To address this question, this research explores the potential of local, domain-specific data loops and no-code interfaces, that can create a more equitable and local conscious technological landscape that prioritizes human ownership and promotes sustainable growth.

Through a process of experimentation and prototyping, a platform was developed from UI design to backend development and user database, gaining a deep understanding of the technical complexities and challenges of decentralized AI systems. This hands-on approach informed the development of a decentralized intelligence framework that prioritizes community governance, transparency, and accessibility.

The research engaged with a broader audience through exhibitions, workshops, and conversations with experts in AI development, politics, interaction design, and university research. These conversations provided valuable insights into the possibilities of open-source and decentralized approaches, and shaped the development of the framework.

Long-term testing was conducted through collecting data on projects and university contexts. Initially, the focus was on neighborhood data, but scaled down to a university-focused approach. This testing allowed for the gathering of insights into the practical applications and implications of decentralized AI systems in real-world contexts.

The mission of BLOB Browser is to democratize AI development, ensuring that the benefits of technological advancements are equitably distributed. The vision is to create a more inclusive and collaboratively governed intelligence ecosystem that promotes transparency, accessibility, and an intelligence ecosystem of sustainable growth.