I’ve been working on a framework for how humanity might govern AGI and advanced automation democratically, rather than through corporate or state control. This seems relevant to LessWrong given ongoing discussions about AI alignment, coordination problems, and long-term civilizational design. My central claim: Technical AI alignment is necessary but insufficient—we also need institutional alignment. Even if we solve the technical problem of making AGI follow instructions, we still need to decide whose instructions it follows and how those decisions get made.
The Coordination Problem Current trajectories seem to lead toward:
• Private companies controlling AGI (concentration of unprecedented power)
• State monopolies on AGI (authoritarian potential)
• Uncoordinated development (race dynamics, inadequate safety)
• Development bans (likely unenforceable, forgoes benefits)
None of these solve the fundamental governance question: How do we ensure transformative AI systems serve broad human interests rather than narrow ones?
A Proposed Framework
I’ve developed what I’m calling the Continuum Civic Stack, a governance framework for post-scarcity society built around:
1. Constitutional constraints on AI systems (Machine Governance Protocol) - legal-grade rules requiring transparency, human oversight, logging of decisions, emergency overrides
2. Commons-based infrastructure—publicly owned automation networks providing universal services with democratic control over priorities
3. Distributed governance—local assemblies federating upward, maintaining human sovereignty while using AI for coordination
4. Transparent coordination systems—open-source algorithms with all decisions logged in tamper-evident public records
The framework attempts to address: How do we maintain human agency and democratic legitimacy when AI systems manage most infrastructure?
Where I Need Your Help.
I’m probabilistically uncertain about several key assumptions:
1. Alignment feasibility: Does this assume too much about our ability to technically align AGI? The MGP treats alignment as solved—is this reasonable or should I design for partial/semi-alignment?
2. Game theory: What are the race dynamics? Why would actors adopt constrained AI when competitors might not? How robust is this to defection?
3. Speed mismatch: Can human governance meaningfully oversee systems operating at computer speeds? Even with transparency and logging, response time might be inadequate.
4. Adversarial robustness: How might a misaligned ASI subvert these mechanisms? Could it manipulate the information systems it’s supposed to be governed by?
I’m aware this intersects with existing work
• Constitutional AI (Anthropic) - technical alignment
• Cooperative AI research (Dafoe et al) - multi-agent coordination
• Ostrom’s commons governance—but applied to AI/automation
Where I think this adds value:
Integration across technical alignment, institutional design, and economic structure—most frameworks tackle one but not all three. Discussion Questions:
• What are the strongest objections to democratic governance of transformative AI?
• Are there historical/contemporary examples that validate or invalidate key mechanisms?
• What existing research should inform this work?
I have more detailed technical specifications but wanted to start with this overview. Happy to engage with thoughtful criticism.
[Note: Draft developed with AI assistance for clarity and structure]
[Question] Designing Democratic Governance for Post-AGI Society: A Framework for Feedback
I’ve been working on a framework for how humanity might govern AGI and advanced automation democratically, rather than through corporate or state control. This seems relevant to LessWrong given ongoing discussions about AI alignment, coordination problems, and long-term civilizational design.
My central claim: Technical AI alignment is necessary but insufficient—we also need institutional alignment. Even if we solve the technical problem of making AGI follow instructions, we still need to decide whose instructions it follows and how those decisions get made.
The Coordination Problem
Current trajectories seem to lead toward:
• Private companies controlling AGI (concentration of unprecedented power)
• State monopolies on AGI (authoritarian potential)
• Uncoordinated development (race dynamics, inadequate safety)
• Development bans (likely unenforceable, forgoes benefits)
None of these solve the fundamental governance question: How do we ensure transformative AI systems serve broad human interests rather than narrow ones?
A Proposed Framework
I’ve developed what I’m calling the Continuum Civic Stack, a governance framework for post-scarcity society built around:
1. Constitutional constraints on AI systems (Machine Governance Protocol) - legal-grade rules requiring transparency, human oversight, logging of decisions, emergency overrides
2. Commons-based infrastructure—publicly owned automation networks providing universal services with democratic control over priorities
3. Distributed governance—local assemblies federating upward, maintaining human sovereignty while using AI for coordination
4. Transparent coordination systems—open-source algorithms with all decisions logged in tamper-evident public records
The framework attempts to address: How do we maintain human agency and democratic legitimacy when AI systems manage most infrastructure?
Where I Need Your Help.
I’m probabilistically uncertain about several key assumptions:
1. Alignment feasibility: Does this assume too much about our ability to technically align AGI? The MGP treats alignment as solved—is this reasonable or should I design for partial/semi-alignment?
2. Game theory: What are the race dynamics? Why would actors adopt constrained AI when competitors might not? How robust is this to defection?
3. Speed mismatch: Can human governance meaningfully oversee systems operating at computer speeds? Even with transparency and logging, response time might be inadequate.
4. Adversarial robustness: How might a misaligned ASI subvert these mechanisms? Could it manipulate the information systems it’s supposed to be governed by?
I’m aware this intersects with existing work
• Constitutional AI (Anthropic) - technical alignment
• Cooperative AI research (Dafoe et al) - multi-agent coordination
• Platform cooperativism—democratic tech ownership
• Ostrom’s commons governance—but applied to AI/automation
Where I think this adds value:
Integration across technical alignment, institutional design, and economic structure—most frameworks tackle one but not all three.
Discussion Questions:
• What are the strongest objections to democratic governance of transformative AI?
• Are there historical/contemporary examples that validate or invalidate key mechanisms?
• What existing research should inform this work?
I have more detailed technical specifications but wanted to start with this overview. Happy to engage with thoughtful criticism.
[Note: Draft developed with AI assistance for clarity and structure]