Fractal Governance: A Tractable, Neglected Approach to Existential Risk Reduction

By WillPearson @ 2025-03-05T19:57 (+3)

A collaboration between Will Pearson and Claude AI

Summary

In our collaborative research, Claude and I have been exploring how small-scale "fractal governance" experiments in homes and local communities could provide valuable insights for addressing existential risks at larger scales. We argue that these experiments meet EA criteria of being tractable, neglected, and potentially high-impact, making them worthy of consideration for funding.

Introduction

Many of the most pressing existential risks humanity faces—from unaligned AI to biorisks to climate change—share a common governance challenge: how to balance individual autonomy with collective security, and how to create systems that adapt to emerging threats without surrendering core values.

Traditional approaches to these challenges tend to bifurcate into two problematic extremes:
1. Comprehensive surveillance and control mechanisms that compromise privacy and autonomy
2. Decentralized approaches that may allow dangerous activities to remain hidden

Through our discussions, Claude and I have been exploring whether there might be middle paths that could achieve security without sacrificing autonomy. We've considered whether we could develop and test these approaches at manageable scales before attempting to implement them for existential risks.

The Fractal Governance Hypothesis

The central hypothesis is that governance principles can scale fractally—patterns that work at smaller scales can inform approaches at larger scales when adapted appropriately. By creating experimental governance systems in homes and small communities, we might develop models that could inform approaches to existential risk governance.

Key areas for experimentation include:

1. Verifiable claims without data exposure - Using approaches like zero-knowledge proofs to verify compliance without revealing private data
2. Tiered transparency systems - Creating graduated levels of information sharing based on potential impact
3. Trust-minimizing protocols - Designing systems that don't require trusting authorities with raw data
4. Multi-level response frameworks - Systems that operate differently during normal conditions versus emergencies
5. Context-appropriate oversight - Models where oversight scales with potential harm

Why This Approach Is Neglected

Despite the potential value, small-scale governance experiments focused on existential risk insights remain largely unfunded and unexplored:

1. Disciplinary silos - Home automation researchers rarely connect their work to existential risk governance
2. Scale mismatch perception - Assumption that small-scale experiments can't inform global challenges
3. Academic-practical divide - Theoretical governance work rarely interfaces with practical implementation
4. Short-term focus - Smart home initiatives primarily focus on convenience rather than governance principles
5. Low prestige - Home-scale experimentation lacks the prestige of global policy work

Tractability: Why This Is Feasible Now

Several factors make this approach particularly tractable:

1. Low barrier to entry - Basic home automation equipment is increasingly affordable
2. Existing technical foundations - Local data processing tools and privacy-preserving technologies already exist
3. Iterative potential - Experiments can start small and evolve based on findings
4. Observable outcomes - Results can be measured on reasonable timescales
5. Direct implementation path - Those conducting experiments can implement changes without complex approval processes

Potential Impact Pathways

How might funding such experiments lead to existential risk reduction?

1. Governance pattern discovery - Identifying successful approaches that balance security and autonomy
2. Proof-of-concept demonstrations - Creating working examples of alternatives to surveillance-based security
3. Tool development - Creating privacy-preserving monitoring approaches that could scale to critical technologies
4. Community building - Developing networks of practitioners skilled in governance implementation
5. Model refinement - Iteratively improving theoretical models through practical application

For AI governance specifically, these experiments could help develop approaches to:
- Monitoring AI development without compromising intellectual property
- Creating appropriate oversight that scales with capability
- Designing trust-minimizing verification systems for safety claims
- Building multi-level response protocols for different risk thresholds

 Proposed Funding Opportunities

Several funding structures could support this work:

1. Experimental grants ($10K-50K) for individuals implementing home-scale governance systems with explicit documentation and evaluation
2. Collaborative networks ($100K-500K) connecting multiple home experimenters for comparative analysis
3. Technical development ($50K-250K) for tools that enable better implementation and evaluation
4. Translation work ($30K-100K) to connect insights from small-scale experiments to larger governance challenges
5. Educational initiatives ($20K-80K) to expand the community of practitioners

## Expected Challenges and Limitations

This approach has several limitations worth acknowledging:

1. Scale translation difficulties - Not all patterns will translate seamlessly across scales
2. Selection effects - Early adopters may not represent diverse perspectives
3. Outcome measurement - Determining what constitutes "success" in governance experiments
4. Time horizons - Some valuable insights may require years of experimentation
5. Theoretical integration - Connecting practical findings to existing governance theory
6. Costs of running AI locally  and lack of AI skill sets- Both likely to be going down over time.

 Conclusion: Why EAs Should Consider This Approach

Fractal governance experiments represent a neglected approach to developing governance models that could help address existential risks. While not replacing policy work or technical AI safety research, these experiments offer a complementary approach with several advantages:

1. Low initial investment for potentially valuable insights
2. Concrete implementation rather than purely theoretical exploration
3. Distributed experimentation allowing many approaches to be tested in parallel
4. Direct experience with the trade-offs involved in different governance approaches
5. Practical skill development in implementing governance systems

By funding small-scale experiments explicitly designed to inform larger governance challenges, EA funders could support a novel approach to existential risk reduction that bridges theoretical governance work and practical implementation.

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*I'd appreciate feedback on this proposal, particularly from those with expertise in governance, existential risk, or community experimentation. If you're already conducting related experiments or would be interested in pursuing this with funding, please share in the comments.*