BLOB - Building Open Local Bots¶
Democratizing artificial intelligence through federated knowledge networks
Research Overview¶
This thesis explores the development of community-governed artificial intelligence systems that prioritize local autonomy, democratic oversight, and federated knowledge sharing. Moving beyond centralized AI platforms, this research demonstrates how communities can deploy, control, and benefit from AI technologies while maintaining complete data sovereignty.
The work combines practical system development with theoretical frameworks, resulting in functional platforms like Oatflake that enable communities to create their own AI knowledge systems. Through distributed training, local processing, and democratic governance mechanisms, these systems prove that powerful AI capabilities can exist with respect of community control and privacy.
How can we design accessible governance systems to enable sustainably adapting distributed intelligences?¶
Thesis Documentation¶
Core Concepts
Foundational ideas driving community-governed AI: distributed training, democratic oversight, federated networks, and local sovereignty.
Experiments
Practical implementations and prototypes: Oatflake platform, LAIA project, LLUM exhibitions, and community validation studies.
Research Methodology
Design research approaches, community engagement methods, technical validation processes, and iterative development cycles.
Research Context
Academic foundations, related work, theoretical frameworks, and positioning within AI governance and decentralization literature.
Research Roadmap
Past achievements, current milestones, and future development plans for community-governed AI ecosystem expansion.
Interactive Playground
Live demonstration of Oatflake platform, GitHub repositories, community access, and hands-on experimentation space.
Research Impact¶
Academic Contributions¶
This research contributes to multiple academic domains including human-computer interaction, distributed systems, AI governance, and community-centered design. The work bridges theoretical frameworks with practical implementations, providing both conceptual advances and functional systems.
Technical Innovation¶
The development of local AI processing pipelines, federated knowledge architectures, and democratic governance mechanisms creates new technical approaches for community-controlled technology deployment.
Social Innovation¶
By demonstrating that communities can successfully govern their own AI systems, this research provides pathways for digital sovereignty, knowledge democratization, and community empowerment in an increasingly AI-driven world.
Complete Documentation¶
📚 Documentation Status
Work in Progress: This documentation is actively being developed and updated. New sections, experiments, and insights are added regularly as the research evolves. Check back frequently for the latest developments in community-governed AI systems.
Last Updated: June 2025