ABOUT
The Embodied Restoration Lab is a design initiative by architect Afaina de Jong that explores the redefinition of values between architecture, ecology and diasporic knowledge through the framework of algorithmic systems design. The Embodied Restoration Labs collective ecosystem of generative algorithmic models that is grounded in the archives of a diasporic community in a effort to exchange and transfer collective knowledge into a distributed systems ecology.
The building of decentralised AI based in communities of knowledge within the Embodied Restoration Lab is aimed at offering accessible alternative to institutional decline and the privatisation of knowledge. The creation of collective intelligence around a decentralised ecosystem of generative AI that makes effort to apply diasporic thinking into practice is the essential urgency that drives the Embodied Restoration Lab. With many of the educational and knowledge institutions under pressure it is important for this community to be able to have the knowledge within their practices to be in conversation with each other and accessible to each other and their respective communities of students and scholars. And importantly, be part of the public imaginary on their own terms.
Collective Contributor Ecosystem
Notions of consent, ownership, transparencies in which relationships are being made, what knowledge is being applied in outcomes, low carbon footprints and human connections and social contracts are important modes of development for this collective ecosystem of generative AI models and archives.
Social Contract
All the contributors within the Embodied Restoration Lab are the owners of the resources: the multiple models, the image generation tools, and more. A next step for this collective system is the development of distributed computing resources among the contributors as part of a expaneded social contract.
Building Archives
By building and testing the contributor archives collectively, it foregrounds questions of metadata, consent, and ownership, while also opening possibilities for shared imagination and restorative knowledge. This process questions the ways in which archives determine what is visible, valued, or remembered.
Decentralized AI
The collective ecosystem is an attempt to decentralize knowledge through multi-modal generative AI models, and to highlight the capability to exchange, visualize and refine knowledge necessary for collective intelligence to thrive without being dependent or extracted by centralized generative AI models
