The Sphere: A Decentralized Platform for Human Organisation
This index presents the Sphere project as a single coherent narrative — from philosophical motivation through core theory to practical implementation. It reads like a whitepaper or thesis, building each idea on the last.
0. Abstract
Section titled “0. Abstract”The Sphere is a vision for a decentralized social network built on trust-based connections between people, governed by flexible and composable decision-making structures called “governance engines,” and extended with value-based voting, open-source incentive systems, and democratic tooling. It aims to better represent the network structure of human interaction and provide a scalable, flexible, and stable platform for human organisation.
1. Introduction & Motivation
Section titled “1. Introduction & Motivation”Why does this project exist? Technology has outpaced our ability to organize wisely. We have unprecedented tools but outdated structures for wielding them collectively. The Sphere project starts from five foundational principles.
2. Core Theory
Section titled “2. Core Theory”2.1 Trust-Based Social Networks
Section titled “2.1 Trust-Based Social Networks”The foundation layer. Rather than the flat “friend/follower” model of existing social media, the trust-based social network models human relationships as a directed graph with typed, weighted connections. Entities (users, groups, algorithms) connect through relationships that carry meaning — “knows”, “trusts”, “is member of” — with fine-grained permissions controlling data flow.
Key sub-concepts:
- Identity: The hard problem of proving who someone is in a decentralized system without a central authority. Explores 1-to-1 identity, pseudonymity, and identity recovery. → Identity
- Ego Network: How the network looks from one individual’s perspective — the personal view of connections and communities. → Ego Network
- Data Ownership: Users control their own data, deciding who sees what under which conditions, going far beyond the public/private binary. → Web3 Social Media
2.2 Groups: Circles & Spheres
Section titled “2.2 Groups: Circles & Spheres”Building on the individual trust graph, people organize into groups. Circles are simple group models (autocratic, representative, pure, virtual). Spheres are composable super-groups that can contain sub-circles and sub-spheres, enabling hierarchical organization without centralized control.
2.3 Governance Engines
Section titled “2.3 Governance Engines”The central innovation. A governance engine is an abstracted representation of a governance structure formalized into four elements — Entities, Objects, Procedures, and Connections — forming an activity graph. This graph can represent any decision-making process, from a simple majority vote to a complex parliamentary system with courts, committees, and constitutional amendments. Crucially, governance engines can modify themselves.
→ Governance Engine → Democratic Procedures (full catalog of procedure types)
2.4 Social Contracts & Trust Mechanics
Section titled “2.4 Social Contracts & Trust Mechanics”The contractual layer. Social Smart Contracts lift smart contract logic from pure numerical transactions to human agreements verified through human decision. Social Tokens provide the reputation and trust tracking that makes these contracts enforceable without central authority.
→ Social Smart Contracts → Social Tokens
2.5 Value Networks & AI Alignment
Section titled “2.5 Value Networks & AI Alignment”The most abstract layer. Instead of voting for representatives, people vote on values — formally defined value objects with legal descriptions and AI training data attached. Weighted and destructive voting allow nuanced expression of preference and confidence. This feeds directly into AI alignment, providing a democratic mechanism for guiding AI behavior.
→ Value Networks → AI Alignment
3. Applications
Section titled “3. Applications”The core theory enables a range of practical applications:
3.1 Community Management & E-Democracy
Section titled “3.1 Community Management & E-Democracy”Governance engines applied to real-world democratic processes, enabling participation beyond traditional election cycles. Visualization and simulation of organizational structures.
→ E-Democracy → Decentral Voting Systems
3.2 QuestBoard — Open-Source Funding
Section titled “3.2 QuestBoard — Open-Source Funding”A dapp connecting users who need features with developers who can build them, mediated by token-based bounties, smart contracts, and reputation tracking. The economic engine for open-source development.
→ QuestBoard → Open-Source Development
3.3 Decentral University
Section titled “3.3 Decentral University”Decomposing the university into its core functions (research, teaching, accreditation, identity) and rebuilding each on decentralized protocols.
→ Decentral University → Decentral Knowledge Verification
3.4 Localized Communities
Section titled “3.4 Localized Communities”Privacy-preserving location protocols that enable local community organization without GPS surveillance.
3.5 Community Merging & Splitting
Section titled “3.5 Community Merging & Splitting”Formal protocols for handling the inevitable duplication and fragmentation of online communities.
4. Technical Architecture
Section titled “4. Technical Architecture”Three software layers mirror the three conceptual layers:
- Blockchain Layer — block drivers interfacing with external chains
- Network Layer — P2P node infrastructure for managing the social graph
- Application Layer — plugins and custom functionality on top
Multiple consensus mechanisms operate across layers: proof-of-work on chains, “proof of chain” for network gossip, and “proof of convergence” for application-level certainty.
5. Challenges & Open Questions
Section titled “5. Challenges & Open Questions”- Identity at scale: 1-to-1 identity may be fundamentally impossible to enforce in a fully decentralized system
- Self-modifying governance: How to safely allow structures to change themselves without creating instability
- Attack vectors: Corrupt groups gaining organizational efficiency (especially with AI actors)
- Network fragmentation: The risk of splitting into many unconnected sub-networks
- Grounding in reality: Abstract protocols remain vulnerable to fake users and bots without real-world anchoring