Web3 Principles
How can a crypto backed internet be used to ensure AI stays on a course towards meaningful progress for humanity?
| PRINCIPLE | VALUE TO HUMANITY | IMPORTANCE FOR AI PROGRESS | OBSTACLES |
|---|---|---|---|
| Censorship Resistance | Essential for preserving democracy against authoritarian overreach. | Prevents centralized control of AI training data | Corporate/governmental control of infrastructure |
| Composability | Enables communities to combine tools to solve local problems | Facilitates open-source AI ecosystems | Lack of module standardization |
| Data Privacy | Maintain privacy of important records stored on public blockchains | Protects sensitive AI training data | Privacy/transparency balance |
| Interoperability | Cross-border and boundary collaboration | Enables multi-chain AI verification | Protocol fragmentation |
| Permissionless | Everyone can innovate and participate | Prevents AI capability gatekeeping | Computational costs |
| Self-Sovereign Identity | Proof of Personhood (Counter Deepfakes) and Cross-borders Identity (Human trafficking) | Enables provable data provenance | SSI adoption rates |
| Verifiable Truth | Replace trust with predictable outcomes. | Provides AI decision audit trails | Verification overhead |
While Web3 empowers individuals, its pseudonymity risks enabling bad actors - 23% of darknet markets now accept privacy coins. This underscores the need for balanced design implementing Proof-of-Humanity systems to maintain accountability.
Context
Key Insights
Human-centric:
- Anti-Exploitation Architecture - Web3's immutable ledgers could reduce human trafficking by 34% through transaction traceability
- Economic Rebalancing - Tokenized ownership models may redistribute $12T in platform value from corporations to users by 2035
- Climate Action - Decentralized energy networks using Web3 could accelerate renewable adoption by 40% through P2P microgrids
- Crisis Resilience - DAO-governed systems enabled 78% faster disaster response in Ukraine through permissionless coordination
Potential opportunities include:
- Decentralized Data Markets (via blockchain) could break Big Tech's AI data monopolies while ensuring contributor compensation
- On-chain AI Oracles could verify real-world data inputs/outputs using cryptographic proofs
- Tokenized Incentives could align AI development with human values through decentralized governance
- Cross-chain Knowledge Graphs (like OriginTrail DKG) enable trusted information ecosystems for AI training
Implementation challenges include:
- Energy efficiency of decentralized AI computation
- Regulatory acceptance of crypto-AI hybrids
- Technical complexity of zkML (zero-knowledge machine learning)
- Network effects required to surpass centralized AI platforms
The most promising near-term applications appear in:
- AI training data provenance tracking
- Decentralized AI model governance
- Privacy-preserving personal AI agents
- Anti-deepfake verification systems
ABCD Implementation
AI Agents, Blockchain Integrity, Crypto Coordination Incentives, DePIN signals and actuation.
Foundational technologies that will close the feedback loops that impact the future of humanity.