The interdisciplinary project  AI_am explores how artificial intelligence (AI) and contemporary dance can inform and advance each other. Founded in 2013, the project brings together experts from the fields of dance, cognitive science, graphics and coding.

The project focuses on creating an improvised duet between an AI and a human dancer. The avatar, projected on stage, observes and learns the movements of the dancer, but also extends them with its own variations. Throughout the performance, the distinction between “teacher” and “student” gradually blurs, as the human dancer begins to find inspiration in the avatar’s novel movements.

By applying sophisticated machine learning techniques in the context of dance and by staging a unique meeting between art and science, the project seeks to rethink what performing art is or could be. At the same time, the project also raises more general questions about AI and its place in the world.

AI_am has been presented at TEDxDanubia, in Budapest, Hungary and TEDxGöteborg, in Gothenburg, Sweden in 2015, as well as Gothenburg Science Festival and Brain Bar Budapest in the frame of smART! Xtra Lab//Augmented Body in 2016 . The team has published and presented research papers in several international conferences including the 2014 & 2015 International Movement and Computing Workshop, the 24th International Joint Conference on Artificial Intelligence (IJCAI-15) and the 21st International Symposium on Electronic Art (ISEA2015). The Kinetic Dialogues interactive installation was presented at the ARTE@IJCAI exhibition at the Centro Cultural Borges in Buenos Aires and ISEA2015 in Vancouver.

AI_am here the project’s first evening-length show was premiered at Trafo House of Contemporary Arts, Budapest and 3:e Vaningen, Gothenburg in October 2017.

Published papers:

Berman A., James V. (2018) Learning as Performance: Autoencoding and Generating Dance Movements in Real Time. In: Liapis A., Romero Cardalda J., Ekárt A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2018. Lecture Notes in Computer Science, vol 10783. Springer, Cham

Alexander Berman and Valencia James “Kinetic Imaginations: Exploring the Possibilities of Combining AI and Dance”,  In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, 2015. ijcai15-344

Alexander Berman and Valencia James “Kinetic Dialogues: Enhancing creativity in dance”, In ACM Proceedings of the 2nd International Workshop on Movement and Computing (MOCO’15), Vancouver, 2015. MOCO15BermanJames

Alexander Berman and Valencia James “Improvising virtual dancer meets audience: Observations from a user study “, In Proceedings of the 21st International Symposium on Electronic Art (ISEA2015), Vancouver, 2015. isea2015_submission_106

Alexander Berman and Valencia James “Towards a Live Dance Improvisation between an Avatar and a Human Dancer “, In ACM Proceedings of the 1st International Workshop on Movement and Computing (MOCO’14), Paris, 2014. MOCO14BermanJames


“AI as an Improvisation Tool- Open Studio”, Discussion and workshop for dancers, choreographers and artists interested in creative software. Trafo studio, Budapest, Nov. 2015.

“Creating with AI”, Workshop for dancers, choreographers and artists interested in creative software.  Gothenburg Science Festival, 3:e Vaningen, Gothenburg, Apr. 2016.

“AI, Empathy and Dance”, Workshop for professional dancers and choreographers. Trafo studio, Budapest & 3:e Vaningen, Gothenburg, Dec. 2016.

Valencia James – Lead artist, Research, choreography and performance
Botond Bognár – Concept and research
Alexander Berman – AI research and development
Gábor Papp – Creative coding, rendering
Gáspár Hajdu – Motion capture, rendering, architectural design