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Publikasjoner
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Diego Marin-Bucio
(2026).
A Framework for Human–AI Dance Creation: The Machinic Movement Matrix.
I Patrice Guyot & Gregoire Bosselut (Red.),
MOCO '26: Proceedings of the 10th International Conference on Movement and Computing.
Association for Computing Machinery (ACM).
ISSN 9798400725005.
s. 1–9.
doi:
https:/dl.acm.org/doi/10.1145/3802842.3802849.
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This article proposes a conceptual framework for analyzing human–machine co-creation in dance through the lens of embodied interaction and human–AI collaboration. While the integration of AI in the performing arts has expanded rapidly, critical tools for evaluating the nature and degree of machine participation in computational creativity and interactive performance remain limited. To address this gap, the paper introduces a three-axis analytical model that characterizes human–AI interaction through generativity, responsiveness, and agency distribution. Together, these dimensions form a taxonomy of machinic agency in choreographic processes, classifying machine roles as tools, catalysts, puppets, or collaborators.
This work contributes to the growing field of dance technology by providing a theoretical framework and analytical vocabulary for understanding how kinematic communication and relational agency unfold in creative practice. It further proposes a set of conceptual categories—intermedial dance, choreorobotics, high-tech puppetry, AI dance, cyborg dance, and human–AI dance—to distinguish among diverse modes of human–machine performance interaction, offering researchers and artists a structured approach for analyzing and designing embodied human–machine dance collaborations.
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Diego Marin-Bucio, Anne Danielsen, Noumouke Doumbia & Rainer Polak
(2026).
Memory in performance: kinesthetic and procedural dimensions of skill acquisition in dance improvisation.
Frontiers in Psychology.
17.
doi:
10.3389/fpsyg.2026.1751590.
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Improvisation is central to creative behavior across artistic and everyday domains, yet it is often portrayed as either pure freedom or rule-bound execution. While research in music and dance has shown that improvisation draws on structured kinesthetic vocabularies, less is known about how cultural rhythm and embodied memory interact in real time within and across genres. This study addresses that gap through ethnographic fieldwork in West Africa, where the first author, trained in contemporary dance, engaged in learning and performing Malian djembe dance. Drawing on autoethnography with a phenomenological orientation, alongside participant observation and conversations with Malian drummers and dancers, the analysis examines how kinesthetic and procedural memories inform real-time performance. Findings suggest that improvisation operates through culturally specific ways of sensing and attending to movement: dancers navigate genre-specific repertoire, rhythmic cues, and bodily affordances to evoke and transform embodied material. However, rather than merely reproducing fixed repertorial units , dancers also reconfigure embodied resources such as movement qualities in responsive and inventive ways. Our research supports the view of improvisation as structured play rather than unbound invention and advances the discourse by emphasizing the reconstructive play of embodied recall—how cultural and personal memories are recomposed in performance. Overall, the study contributes to understanding improvisation as a cognitive and cultural process: not the free invention of form but the creative reorganization of embodied memories within shared perceptual and rhythmic systems.
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Diego Marin-Bucio
(2025).
Dancing Embryo: Enacting Dance Experience Through Human-AI Kinematic Collaboration.
Documenta: tijdschrift voor theater.
ISSN 0771-8640.
42(1),
s. 247–277.
doi:
10.21825/documenta.93276.
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This paper explores the intersection of dance, human experience, and artificial intelligence (AI), focusing on how AI can engage in dance-like movements through kinematic co-creation with human performers. The study challenges traditional notions of dance, which are typically centered on human physicality and expressivity, by demonstrating how AI-generated movements can evoke meaningful dance experiences. The project, Dancing Embryo, is a collaboration between a dancer-choreographer and a computational scientist to create an interactive AI capable of generating and transforming dance movements. The AI dancer, designed using motion data from contemporary dancers, participates in real-time performances by synchronizing features of its movements with a human dancer. This work expands the definition of dance to include non-human agents and emphasizes co-creativity between humans and machines. The paper discusses the technological, philosophical, and artistic implications of AI dance, proposing that the experience of dance can be perceived and completed through human interpretation, even when performed by a machine.
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Diego Antonio Marin Bucio
(2024).
Consciencia intuitiva en la construcción de experiencias kinestésicas: un análisis estructural y fenomenológico de la creación dancística.
Corpo Grafías Estudios críticos de y desde los cuerpos.
ISSN 2390-0288.
11(11),
s. 92–103.
doi:
10.14483/25909398.19823.
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El cuerpo atraviesa diferentes estados durante la creación de danza colectiva, su comunicación con otros cuerpos (al igual que la conexión con el suyo propio) abarca una compleja interacción que, además, sigue sensaciones imaginativas sugeridas por el coreógrafo. Este artículo expone, a través del análisis estructural de una pieza coreográfica, los momentos de identificación kinestésica ocurridos en y entre los bailarines durante su creación. El análisis sigue la metodología de Spiegelberg para el análisis fenomenológico y la metodología de Anca Giurcesco para análisis estructural dancístico, con el objetivo de comprender cómo la relación entre las ideas del coreógrafo toman forma en y a través de los cuerpos de los bailarines. El texto define conceptos como las ‘formas de congruencia’, desencadena preguntas sobre la consciencia interoceptiva durante la búsqueda de congruencia entre respiración y movimiento colectivo, y muestra la coherencia entre la propuesta poética del coreógrafo y su interrelación física objetiva.
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Diego Antonio Marín Bucio
(2023).
Danza y co-creatividad kinestésica Humano-IA.
MAGOTZI Boletín Científico de Artes del IA.
ISSN 2007-4921.
11(23),
s. 1–5.
doi:
10.29057/ia.v11i22.10684.
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La interacción humano-maquina en la danza no es un fenómeno nuevo, sin embargo, la evolución de la Inteligencia Artificial (IA) en los últimos años permite nuevos escenarios donde se plantean novedosos métodos de colaboración creativa entre la inteligencia humana y la artificial. Desde un enfoque interdisciplinario, este artículo provee un análisis de distintos softwares para la creación coreográfica y sintetiza los hallazgos provenientes de la colaboración creativa entre el autor y un bailarínde IA, los cuales fueron presentados en el Leverhulme Centre for the Future of Intelligence en la Universidad de Cambridge (Reino Unido). El autor concluye que para co-crear danza con una IA no basta con utilizarla, sino que es fundamental propiciar una experiencia donde el humano y la maquina puedan exponerse a una influencia mutua que no se limite al razonamiento lógico, sino que se base en la intuición kinestésica.
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Diego Antonio Marín Bucio
(2021).
Dance creative processes during the Covid-19 pandemic. File 1: social distance in the studio.
Academia Letters.
ISSN 2771-9359.
1(1).
doi:
10.20935/AL3664.
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The article documents and analyzes how the community of dance experienced COVID-19 Pandemic in some different cities and contexts. In this file, the analysis focuses on the physical contact during rehearsals and dance lessons with three different cases around France, as well as reflections about the socio-cultural conditions of the dance community and the future of dance on the screens.
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Diego Marin-Bucio
(2024).
Encarnando lo artificial: danza y co-creatividad humano-IA.
Universidad Latina de América.
ISBN 9786077030263.
170 s.
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"Encarnando lo artificial" ["Embodying the artificial"] examines how dance changes when humans create with AI, asking whether AI can truly dance, co-create, or only act as a tool. Drawing on theory, history, fieldwork, and the author’s own artistic practice, the book proposes a framework for distinguishing forms of human–machine interaction in dance and introduces the Machinic Movement Matrix as a way to analyze agency, communication, and collaboration. It argues that genuine human–AI co-creation depends on reciprocal, embodied communication rather than simple automation. The book also addresses the aesthetic, ontological, and ethical stakes of posthuman dance in an era of generative AI.
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Diego Marin-Bucio
(2024).
Hacia una danza posthumana: encarnando lo artificial.
Paso de Gato.
ISBN 9786078584727.
143 s.
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Hacia una danza posthumana ["Towards a posthuman dance"] questions the boundaries of artistic creation by testing the experience of dancing in an artificial intelligence (AI) entity. This synthesised edition of "Encarnando lo artificial" presents recent experiences of dance creation with machines and introduces concepts and terminology for understanding human-AI interaction in the performing arts. The author also presents a synthesis of the reflections arising from his collaboration with an AI dancer.
The author expresses a perspective far removed from anthropocentric premises in order to break with the conventional understanding of dance, challenging concepts such as the body and creativity. He also reflects on the ethics of its application in the performing arts and its impact on the cultural industries.
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Diego Marin-Bucio
(2026).
Kinetic listening: Exploring Dance Rhythm as Embodied Temporality in Movement.
doi:
https:/www.nofod.org/wp-content/uploads/NOFOD_2026_LHI_Netu%CC%81tga%CC%81fa_.pdf.
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This research presents the development and initial pilot results of Kinetic Listening, a techno-sensory methodology for dance pedagogy and choreographic creation with visually impaired participants, based on the real-time sonification of body movement.
The project explores how integrating auditory and kinaesthetic perception—of one’s own and others’ movements—can support learning, memorization, and composition without reliance on visual mediation. Using inertial sensors connected to MIDI systems, movement is translated into sound, generating a sonic-kinetic vocabulary through which motion can be experienced simultaneously as auditory and spatial structure. From an interdisciplinary perspective, Kinetic Listening proposes sound as both a compositional tool and a perceptual anchor for developing motor memory and spatial coordination. In doing so, it challenges the visual hegemony in dance pedagogy and advances multisensory, inclusive models of choreographic transmission. The study follows a qualitative methodology combining ethnography, movement analysis, and experimental choreographic laboratories with participants with diverse visual conditions. The process unfolds across phases of technological development, methodological exploration, and pedagogical implementation. Preliminary results from pilot studies in Mexico and Norway suggest that movement sonification enhances spatial orientation, choreographic recall, and collective movement-making through sensorimotor listening
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Diego Marin-Bucio
(2026).
Improvisation and interaction in djembe dance.
doi:
https:/www.uio.no/ritmo/english/projects/djembedance/events/djembedance-symposium/.
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This presentation examines how dance improvisation emerges as a coherent, culturally meaningful, and interactionally situated flow of movement. Drawing on two studies from an article-based PhD project, Memory in Performance and Interaction, Structure, and Style, it considers improvisation from both experiential and relational perspectives. The first part explores how kinesthetic memory and thinking-in-movement enable dancers to generate and adapt movement in real time. Rather than being either completely spontaneous or predetermined, improvisation emerges through embodied experience, culturally learned movement possibilities, and the changing conditions of the present moment. The second part turns to djembe dance, examining how improvisation is further shaped through interaction between dancers and musicians. Through examples of motif loops, rhythmic offers and calls, movement qualities, and stylistic variation, the presentation shows how structure, style, and interaction operate interdependently. It argues that improvisation is not simply an expression of individual choice, but an embodied and relational process through which movement remains both adaptable and culturally recognizable.
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Sunniva Monclair Bøe, Elise Koppang Frøjd, Alexander Refsum Jensenius, Diego Marin-Bucio, Benedikte Wallace & Olivier Lartillot
(2026).
Debatten raser om KI i kulturfeltet: Trenger vi egentlig musikere, forfattere og filmprodusenter nå?
[Journal].
Forskning.no.
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Norske forskere vil finne ut hvordan kreative utøvere kan være med på å utvikle kunstig intelligens – og motsatt.
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Diego Marin-Bucio
(2025).
The Origins of Intelligence – A performative statement on the primacy of movement.
doi:
https:/diegomarin.art/portfolio/the-origins-of-intelligence/.
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This choreographic performance interrogates the foundations of consciousness and the role of the body in the emergence of intelligence. The work traces the tension between biological evolution and artificial cognition, asking whether intelligence can exist without movement—or thought without sensation. Guided by enactivist perspectives, the piece unfolds between the microscopic pulse of organic life and the glitch aesthetics of computational environments. Through this interplay, human physicality meets digital motion, composing a rhythmic architecture between the living and the synthetic.
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Diego Marin-Bucio
(2025).
Machinic Movement Matrix: A framework and tool for human-AI dance-creation.
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The Machinic Movement Matrix (MMM) is a conceptual framework for analyzing and designing human–machine creative interaction in dance. Developed through practice-led research combining dance anthropology, posthumanist theory, and AI design, the MMM offers a structured method for identifying how artificial systems participate in—or fall short of—genuine creative collaboration. Rather than focusing on the aesthetic outcomes of human–machine interaction, the MMM examines the underlying creative roles, levels of interactivity, and power dynamics that shape these processes.
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Diego Marin-Bucio
(2025).
Matriz de Movimiento Maquínico (MMM): Una herramienta conceptual sobre la creación de danza humano-máquina.
doi:
https:/masters.filescat.uab.cat/muet/classe-magistral-amb-diego-marin-bucio/.
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This lecture introduces a conceptual framework for mapping the ontological roles of technology in choreographic creation. Drawing on case studies of AI-integrated works, it examines human–machine interaction and the redistribution of agency across dancers, choreographers, and computational systems. The resulting framework offers a practical tool for distinguishing when AI functions as an instrument and when it participates as an active co-creator in dance.
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Diego Marin-Bucio
(2025).
Co-creation of rhythm in Djembe Music-Dance.
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This talk examines the intricate and reciprocal relationship between music and dance in the context of Djembe rhythms. At the heart of these celebrations lies a unique interplay where rhythm serves as both a foundation and a catalyst for collective expression. Alongside Djembe playing, dancers and musicians engage in a dynamic process of mutual influence, creating a multimodal dialogue that evolves in real time. The discussion explored how rhythm emerges, not as a static entity, but as a shared negotiation where movement and sound coalesce to generate meaning and aesthetic congruence. Central to this process is the interplay between music and dance through structured improvisational elements, which provide a double-encoded catalyst that works as a framework and as a creative stimulus. Through video recordings and a comparative analysis of Djembe music and dance structures, I illustrate how this rhythmic catalyst takes shape through elastic sound and movement phrases that influence the decision-making of both, dancers and musicians.
This study reveals that Djembe's rhythms transcend unimodal agency to become a collective/multimodal phenomenon. The insights gained underscore the transformative power of rhythm in co-creative processes, offering remarkable perspectives on performance, dialogue, and the interplay between sound and movement.
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Diego Marin-Bucio
(2025).
Matriz de Movimiento Maquínico (MMM).
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This lecture introduces a conceptual framework for mapping the ontological roles of technology in choreographic creation. Drawing on case studies of AI-integrated works, it examines human–machine interaction and the redistribution of agency across dancers, choreographers, and computational systems. The resulting framework offers a practical tool for distinguishing when AI functions as an instrument and when it participates as an active co-creator in dance.
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Diego Antonio Marin Bucio
(2024).
Embodying the artificial: a multimodal human-machine performance.
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Diego Antonio Marin Bucio
(2024).
¿Puede una IA bailar?
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Las reflexiones y resultados que se presentan en este artículo tienen su origen en la experiencia de diseñar un bailarín de inteligencia artificial y la posterior cocreación de danza humano-IA en el proyecto «Dancing Embryo» (Marin, Wallace y 6A9). La investigación gira en torno a tres etnografías que captan el proceso de colaboración entre humanos y máquinas para crear e interpretar danza. Esta investigación trasciende la mera innovación tecnológica para convertirse en una profunda indagación filosófica, que cuestiona la naturaleza y los límites del arte de la danza.
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Diego Antonio Marín Bucio & Rainer Polak
(2024).
Exploring motion capture systems in dance research: a case study of djembe dance from West Africa.
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Diego Marin-Bucio
(2024).
Aproximaciones a la inteligencia artificial en la creación de danza: la IA como herramienta, títere o colaborador.
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This presentation reported the research outcomes of incorporating generative AI in the creation of concert dance, evaluating its role as a tool, puppet, or collaborator. Employing an interdisciplinary theoretical framework encompassing 4E cognition, phenomenology of perception, Actor-network theory and Entrainment theory, human-AI interactions are examined. Ethnographic methodologies and phenomenological analysis reveal power dynamics and modes of creative interrelation in dance creation with AI and other technologies. The results present a taxonomy and conceptual model, highlighting how AI can transcend from a mere creative catalyst to an active agent in producing aesthetic works. This structured approach facilitates the understanding, differentiation and application of emerging technologies in dance, proposing new paradigms for human-machine creative collaboration.
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Diego Antonio Marín Bucio
(2023).
Curiosity, culture, career and community.
[Journal].
London, England.
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Diego Antonio Marín Bucio
(2022).
Human-AI dance: hybrid co-creativity in the posthuman era.
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The talk challenges previous approaches to creative collaboration between humans and artificial intelligence, questioning whether we are only using AI to enhance our own creativity rather than a collaboration between two creative agents.
In addition, the author argued for the development of more body-interactive AI systems, as he alerts us to the potential decline of bodily-kinesthetic intelligence. His point was accompanied by a proposal presented together with Benedikte Wallace, where Diego Marín and an interactive AI created and performed dance in real-time.
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Publisert
12. sep. 2023 10:00
- Sist endret
18. mai 2026 16:36