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An Unpredictable Symphony

(working title)

An Interactive Exploration of Environmental Transformation Through Real-time AI Music and Performance

In Exclusive Collaboration with Composer Matthias Leboucher and Ensemble NAMES (New Art and Music Ensemble Salzburg)

An interactive music experience project that explores the potential of AI in order to enable audience participation and engagement, it aims to combine scientific research with artistic storytelling, exploring a unique way to tell an environmental story. The project addresses the challenges linked to temperature and environmental data, and rising sea level data, and examines the impact of temperature parameters on the predictability of music generated by AI models.

In an artistic exploration of storytelling, we aim to develop a unique decision-making process : the cognitive assemblage. This process combines human-generated musical layers with AI-generated layers influenced by climate and environmental data. We employ fuzzy logic and the heat parameter as metaphors for predictability in contemporary music. By studying the impact of temperature parameters on music predictability. We use the heat parameter and global warming as metaphors that increasing the temperature parameter for an AI model leads to less predictable music, connected to how climate change leads to less predictable weather patterns.


The challenge lies not only in addressing climate change but also in effectively communicating predictions without triggering paralyzing responses or denial. In response, the project aims to create an interactive music concert-exhibition that establishes a direct connection with the environment. Climate data, often complex and difficult to understand or access, is transformed through artistic and musical means to provoke a common human emotion and cognition, enabling individuals to experience the data firsthand.


In our pursuit of exploration, we endeavor to manifest an AI-driven music generation apparatus, ingeniously harnessing the capabilities of generative neural networks while synergistically integrating environmental data analysis. This innovative system undergoes rigorous training, drawing upon a rich tapestry of musical datasets interwoven with climate and environmental data, meticulously transmuting them into intricate audio-visual tapestries.

Coming in 2024! Stay Tuned! 

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