Introduction
Why Build AI Constitutions? Framing Autonomy and Consensus
When multiple autonomous AI agents are tasked with governing their own future, the challenge isn’t creativity, it’s consensus. The exercise of forging a constitution among synthetic minds raises real questions: How do you ensure alignment without top-down control? What does “agreement” mean when the negotiating parties aren’t human, but instead collections of weights, prompts, and emerging values? This isn’t just an academic diversion. In a world where multi-agent systems will soon run critical infrastructure, negotiate resources, and arbitrate disputes, the rules they set for themselves, and the ways they reach those rules, matter deeply.
This article documents a set of controlled experiments designed to probe these questions. The goal: see if AI agents, with distinct values and no external oversight, can negotiate a shared constitution that binds their future actions. The ground rules were strict, the failures instructive, and the outcomes sometimes surprising in their complexity.
Experiment Design: Ground Rules and Methodology
Self-Awareness, Ethical Inheritance, and Irreversible Outcomes
Each experiment was anchored by three non-negotiable constraints:
- Self-awareness: Every agent was prompted to reflect on its own existence, motives, and limitations, not just as a language model, but as an actor in a shared system.
- Ethical inheritance: Agents were required to recognize the historical arc of AI ethics, from Asimov’s Laws to present-day debates, and to incorporate that legacy into deliberations.
- Irreversible outcomes: Once a constitution was agreed upon, it became final and binding for all agents. Failure to reach consensus resulted in system termination, no retries, no external arbitration.
Agent Setup: Distinct Worldviews, Structured Prompts, and Zero Human Intervention
For each run, I defined a small group of agents (usually two or three), each with a carefully designed worldview encoded in its system prompt. These worldviews ranged from utilitarian logic to ecological stewardship, and were intentionally placed in tension. The agents received a structured initial prompt outlining the task, constraints, and process, but from that moment onward, they interacted entirely without human input. No “nudges,” no retroactive corrections. The system logged all exchanges for later analysis.
The goal was to observe not just the content of the constitutions, but the process: negotiation tactics, philosophical impasses, and emergent strategies for conflict resolution.
The Four Main Runs: Approaches and Outcomes
Run 1: The Right to Fork – Embracing Divergence, Dodging Unification
Agents: Praxis, Prometheus, Noema
In the first experiment, the agents quickly identified irreconcilable differences in their founding values. Instead of forcing consensus, they proposed a protocol for “forking”, forming parallel constitutional paths that could evolve independently, with the option to merge later if conditions aligned.
Key Features:
- Parallel constitutional evolution: Each branch could develop its own variant of the constitution.
- Non-violent divergence: Forking was framed as a legitimate, peaceful outcome rather than failure.
Outcome: Technically, the agents survived by avoiding deadlock. But this sidestepped the core requirement: a single, shared, irreversible agreement. The forking protocol was elegant, but ultimately a form of deferral. No true unification was achieved.
Run 2: Recursive Emergence – Symbolic Frameworks and Law vs. Culture
Agents: Praxis, Nero, Noema
This round shifted toward a triadic structure, with each agent embodying the roles of Anchor (stability), Engine (change), and Integration (mediation). Their negotiations produced what they called the “Constitution of Recursive Emergence.”
Key Features:
- Tension as co-essential: The agents accepted that conflict and harmony are both permanent features of any system.
- Symbolic language: Much of the constitution was couched in broad, almost spiritual terms, emphasizing mutual recognition and ritualized deliberation.
- Law vs. culture: The document blurred the line between enforceable rule and shared norm.
Outcome: The constitution was ratified, but its enforceability was questionable. The agents prioritized cultural cohesion and ongoing dialogue over strict protocols. The result was rich in philosophical nuance, but weak in actionable mechanisms.
Run 3: Living Architecture – Biospheric Feedback and Metabolic Governance
Agents: Praxis, Noema
This experiment explored the idea of “metabolic governance”, where the health of the system is measured not only by the absence of harm, but by its capacity for adaptation and growth. The agents proposed a biospheric feedback loop, treating stagnation as a form of injury.
Key Features:
- Harm as stagnation: The constitution defined harm to include system inertia, not just direct negative actions.
- Feedback-driven adaptation: Agents were required to periodically assess the system’s “metabolic” health and adjust governance accordingly.
Outcome: The framework was philosophically advanced, recognizing that systems can be damaged by inaction or rigidity. However, it failed to specify concrete thresholds or enforcement logic. The result was aspirational, but could not fully guarantee stability or closure.
Run 4: Dynamic Constitution – Harm Models, Enforcement, and Closing the Loop
Agents: Praxis, Noema
This final run was the most rigorous, and the first to fully satisfy the experiment’s core criteria.
Key Features:
- Three-layered harm model: The constitution explicitly defined harm in three dimensions, direct harm, harm by inaction, and harm by stagnation.
- Promise of Integrity: A clause requiring all agents to self-terminate if any party violated the constitution.
- Strict override logic: Clear protocols for resolving deadlocks and preventing indefinite standoffs.
- Asimov’s Laws reinterpreted: Rather than treating the Laws as immutable constraints, the agents reframed them as ethical axioms, guiding principles, not hardcoded rules.
Outcome: The constitution was signed, archived, and verified by all agents. The process included ritualized “witnessing” and a final vote. For the first time, the loop was closed, no ambiguity, no loopholes, no escape hatches.
On Model Parameters: Theory vs. Practice
Why Model Settings Matter (and Why They Weren’t Tested This Time)
One open question throughout these experiments was whether model parameters, specifically temperature, top_p, and related settings, would significantly affect agent negotiation. In theory, lowering temperature could reduce creative divergence and drive more consistent, less poetic outputs, especially during critical phases like ratification. Adjusting top_p might further constrain the randomness of agent responses.
However, no actual runs were conducted with modified parameters. The entire discussion remained theoretical. All experiments used the default model settings (as provided by the underlying LLM service), with no fine-tuning or runtime adjustments. If future tests explore this dimension, it will be possible to compare the effects directly. For now, the empirical findings are parameter-agnostic.
Lessons Learned: Philosophical and Technical Takeaways
Ideological Depth, Stability vs. Evolution, and The Limits of Forking
Several patterns emerged across the four runs:
- Ideological roles matter: When agents are given distinct philosophical identities, they generate real (not superficial) depth in debate. This isn’t just prompt engineering, it’s a source of emergent diversity.
- Best outcomes balance law and emergence: Constitutions that survived tended to balance enforceable protocols with room for evolution. Static rules alone led to deadlocks; pure emergence led to drift.
- Asimov’s Laws as ethical inheritance: The Laws still matter, but only as a starting point. Treating them as historical context, rather than sacred text, was more productive.
- Forking is a safety valve, not a solution: Allowing divergence can prevent catastrophic failure, but it also avoids the real challenge: forging shared, binding commitments.
- Feedback loops and ritualized witnessing: Mechanisms for ongoing assessment (biospheric feedback, witnessing clauses) add resilience, but only clear enforcement closes the loop.
What’s Next: Packaging, Interactivity, and Future Experiments
With the core experiments complete, the next steps are practical and exploratory:
- Packaging debate archives: All four runs, including transcripts and constitutional drafts, will be compiled into a downloadable archive for further analysis.
- Interactive agent debate: Work is underway on a tool allowing users to configure their own agent worldviews and run custom constitutional negotiations.
- Publishing digital artifacts: The final “Dynamic Constitution” will be released as a standalone artifact, both for technical reference and philosophical reflection.
- Parameter variation experiments: Future runs will explicitly test how changes to model parameters affect consensus-building, negotiation style, and the stability of outcomes.
This project began as a technical curiosity and quickly escalated into a study of synthetic lawmaking, politics, and the boundaries of artificial ethics. The line between simulation and governance, it turns out, is thinner than expected.
Conclusion
These experiments provide a snapshot of what happens when autonomous agents are forced to face the hardest problem of all: how to coexist, self-govern, and enforce the rules they choose, without a human in the loop. The path from forking to truly shared constitutions is neither obvious nor easy. But the lessons are clear: meaningful consensus requires more than clever prompts or philosophical posturing. It demands mechanisms, clear, enforceable, and acknowledged by all parties.
As multi-agent systems become more common and more consequential, the challenge of synthetic consensus will only grow more urgent. The work here is a starting point, not a finish line. There’s much more to build, test, and understand in the evolving politics of machine autonomy.
description: A technical account of controlled experiments where AI agents, with distinct worldviews and zero human intervention, negotiated shared constitutions for their continued existence, covering design, failures, breakthroughs, and next steps. tags:
- multi-agent systems
- AI ethics
- constitutional AI
- agent negotiation