Enterprise AI Analysis
Precious Camouflage - Artistic Research for the Creation of a Dance Piece with Humans and AI
Authors: Charlotte Triebus, Ivana Druzetic-Vogel, Christian Geiger
Date: September 03-07, 2025
This paper presents the layout of and research behind the dance performance Precious Camouflage, which explores the interplay between human movement and artificial intelligence (AI) within a museal space. The work stages four AI systems that interact live with a contemporary dance ensemble and the audience, critically examining themes of agency, surveillance, interpretation, and body politics. By intertwining choreographic principles with real-time AI responses, the performance challenges traditional notions of authorship and reflects on the societal and ethical implications of digital technologies. In addition to presenting the communicative setup, the work is accompanied by extensive research on ethical questions, with a focus on the representation of bodies in datasets. This paper reflects on the artistic research methodologies applied in Precious Camouflage, highlighting their relevance for both performative arts and Human-Computer Interaction (HCI) contexts. Background materials and the recorded performance are available at http://www.precious.dance.
Executive Impact & Strategic Value
"Precious Camouflage" offers critical insights into the intersection of art and AI, with tangible implications for ethical AI development, interdisciplinary innovation, and enhanced stakeholder engagement.
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Deep Analysis & Enterprise Applications
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This section details the iterative, practice-based inquiry employed in "Precious Camouflage." It combines aesthetic experience with systematic reflection, integrating experimental practices, digital technologies, and critical discourse. The research unfolded in three phases over two years, exploring how AI systems engage with the moving human body, refining systems with dancers, and synthesizing outcomes into the final performance and mediation formats.
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Research Phases Completed
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Performance Duration
This category explores the dramaturgical structure of "Precious Camouflage," centered on a feedback loop between AI and dancers. The performance features four AI systems interacting live with a contemporary dance ensemble, interpreting content in real-time through various outputs on LED screens. The 60-minute piece is divided into eight parts, evolving from synchronized movements to spontaneous outbursts influenced by AI interpretations, critically examining themes of agency, surveillance, and body politics.
Agents' Loop Communication Flow
Dancer / Space Input
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Captured by Camera
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AI1 Probabilities
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AI2 Textual Analysis
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AI3 Visual Illustration
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AI4 Interpretation in Liquids
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Feedback to Performance
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Real-time AI Systems Engaged
This section grounds "Precious Camouflage" in critical theory, addressing themes such as communication, language, interpretation bias, intra-action, agency, human/non-human moral, and surveillance. It challenges traditional notions of authorship by viewing AI as an active creative participant and explores how AI systems, influenced by their training datasets, can perpetuate biases and shape behavior, mirroring societal monitoring. The work adopts a non-anthropocentric perspective on agency and embodiment.
Human vs. AI Interpretation in Artistic Context |
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Human Interpretation |
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The choreographic material for "Precious Camouflage" was developed based on six core principles. These principles guided the creation of poses, movements, actions, and constellations, framed by two meta-principles: "staging for the unpredictable spectator" and "artistic research as a staging tool." Key principles included "the archive as a resource for neural networks and dancers," "Pat my Back; mind-bending and gravity-defying movement," "agency, surveillance, hiding from technology," "research and negotiation on drooling," "telephone principle," and "AI trainings chart."
Overcoming AI's Moralizing Bias: The 'Drooling' Experiment
The research involved discussions with an AI system that refused to depict 'spit' or 'drooling,' deeming it disrespectful. The AI would only generate images of water flowing from mouths or abstract 'drooling sculptures.' This refusal highlighted AI's inherent biases in representing human bodily functions. The artistic response was to embed this limitation into the choreography, culminating in the 'Ocean of Spit' scene where dancers deliberately spit, emphasizing the human element and challenging AI's 'moralizing' stance. This artistic intervention reveals how AI systems, far from neutral, inherit and perpetuate societal beliefs and taboos embedded in their training data.
Impact: Demonstrated AI's inherent biases, informed choreographic development, and critically reflected on the social and ethical implications of digital technologies regarding body representation.
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Your Implementation Roadmap
A phased approach to integrating the learnings from artistic AI research into your organization, fostering innovation and ethical development.
Phase 1: Discovery & Ethical Frameworking
Conduct a deep dive into organizational goals and existing AI initiatives. Establish a bespoke ethical framework for AI development, drawing on insights from the 'Precious Camouflage' project regarding bias, agency, and data representation.
Phase 2: Pilot Project & Iterative Design
Implement a pilot project applying choreographic and artistic research methodologies to an AI challenge within your enterprise. Focus on real-time feedback loops and iterative refinement, mirroring the performance's dynamic interaction between humans and AI.
Phase 3: Cross-Disciplinary Integration & Training
Expand the pilot into broader departmental integration. Develop training modules that educate teams on the societal and ethical implications of AI, promoting critical reflection and a non-anthropocentric perspective across your workforce.
Phase 4: Performance & Continuous Evaluation
Establish continuous monitoring and evaluation of AI systems, similar to a live performance. Encourage 'unpredictable spectator' engagement (user feedback) and adapt systems based on evolving ethical and operational insights, fostering long-term, responsible AI innovation.
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