Inventory (desierto/inundación)
A.I, digital print. 2023-2024
Work created from the co-creative developments of the Desierto/Inundación project by the group holosci[u]dad[e], an Ibero-American platform for research in art and technology.
Composed by: Lilian Amaral, Marcos Umpièrrez, Bia Santos, Liliana Fracasso, Marina Buj Corral, Laurita Ricardo de Salles, Mirian Celeste Martins, Suzete Venturelli, Brenda Marques Pena, Luis López Casero, José Prieto, Vega Ruiz, Paula Carolei, Daniel Toso, Matheus Montanari, Ivan David, Carina Flexor, Fernando Palacios, Luisa Fernanda Giraldo Murillo, Karla Brunet, Ricardo Dal Farra.
This artwork explores AI, climate change, and co-creation by reversing the roles of artist and machine. Through classifying AI-generated images around themes like “desert” and “flood,” it creates visual maps and datasets. The project highlights collaboration, environmental awareness, and new forms of artistic authorship.
This project emerges from a broader series of experiments at the intersection of artificial intelligence, environmental themes, and artistic authorship. Challenging the traditional paradigm in which machines are tools and artists are sole creators, the piece inverts this relationship: the AI assumes the image-creator role, while the artist adopts the position of classifier and curator. Rooted in themes of water, climate change, and ecological crisis, the project offers a compelling reflection on how human and non-human agents can collaborate in image-making and meaning-building.
The work originated in a participatory workshop, where AI-generated images were produced in response to environmental prompts. These visuals became the raw material for a unique artistic process. Rather than directly creating new images, the artist developed a structured inventory that categorized the AI-generated visuals into thematic clusters. Special attention was given to the contrasting categories of “desert” and “flood,” two key motifs symbolizing the extremes of the climate crisis. These thematic clusters formed a dynamic visual map, where images were grouped based on both formal similarities and conceptual connections.
By focusing on the act of classification, the artist highlighted the creative potential of organization, curation, and interpretation. The spaces between these image clusters—representing conceptual or aesthetic gaps—were not left empty. Instead, the AI was invited back into the process to generate intermediate images that bridged these gaps, producing speculative visual pathways and narratives. This ongoing interaction between human and machine enabled the emergence of new interpretations and associations within the dataset, opening up fresh possibilities for navigating ecological themes.
More than a static exhibition of visuals, the artwork serves as an evolving system of co-creation between humans and AI. It investigates how machine learning can contribute not only to aesthetics but also to environmental discourse, storytelling, and collaborative thinking. By blurring the boundaries between tool and creator, the project reflects on broader questions of agency, authorship, and our relationship with technology in a time of planetary crisis.
The piece is a meditation on climate, creativity, and the future of art-making—inviting audiences to consider how we might navigate ecological uncertainty through new forms of digital collaboration and visual investigation.