selfdriven AI Usage
The selfdriven AI framework demonstrates how communities, organisations, and practitioners can apply artificial intelligence within trusted, context-aware systems. By combining human identity, community intent, and structured knowledge, selfdriven AI transforms static information into dynamic, verifiable intelligence.
Community-Based Intelligence Usage
Community-Based Intelligence is designed to help communities capture, organise, and activate their collective knowledge.
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Each community begins by gathering its key documents — such as charters, plans, and discussions — and creating a Vector Store through the selfdriven.network AI Interface. This enables the community’s data to become machine-readable and contextually searchable.
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A Community Assistant is then generated, equipped with a “System Card” derived from the Community 5W1H Sheet. This ensures the Assistant understands the community’s purpose, principles, and context.
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Community members, authenticated via their selfdriven Identity (SSI DID), can start conversations with the Assistant through the selfdriven Human Interface (the app). These interactions allow members to ask questions, explore insights, and co-create knowledge.
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When appropriate, conversations can be shared with other community members — such as facilitators or practitioners — to enable collaboration, mentorship, or collective problem-solving.
Implemented using a combination of:
- octology - definitions, constraints
- selfdriven.network - Human, AI, SSI, Entity Interfaces
- selfdriven Progessive Self-Actuation Framework - Community 5W1H Sheet
Related
- selfdriven.health Practitioner-In-The-Loop Services (PITLS)
- selfdriven.network AI Interface
- Use-Cases-Tests
- skillzeb - Community Templates for GenAI alignment