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Botto is a decentralized autonomous artist that produces AI-generated works shaped through continuous community feedback, exploring how authorship and aesthetic judgment can be distributed across humans and machines.
Botto is a decentralized autonomous artist launched on October 8, 2021, operating at the intersection of machine learning and collective decision-making. Conceived by artist Mario Klingemann and developed in collaboration with a wider technical and curatorial network, Botto functions as an ongoing system that generates and evaluates images through a structured feedback loop between algorithm and community.


Each week, Botto produces thousands of image-text prompts using machine learning models. These outputs are presented to a distributed group of participants – often referred to as stewards – who review and then vote on the works. Through this process, a single image is selected and brought to auction. The proceeds are split between the community and the project’s treasury, sustaining both its development and its internal economy.
Central to Botto’s operation is its taste model, a system that is continuously trained on the preferences expressed through community voting. Rather than refining toward a fixed style, this model accumulates tendencies over time, allowing Botto’s visual language to evolve in response to collective input. The resulting images often carry traces of this negotiation, combining aesthetic coherence with a degree of unpredictability that reflects the plurality of its contributors.
Botto’s work has been exhibited internationally and has received recognition within both digital art and broader contemporary art contexts. Its emergence has contributed to ongoing discussions around agency, creative ownership, and the role of machine intelligence within artistic production. By structuring creation as a cyclical process of generation, selection, and redistribution, Botto frames art as something that unfolds over time, shaped by continuous interaction rather than singular intention.
The project is co-led by Simon Hudson, who has played a key role in shaping its organizational and conceptual framework. During Silk Road Chapter 01, Hudson presented Botto’s case and underlying mechanics, offering insight into how the system operates as both an artistic practice and a form of decentralized governance. Within this structure, each image marks a temporary outcome of a system that continues to recalibrate through collective input.
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Botto’s latest body of work, Mirror Stages, extended its system into a live installation. Presented at Art Basel Hong Kong 2026, the work unfolded through generative sessions in which a central image is continuously reshaped in response to audience presence.
From community voting to real-time interaction, Botto functions as an artist whose work is continuously shaped by external signals, integrating human input, in many different forms, directly into its process of creation and therefore redefining authorship as a distributed condition.
