MishMash Centre for AI and Creativity

MishMash is 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.

MishMash explores the meeting point of humans and machines with art and science

News

First vacancy: Administrativ koordinator (Deadline: 15 September)

Why?

Human creativity has both shaped and been shaped by technological developments. Today, human creativity faces unprecedented challenges and opportunities brought by Creative AI, machine systems that can produce results that are both novel and meaningful. This raises several important questions: to what extent are Creative AI systems genuinely creative, how do they differ from human creativity, and how can humans and machines be co‐creative? Furthermore, what are the societal implications of Creative AI, how will producers’ and consumers’ attitudes towards AI‐generated creative content develop, and how can creative approaches to AI have an impact beyond the cultural and creative sectors?

We view artistic exploration as an excellent entry point for engaging in critical discussions about AI and its implications for human‐machine interaction and society. Artistic research has been integral to computer‐based AI development since the early days of computer science, exemplified by early rule‐based systems for music composition and painting. Today, learning-based systems can produce all sorts of artistic products, and several have become popular commercial products, such as Dall‐E (images), ChatGPT (text), and Suno.ai (music).

MishMash aims to expand current knowledge and pioneer new CoCreative AI systems that allow partnerships between humans and machines. We believe researchers and practitioners from creative disciplines are uniquely positioned to develop AI‐based technologies and to do so responsibly, reflecting on their ethical challenges and potential drawbacks.

There are many possibilities with Creative and CoCreative AI systems, but also numerous challenges and knowledge needs:

Challenge 1: How can we design and implement real‐time AI systems for immersive, dynamic, and ethical human‐machine collaborations in artistic performances?
Challenge 2: How can artists integrate AI into their creative processes while maintaining control and addressing biases, cultural implications, and environmental impact?
Challenge 3: How can AI‐generated content and Creative AI systems impact health and well‐being, and be integrated into therapeutic practices while considering empathy, consent, and equity?
Challenge 4: How can Creative AI be integrated into education to enhance learning and foster AI literacy while considering diversity, justice, inclusion and well‐being?
Challenge 5: How can AI enhance innovation in the creative and cultural industries while addressing copyright, rights management, ethical challenges, sustainability, and equitable revenue distribution?
Challenge 6: How can AI enhance the preservation, accessibility, and representation of cultural heritage in archives, libraries, and museums while ensuring ethical and legal compliance?
Challenge 7: How can Creative AI enhance human agency, control, and expression in problem‐solving while adhering to physical, legal, and societal constraints during the creative process?

How?

MishMash will bring together a large multidisciplinary and cross-sectoral group of researchers and practitioners from the arts, humanities, social and natural sciences, design, and engineering. MishMash organises its theoretical and methodological “mishmash” into a structured “mesh,” where projects and activities intersect across themes, approaches, and perspectives.

The WPs are designed around seven core themes, addressing the challenges outlined in the previous section. While some WPs focus on leveraging AI in creative—primarily artistic—applications, others explore the innovative use of AI in adjacent domains, fostering a dynamic interplay between art, science, and society. The work will be conducted by combining a multitude of scientific and arts-based theories and methods, which can be summarised in three interconnected research approaches:

CREATE: making AI-based systems, tools, artworks, and related frameworks and policies. This includes theories and methods from computer science, engineering, and various types of art and design, emphasising creating CoCreative AI systems that prioritise human agency, environmental sustainability, and democratisation of AI technologies.
EXPLORE: using AI-based systems in creative practice and seeing how creative methods can be applied in other domains. This includes investigating how AI can enhance creativity, foster innovation, and support learning and well-being using theories and methods from psychology, therapy, educational sciences, and cultural heritage.
REFLECT: critically studying and discussing the impacts of AI on humans, human creativity, various cultures, and society at large. This includes theories and methods from the humanities and social sciences to ensure responsible AI development and use.

The centre will be a lively, virtual research environment, with weekly online meetings, biweekly work package check-ins, monthly thematic seminars, regular public workshops, life-long learning events, and bi-annual symposia with lectures, performances, and exhibitions.

What?

WP1: AI for artistic performances

WP Leaders: Kyrre Glette (UiO) / Morten Qvenild (NMH) / Georgios Marentakis (HiØ)

This WP focuses on how real-time interaction with AI systems transforms the creative process in applications such as music and art performance, interactive installations, and gaming. We will emphasise AI systems that facilitate continuous interactions between humans and machine agents, especially multiple and embodied AI agents. Countering the current trends of very large models with hard-to-control outputs, we will focus on balancing data-based approaches with artists’ knowledge and search-based methods to achieve personalised and novel outputs. In contrast to WP2 (see below), the emphasis is on supporting live, dynamic, and interactive performance rather than creating a fixed final creative product. Our use cases require synchronous, rich, continuous feedback that unfolds naturally and does not obstruct performance during real-time co-creative improvisation and collaboration. Designing AI systems that can provide and interpret such feedback requires a broader understanding of what must be “explainable” when interacting with AI during creative performance. We posit that embodied AI systems that can sense, act, and behave in a way that is intuitively understood by humans offer unexplored opportunities for spontaneous co-creation in artistic performance and exploration that reach far beyond the current state of the art.

Research Questions:

RQ1.1: How can we design real-time multi-agent and embodied AI systems with rich dynamics to enable immersive and expressive interfaces and interactions?
RQ1.2: How can we integrate and balance data-, knowledge-, and search-based approaches to achieve personalised and enhanced expressive control, and how can the system’s autonomy be adapted to the allocation of control between the human and the machine?
RQ1.3: Which multimodal data are required to determine continuously changing human emotions, and how can we interpret them algorithmically to emulate human empathy during performance?
RQ1.4: How can we map the cybernetic, aesthetic, and ethical implications of human-machine relationships and explore a system’s creative potential?

Approaches:

CREATE: new AI algorithms, open-source software and hardware, and human-machine interaction methods for real-time artistic applications that offer ethical and inclusive technologies for diverse artistic use.
EXPLORE: existing and custom-built interactive AI-based software and hardware solutions in real-world settings, such as concerts, installations, and gaming.
REFLECT: on current challenges and barriers to artistic real-time applications of AI to inform the creation of new algorithms and systems.

WP2: AI in artistic processes

WP Leaders: Budhaditya Chattopadhyay (UiB) / Sashi Komandur (INN) / Synne Tollerud Bull (Kristiania)

This WP focuses on AI systems used in producing works associated with the arts and creative industries, including visual arts, film, VR/XR, literature, performing arts, games, and music. Prompt-based, machine-learning systems are becoming normalised in many workflows, and practitioners and professionals are increasingly aware of their benefits and costs. Concerns include the effects of “outsourcing” creative work and decision-making to AI systems and the hegemonic cultural biases present in many commercial tools. Creativity shapes how communities see themselves and imagine new possibilities. When AI systems reinforce dominant cultural patterns and marginalised alternative perspectives, they risk narrowing public discourse, diminishing cultural diversity, and strengthening existing norms at the expense of exploration and innovation. This raises critical questions about cultural agency: Who decides what stories are told, what images are seen, and what ideas shape our shared reality? This WP will explore new challenges in the creative process, challenging the concept of “neutrality” in AI systems and examining embedded biases. The goal is to ensure that creative tools contribute to more inclusive, diverse, and democratic cultural futures, balancing artistic control with machine dominance to preserve human aesthetic and artistic integrity.

Research Questions:

RQ2.1: How can artists integrate generative AI systems into their ideation and production processes while maintaining creative autonomy and avoiding the risk of machine-driven homogenisation?
RQ2.2: What are cultural and ethical implications for artists and audiences when AI systems integrate into creative processes, and how can these be addressed to ensure diversity and originality?
RQ2.3: How can artists and creative producers employ generative AI tools to push the boundaries of artistic expression while critically engaging with the biases embedded in these systems?
RQ2.4: How can artistic exploration help expose limitations of current AI technologies and inspire the development of more inclusive, artist-centred tools that foster innovation and human agency?

Approaches:

CREATE: new AI-based artistic productions and tools that prioritise artist-centred workflows, enabling creative control and innovation across diverse fields.
EXPLORE: existing AI tools to identify their potentials, limitations, and challenges, focusing on ethical and legal implications and cultural biases.
REFLECT: on how the interplay between AI and human creativity exposes new insights into the act of creation, its impact on audiences, and the social impact of art on contemporary society.

WP3: Creative use of AI for health and well-being

WP Leaders: Claire Ghetti (UiB) / Andreas Bergsland (NTNU) / Jonna Vuoskoski (UiO)

This WP investigates how AI-generated creative content (images, music, literature, media, etc.) impacts human health and well-being. It also examines the use of AI in creative arts therapies to promote mental health and physical well-being and how novel health research methods involving AI can enable new knowledge generation. Engaging in creative processes can promote health and well-being. AI tools offer opportunities for augmenting human creativity, yet their use also raises concerns about the potential devaluation of human qualities like empathy and autonomy. We will explore how AI can both support and create challenges for well-being, creativity, and emotional expression. Ethical considerations are central to this WP, especially how AI can be used responsibly to avoid reinforcing inequalities or biases. Our approach emphasises anti-oppressive practices and seeks to support historically marginalised groups through inclusive AI applications in the arts. Collaboration with users and stakeholders is key to creating innovative solutions while ensuring health-promoting AI interventions are relevant and ethically sound. Critical disability perspectives are incorporated to ensure that AI systems in arts for health are inclusive and accessible for all.

Research Questions:

RQ3.1: How do humans perceive, experience and relate to AI-generated creative content?
RQ3.2: How can Creative AI systems enhance emotional well-being and facilitate therapeutic outcomes?
RQ3.3: What can AI offer research in mental and physical health that incorporates the creative arts?
RQ3.4: How are aspects of consent, equity and justice safeguarded when AI is integrated into creative processes in health contexts?

Approaches:

CREATE: reflexive and user-informed “failsafe” frameworks and guidelines for disability-inclusive integration of AI into the arts for health and well-being.
EXPLORE: how AI-generated content and interactive AI systems affect human behaviour and emotions.
REFLECT: on the benefits and risks to human health and well-being of integrating AI into creative processes.

WP4: Creative use of AI in education

WP Leaders: Hilde Norbakken (UiA) / Sidsel Karlsen (NMH) / Fredrik Graver (INN)

The rapid inclusion of AI into education presents transformative opportunities and challenges for teaching and learning alongside significant pedagogical, ethical and practical issues. This WP explores how education can harness AI to enhance learning opportunities, foster creativity, and support critical thinking and AI literacy. The educational sector is currently characterised by numerous local initiatives to adopt commercial AI tools. However, high-quality, open education resources—especially on Creative AI—are scarce, with hardly any available in Norwegian. There is a clear need for a unified effort to advance AI literacy in Norwegian schools and enhance the understanding and application of Creative AI in higher education and lifelong learning. The aim is to equip future practitioners and educators with the competence to navigate AI’s complexities while providing current educators with resources to minimise a generational gap in AI literacy. WP4 will collaborate closely with researchers from other WPs to incorporate insights from ongoing research into educational programs and curricula and to influence technological developments from an educational point of view.

Research Questions:

RQ4.1: How can Creative AI be effectively integrated to enhance teaching and learning and foster human creativity?
RQ4.2: How can the artistic use of AI within creative and fine arts education challenge and develop hierarchies of knowledge production in education and research?
RQ4.3: What measures can ensure that ethical considerations such as diversity, justice, fairness, inclusion, privacy, trust, and accessibility are central to implementing AI in creative education?
RQ4.4: How can the relationship between AI in formalised education and the application of AI in broader artistic practice be mapped and analysed to advance the use of Creative AI?

Approaches:

CREATE: educational material, models and methods for broad applications through artistic and pedagogical practices with AI, emphasising ethical issues related to diversity, justice, fairness, inclusion, privacy, trust and accessibility.
EXPLORE: the artistic and pedagogical use of AI in formal, non-formal and informal learning contexts, including developing a shared understanding of AI literacy for creative and fine arts education.
REFLECT: on the implications of using AI in education to suggest frameworks and policy recommendations for using AI in education.

WP5: AI in the Creative and Cultural Industries

WPLs: Ragnhild Brøvig (UiO) / Irina Eidsvold-Tøien (BI) / Jon Marius Aareskjold-Drecker (UiT)

Technological innovation has consistently disrupted creative industries’ business models, revenue streams, and legal frameworks. These disruptions have intensified with the rise of digital platforms, streaming services, and AI technologies. AI’s ability to generate cultural content brings new opportunities and significant legal and ethical concerns. Key issues include copyright, moral rights, and the ethics of training AI on human artists’ work, voices, and other bodily expressions without proper agreements. Furthermore, the vast amount of AI-generated content challenges existing revenue-sharing models, requiring a rethinking of traditional frameworks. However, AI can also offer innovative solutions, such as AI-driven identification systems for rights management. Such systems could help harmonise and complete international databases for ownership and metadata, enhancing transparency and efficiency. AI could also facilitate more equitable distribution of royalties across different regions and sectors. This WP is dedicated to exploring both the challenges and solutions that AI presents to the legal and structural dynamics of the creative industries by investigating current practices. It also aims to connect this awareness to the research and development carried out throughout the MishMash network and to disseminate knowledge, ethical and legal guidelines, and newly developed tools to various stakeholders. As part of this effort, Norinnova, a technology transfer office located in Tromsø, will contribute to identifying and commercialising new tools and solutions developed under the MishMash umbrella. Researchers from NORSUS, the Norwegian Institute for Sustainability Research, will write a Life Cycle Assessment (LCA) report to address the environmental impact of new Creative AIs. Furthermore, legal scholars involved in MishMash will share guidelines with legal stakeholders.

Research Questions:

RQ5.1: How does training AI systems on existing artistic expressions and recorded voices raise issues related to privacy, copyright, human rights, private law, and contract law, and what regulatory frameworks are needed to address these legal challenges and guide policy-making?
RQ5.2: What are ethical, environmental, privacy, and safety considerations when training AI models on large datasets for artistic applications, and what strategies can mitigate these concerns effectively?
RQ5.3: How do AI technologies affect the structures of the creative industries, and what business models and regulatory frameworks are needed to accommodate these changes while securing sustained development of ethical practices and human creativity?
RQ5.4: What role can AI play in developing global databases for rights management and ensuring comprehensive and accurate ownership records in the creative industries?

Approaches:

CREATE: academic and cultural awareness through publications and dissemination about the current and future states of affairs, robust infrastructures for data management, recommendations for sustainable business models, and appropriate legislation for handling emerging AI-generated content.
EXPLORE: AI’s impact on artists’ rights and positions within the cultural industries and develop strategies to balance the economic benefits of AI integration with the need to maintain job opportunities.
REFLECT: on how to maintain and develop culturally and economically sustainable business models, regulatory frameworks, and political strategies to address AI-related challenges.

WP6: AI for cultural heritage

WPLs: Ingrid Romarheim Haugen (NB) / Arnulf Mattes (UiB) / Olivier Lartillot (UiO)

Archives, libraries, and museums (the “ABM sector” in Norway) are central institutions for preserving, sharing, and communicating human culture. The National Library of Norway is distinguished by its extensive collection of high-quality digital resources and the advanced Digital Humanities Lab. It is essential to integrate all these resources and numerous local collections in Norway into a cohesive digital framework and further connect them to the European Cultural Heritage Cloud. This necessitates automated, intelligent curation of the vast collections. One focus will be on music, leveraging the cutting-edge computational musicology research at UiO in collaboration with the National Library. We will pioneer hybrid AI models by blending machine learning with musicology and cognition-based symbolic AI. Particular attention will be dedicated to minority cultural expressions, including Norwegian folk music, Sámi joik and world chant cultures. We aim to create models for creating, curating, and analysing comprehensive catalogues transferable to other contexts and cultural heritage areas. The public sector must lead in these technologies, ensuring that powerful new capabilities are used ethically and inclusively. This approach seeks to empower institutions, artists, and the public to leverage archives, exploring the influence of past cultural expressions on contemporary creativity while promoting respectful citation and avoiding plagiarism.

Research Questions:

RQ6.1: How can we significantly advance AI to effectively discover, organise, and showcase the vast richness of cultural heritage and creative works in all forms?
RQ6.2: How can AI technologies be used ethically and inclusively to protect and nurture minority cultural expressions while considering AI’s broader impact on cultural practices?
RQ6.3: How can we advance AI research to enable national institutions to effectively guard against the risks of unchecked and exploitative AI use in cultural heritage?
RQ6.4: How can we develop interlinking systems within cultural heritage and creative works to enhance rights management and highlight their profound impact on contemporary creativity?

Approaches:

CREATE: innovative AI technologies to automatically transcribe, analyse, classify, interconnect, and showcase vast, unstructured multimedia datasets, highlighting the richness of creative works.
EXPLORE: the effectiveness of current and custom AI systems in preserving and nurturing Norwegian cultural expressions, focusing on minority cultures.
REFLECT: on the ethical and legal threats of AI usage in cultural heritage and develop policies and guidelines to ensure responsive, ethical and inclusive use of AI.

WP7: Human-centric AI for Creative Problem-Solving

WP Leaders: Carsten Griwodz (UiO) / Baltasar Beferull‐Lozano (SimulaMet) / Kjetil Nordby (AHO)

This WP explores how a person or group can use Creative AI for task-specific problem-solving. The tasks considered in this WP range from industrial design, where artistic methods are integral to design processes, to emergency rescue scenarios, where imminent problems must be solved by creatively using available resources. We target creative goal-based practitioners, including professionals as diverse as designers, filmmakers, human operators in industrial settings, and emergency service personnel, and we adopt the principles and ideas of Creative AI that MishMash co-creates through its three perspectives. To achieve this in a goal-driven context, new frameworks must be developed that give creators freedom, surprise, control, and inspiration and allow them to evaluate, select, discard, and apply AI’s contributions. The creative process must be interactive, ranging from iterative prompt-based exploration to real-time collaboration with an embodied AI. The process should support creators in addressing their professions’ requirements and other practical challenges, finding pragmatic solutions instead of circumventing them. A key challenge here is potential conflicts between artistic freedom and the practical requirements that the creator must fulfil. AIs developed in this WP will be limited by stricter boundaries than others—from the laws of physics to legal frameworks, such as realism constraints. We will go beyond informed AI approaches in our focus on encoding these limitations into the development principles for Creative AIs. WP7 will generate new knowledge of algorithmic, personal and societal challenges when applying Creative AI in creative practices in collaboration with other WPs facilitated by MishMash’s cross-cutting perspectives.

Research Questions:

RQ7.1: How can we integrate Creative AI in creative problem-solving processes to maintain and develop human agency, control and personal expressive capabilities?
RQ7.2: How can we use algorithmically emulated empathy to achieve a greater sense of human agency and empowerment for humans?
RQ7.3: How can interfaces for AI and AI-supported services be designed to enhance user experience and transparency, making co-creative processes more accessible?
RQ7.4: To what extent can we personalise and customise Creative AI systems that extend to a wide range of applications and contexts, allowing the definition of generic frameworks?

Approaches:

CREATE: AI algorithms that can empower human creativity in pursuing tasks with external goals while remaining within (learned) bounds regarding physical, legal, emotional, social and other constraints.
EXPLORE: how Creative AI algorithms can empower humans while ensuring their sense of agency and ownership by observing, understanding, and adapting to human expression.
REFLECT: about the perception of creativity in problem-solving, ranging from the ability of an AI system to separate recreation from creativity, the creator’s intent, to the perception of a user or an observer of the creation.

When?

The plan is to formally start the centre in December 2025, recruit doctoral and postdoctoral fellows during the spring of 2026 and get up to full speed from the autumn of 2026.

MishMash Gantt chart

Who?

Management group

Alexander Refsum Jensenius (UiO), Director
Daniel Nordgård (UiA), Deputy director
Ida Jahr (INN), Deputy director
Thomas de Ridder (UiB), Research advisor
Nina Rundgren (UiO), Head of administration

Ida Jahr, Daniel Nordgård, Alexander Refsum Jensenius MishMash will be directed by Alexander Refsum Jensenius (UiO) together with deputy directors Ida Jahr (INN) and Daniel Nordgård (UiA). (Photo: UiO)

Work package leaders

Work Package	Lead	Sidekick 1	Sidekick 2
WP1: AI for artistic performances	Kyrre Glette (UiO)	Morten Qvenild (NMH)	Georgios Marentakis (HiØ)
WP2: AI in artistic processes	Budhaditya Chattopadhyay (UiB)	Sashi Komandur (INN)	Synne Tollerud Bull (Kristiania)
WP3: Creative use of AI for health and well-being	Claire Ghetti (UiB)	Andreas Bergsland (NTNU)	Jonna Vuoskoski (UiO)
WP4: Creative use of AI in education	Hilde Norbakken (UiA)	Sidsel Karlsen (NMH)	Fredrik Graver (INN)
WP5: AI in the Creative and Cultural Industries	Ragnhild Brøvig (UiO)	Irina Eidsvold-Tøien (BI)	Jon Marius Aareskjold-Drecker (UiT)
WP6: AI for cultural heritage	Ingrid Romarheim Haugen (NB)	Arnulf Mattes (UiB)	Olivier Lartillot (UiO)
WP7: Human-centric AI for Creative Problem-Solving	Carsten Griwodz (UiO)	Baltasar Beferull‐Lozano (SimulaMet)	Kjetil Nordby (AHO)

Scientific Advisory Board

Benoit Maujean (Head of Technicolor Research, France)
Catherine Fisk (Prof. law, UC Berkeley, USA)
Jon McCormack (Prof. creative computing, Monash University, Australia)
Jyoti Mistry (Prof. film, Gothenburg University, Sweden)
Nancy Baym (Senior Principal Research Manager, Microsoft, New England, USA)
Pamela Burnard (Prof. arts, creativities and educations, University of Cambridge, UK)
Philippe Pasquier (Prof. interactive arts and technology, Simon Fraser University, Canada)
Psyche Loui (Assoc. Prof. creativity and creative practice, Northeastern University, USA)
Ravi Kiran Sarvadevabhatla (Assoc. Prof. computer vision and machine learning, IIIT Hyderabad, India)
Sebastian Risi (Prof. creative AI, IT University of Copenhagen, Denmark)
Xavier Serra (Prof. music technology, Universitat Pompeu Fabra, Spain)
Zhang Qian (Prof. music and recording art, Communication University of China, China)

Partners

+ Norwegian research partners

+ Other Norwegian partners

In alphabetical order:

+ International partners

Numerous international academic and non-academic partners will also be involved, and we will set up an affiliate program for others to join the network and participate in relevant activities.

Funding

More information

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