjon om kreativitet, subversjon og autentisitet i møte med kunstig intelligens. Velkommen!
This workshop is targeted at students and researchers working with video recordings You will learn to use MG Toolbox, a Python package with numerous tools for visualizing and analyzing video files. This includes visualization techniques such as motion videos, motion history images, and motiongrams; techniques that, in different ways, allow for looking at video recordings from different temporal and spatial perspectives. It also includes some basic computer vision analysis, such as extracting quantity and centroid of motion, and using such features in analysis. MG Toolbox for Python is a collection of high-level modules that generate all of the above-mentioned visualizations.The toolbox is relevant for everyone working with video recordings of humans, such as in linguistics, psychology, medicine, human-computer interaction, and educational sciences.
As researchers, we are increasingly using emerging technologies, such as multiple mobile eye tracking, virtual reality, and physiological indicators (e.g., heart rate and respiration) to study professionals’ individual and collaborative work practices. In this workshop, we will demonstrate how these technologies can be provided to professionals in various fields (e.g., education, healthcare, business, engineering, the arts) as a resource for self-reflection, enabling them to study and improve their own practices.
The goal of this workshop is to introduce and facilitate participants to experience novel approaches that use these emerging technologies and tools to help practitioners study their own skills and understand their learning processes. We will also show how focus groups and stimulated recall interviews can encourage and guide professionals to discover ways to incorporate these new technologies into their practice as resources for reflection and growth.
The workshop’s theme is educational practice and research, with a focus on showing how we can offer teachers theoretically driven and empirically validated methodologies for witnessing the micro-processes of collaborative mathematics learning. We will show and discuss how multiple mobile eye-tracking and virtual reality can be used in educational practice and for teacher training and professional development.
This approach and these emerging technologies are applicable not only in education, but also in all other fields of research that aim to study individual and collective practices, as well as professional learning, during the process of acquiring new skills or improving existing ones.
Kunstig intelligens påvirker det meste om dagen også musikklivet og musikkbransjen. Men hva er egentlig KI og hva er utfordringer og muligheter innenfor kunst og kultur? Presentasjonen diskuterer ulike pedagogiske tilnærminger og gir eksempler på hvordan det nye KI-senteret MishMash skal angripe problemstillingene.
A presentation of MishMash, a large Norwegian consortium dedicated to exploring the intersection of AI and creativity. Our primary objective is to create, explore, and reflect on AI for, through, and in creative practices. We will investigate AI’s impact on creative processes, develop innovative CoCreative AI systems, and address AI’s ethical, cultural, and societal implications in creative domains.
A presentation of MishMash, a large Norwegian consortium dedicated to exploring the intersection of AI and creativity. Our primary objective is to create, explore, and reflect on AI for, through, and in creative practices. We will investigate AI’s impact on creative processes, develop innovative CoCreative AI systems, and address AI’s ethical, cultural, and societal implications in creative domains.
Fra leksikon til psykolog og kunstner – på rekordtid har kunstig intelligens blitt en stor del av livene våre. Hvordan bør kunstfeltet møte denne nye teknologien? Vil KI gjøre tegnere og illustratører overflødige, eller er dette snarere en enorm mulighet for utøvende kunstnere?
Den kunstige intelligensens frammarsj fortsetter å være den største kulturelle og samfunnsmessige omveltningen siden den industrielle revolusjonen. Siden fjorårets konferanse har det skjedd vanvittig mye, derfor inviterer vi igjen til en dag fylt med internasjonale nøkkelpersoner, banebrytende prosjekter og nye perspektiver på hvordan KI endrer måten vi utvikler, produserer og opplever film.
Alexander Refsum Jensenius
;
Kristin Bergtora Sandvik
;
Birgitte Grimstad
;
Andreas Hoem Røysum
;
Lars Klevstrand
På konsert føler vi samhold med fremmede, viser forskning. I et kort øyeblikk samler musikken oss. Hvordan kan musikk også samle oss i urolige tider? Flere artister jobber for fred, på ulike måter. Møt noen av dem på Scene Domus Bibliotheca! Hva er det med akkurat musikk som forener oss? Bli med på musikksnakk med artistene Birgitte Grimstad, Lars Klevstrand og Andreas Røysum. Du møter også fredsforsker Kristin Bergtora Sandvik. Her vil musikkprofessor Alexander Refsum Jensenius lede samtalen med ulike spørsmål knyttet til tematikken – kanskje svarer de på ditt spørsmål også? Samtalen er beregnet for et publikum uten faglig bakgrunn i temaet.
I forbindelse med utstillingen Conscientia på Gamle Munch arrangeres en samtale om bevissthet og det å skape.
Utgangspunktet for tema til utstillingen er bevissthet og forhold knyttet til det å skape.
En del av utstillingen tar utgangspunkt i en serie med selvportretter av Randi Wøien basert på MR bilder tatt av hennes eget hode. Bildene representerer et sett av intrikate mønstre i ulike størrelser og sammensetninger og kan refereres til ulike organer, andre vesener og ren natur. Samtidig er de en representasjon av kunstneren slik hun er satt sammen i sitt eget hode. Keramiker Jorid Krosse lager objekter med form og mønster som tar inspirasjon fra naturen og kan relateres til organiske strukturer, hoder og andre vesener. I samspill med maleriene vil de keramiske objektene settes i en relasjon til det kroppslige.
Samtalen om bevissthet og det å skape bruker utstillingen som et utgangspunkt til å få belyst hva den skapende prosessen kan bety for vår egen utvikling og hvordan hjernen fungerer og responderer på skapende prosesser. Tema for samtalen vil være forholdet mellom kunst og bevissthet, om relasjonen mellom maleri og objekt og om hvordan det å skape kunst kan påvirke vår forståelse av oss selv og omgivelsene.
For tiden forskes det mye på hva som faktisk skjer i hjernen når man skaper noe. Vi har fått med oss to av de fremste forskerne på temaet fra universitetet i Oslo.
Alexander Refsum Jensenius er professor i musikkteknologi ved Universitetet i Oslo, hvor han også leder RITMO Senter for tverrfaglige studier av rytme, tid og bevegelse og MishMash Senter for KI og kreativitet. Han forsker på hvordan lyd og musikk påvirker kropp og sinn, bevisst og ubevisst.
Tor Endestad er førsteamanuensis i kognitiv- og nevropsykologi på univeristetet i Oslo og er tilknyttet Ritmo. Han leder FRONT neurolab og forsker på kognitiv psykologi og kognitiv nevrovitenskap med fokus på hjerneavbildningsmetodikk. Pågående forskningsprosjekter omfatter studier av basale mekanismer i oppfattelse av rytme og tid, oppmerksomhet og hukommelse.
Til å moderere samtalen har vi fått med oss Per Snaprud. Han er vitenskapsjournalist og før det hjerneforsker. Han arbeider i det Stockholm baserte magasinet Forskning og Framsteg og har tidligere vært virksom ved Dagens Nyheters og Sveriges Radios vitenskapsredaksjoner. Han er også forfatter av boken «Medvetandets återkomst, om hjärnan, kroppen och universum».
Victoria Johnson er fiolinist, underviser ved Institutt for musikkvitenskap og deltar i ulike forskningsprosjekter ved UiO. Hun har hatt solokonserter blant annet under Festspillene i Bergen, Ultima, Borealisfestivalen og Soundwaves i London. Hennes lidenskap for samtidsmusikk har resultert i flere bestillingsverk og plateinnspillinger. I denne sammenhengen vil hun spille musikk som er direkte komponert til bildene og objektene i utstillingen.
Panel discussion with Robertina Šebjanič, Anetta Mona Chişa, Alexander Refsum Jensenius. Moderated by Benedetta D'Ettorre.
This panel examines the boundary zones where artistic and scientific approaches intersect, entangle, and permeate into one another. Bringing together practitioners working across more-than-human ecologies, technological imaginaries, and embodied research, the conversation will explore how meaningful collaboration can emerge from inter- and trans-disciplinary exchange.
Rather than framing art and science as opposites, we ask how their methods can become mutually generative; how artistic mindsets can expand scientific inquiry, and how scientific perspectives can deepen artistic experimentation. The session aims to discuss questions related to collaborative ethics, shared vocabularies, and the value of embracing “noise” as a catalyst for new forms of knowledge-making.
This thesis investigates how synchronized whole-body movement shapes the experience of listening
to music. The two research questions ask whether floor movement changes the listening
experience, and whether the specific character of the movement matters for that experience.
To address these questions, a one-degree-of-freedom robotic floor was designed and built from
scratch. The system, named Harmonic Audio-Reactive Platform (HARP), lifts a person standing
on it in a vertical rolling motion derived from features extracted from the music. Two motion patterns
were implemented for use in the study: a simple pattern oscillating at the beat frequency,
and a complex pattern that combines two sinusoids whose amplitudes vary with the spectral content
of the music. The hardware, software, and trajectory generation are described in detail in the
thesis, and form a methodological contribution alongside the empirical findings. Six participants
took part in a within-group user study. Each experienced three songs from contrasting genres
(classical, EDM, and metal) under three motion conditions (no motion, simple, and complex),
giving nine conditions per participant. A qualitatively-driven mixed methods design was used.
Semi-structured interviews were analyzed with reflexive thematic analysis, alongside Likert ratings,
amplitude adjustment logs, synchronization measurements, and video observations. Three
themes were constructed from the interviews: Enjoyment, Emotion, and Congruence. Across
all data sources, the most consistent finding is that motion pattern preference is personal. No
single pattern worked for everyone, and the same pattern could feel mismatched or stressful to
one participant and meaningful to another. The movement was mostly received as adding to the
listening experience, with Likert ratings, qualitative themes, and participants’ own descriptions
of real-world use pointing the same way. Synchronization between music and motion shaped the
experience but its specific role could not be settled within this study.
Hører du på musikk i 528 Hz, 432 Hz eller 8D kan det gjøre underverker for den mentale helsen din, ifølge en rekke videoer på sosiale medier. Er det sant – eller bare tull?
Mase på folk om å danse sjølv om dei ikkje vil? Ja, - eller nei takk til KI-musikk? Skal 12-åringen få vite at han syng falskt? Og: Satse på musikken - eller safe? Med Tine Thing Helseth, Alexander Jensenius og Ragnhild Folkestad. Programleiar Kjersti Anderdal Bakken.
I kveld var en rekke personligheter fra musikkmiljøet samlet til debatt ved Universitetet i Oslo. Temaet var «Kan musikk skape fred?». Blant deltakerne var Birgitte Grimstad og Lars Klevstrand , som har underholdt med musikk i flere tiår. Debatten ble ledet av blant annet professor i musikkvitenskap ved UiO, Alexander Refsum Jensenius.
Et stort, nytt forskningssenter er bevilget 173 millioner. Det skal undersøke skjæringspunktet mellom kunstig intelligens (KI) og kreativitet, blant annet ved å se på bruk av KI i kunstneriske prosesser.