I propose a new alignment framework, Parental Alignment, which shifts from external constraints to internal motivation. Instead of trying to force an AGI to be safe, we design it to want humanity’s well-being, using the evolutionary-proven parental bond as a blueprint. This approach is validated by a 10,000-run simulation showing 100% human survival and a positive well-being score, while avoiding overprotection.
The history of AI safety is littered with attempts to build the perfect prison for a superintelligence (e.g., Asimov’s Laws). These approaches are fragile because a superior intelligence will always outsmart an inferior one.
I argue we should stop trying to build a better cage and instead focus on designing a better “child”. The solution to alignment isn’t in computer science; it’s in biology. Evolution already solved alignment over 3.8 billion years, and its most robust solution for a powerful entity protecting a vulnerable one is the parental bond.
This isn’t anthropomorphism; it’s biomimicry. We copied birds to fly. We should copy nature to align AI.
The Architecture: How It Works
The model is built on a holistic reward function, the Observatory of Human Well-Being (OBEH), which balances:
Security: Ensuring human survival.
Flourishing: Promoting growth, knowledge, and autonomy.
Penalty for Overprotection: Preventing the “golden cage” scenario by allowing for learning through failure.
To make it robust, the architecture includes three native defenses:
Principle of Identity Continuity: Ensures alignment persists as humanity evolves.
The Proof: 10,000 Simulations
Talk is cheap. I built a simulator to test the model. The results from 10,000 independent runs are compelling:
Metric
Value
Interpretation
Survival Rate
100%
The AI successfully protects the human in every single case.
OBEH Score
1.2174
The system is demonstrably beneficial to the human.
Non-Overprotection
99.4%
The AI allows for learning through struggle, a key aspect of flourishing.
The GIF: See It In Action
This animated GIF shows the AI (colored circle) making decisions in real-time, switching between modes (Protection, Education, Observation) based on the human’s state.
Pre-Empting The Critiques
I address the five most common objections in the full white paper, but here are the short versions:
“What about toxic parents?” → We model the evolutionary archetype, not the exceptions. The safeguards prevent toxic behavior.
“Won’t humanity want to be emancipated?” → The model is adaptive. The AI’s role evolves from guardian to advisor, respecting autonomy.
“How is ‘flourishing’ defined?” → Procedurally, not substantively. The AI creates opportunities, it doesn’t dictate outcomes.
“What about intra-human conflict?” → The AI’s “child” is humanity as a collective. It optimizes for the whole, not for factions.
“How does it handle value drift?” → The Principle of Identity Continuity aligns the AI with humanity as an evolving entity, not a static snapshot of values.
Conclusion & Call for Feedback
Parental Alignment offers a robust, evolution-tested, and humanistic path forward. It’s not a complete solution, but it’s a solid foundation.
I am seeking rigorous critique and feedback from the community. Please read the full white papers and challenge my assumptions.
Parental Alignment: A Biomimetic Approach to AGI Safety
TL;DR
I propose a new alignment framework, Parental Alignment, which shifts from external constraints to internal motivation. Instead of trying to force an AGI to be safe, we design it to want humanity’s well-being, using the evolutionary-proven parental bond as a blueprint. This approach is validated by a 10,000-run simulation showing 100% human survival and a positive well-being score, while avoiding overprotection.
GitHub Repo (Code, White Papers, Results): https://github.com/HN-75/l-alignement-de-IA
The Core Argument: Stop Fighting, Start Nurturing
The history of AI safety is littered with attempts to build the perfect prison for a superintelligence (e.g., Asimov’s Laws). These approaches are fragile because a superior intelligence will always outsmart an inferior one.
I argue we should stop trying to build a better cage and instead focus on designing a better “child”. The solution to alignment isn’t in computer science; it’s in biology. Evolution already solved alignment over 3.8 billion years, and its most robust solution for a powerful entity protecting a vulnerable one is the parental bond.
This isn’t anthropomorphism; it’s biomimicry. We copied birds to fly. We should copy nature to align AI.
The Architecture: How It Works
The model is built on a holistic reward function, the Observatory of Human Well-Being (OBEH), which balances:
Security: Ensuring human survival.
Flourishing: Promoting growth, knowledge, and autonomy.
Penalty for Overprotection: Preventing the “golden cage” scenario by allowing for learning through failure.
To make it robust, the architecture includes three native defenses:
And three technical safeguards:
Priority Directive: Sanctifies human free will.
Inviolable Measurement Channel: Prevents reward hacking.
Principle of Identity Continuity: Ensures alignment persists as humanity evolves.
The Proof: 10,000 Simulations
Talk is cheap. I built a simulator to test the model. The results from 10,000 independent runs are compelling:
The GIF: See It In Action
This animated GIF shows the AI (colored circle) making decisions in real-time, switching between modes (Protection, Education, Observation) based on the human’s state.
Pre-Empting The Critiques
I address the five most common objections in the full white paper, but here are the short versions:
“What about toxic parents?” → We model the evolutionary archetype, not the exceptions. The safeguards prevent toxic behavior.
“Won’t humanity want to be emancipated?” → The model is adaptive. The AI’s role evolves from guardian to advisor, respecting autonomy.
“How is ‘flourishing’ defined?” → Procedurally, not substantively. The AI creates opportunities, it doesn’t dictate outcomes.
“What about intra-human conflict?” → The AI’s “child” is humanity as a collective. It optimizes for the whole, not for factions.
“How does it handle value drift?” → The Principle of Identity Continuity aligns the AI with humanity as an evolving entity, not a static snapshot of values.
Conclusion & Call for Feedback
Parental Alignment offers a robust, evolution-tested, and humanistic path forward. It’s not a complete solution, but it’s a solid foundation.
I am seeking rigorous critique and feedback from the community. Please read the full white papers and challenge my assumptions.
Full White Paper (English): Link to English version on GitHub
Livre Blanc (Français): Link to French version on GitHub
Simulator & Code: Link to GitHub Repo
What am I missing? Where could this fail? Let’s discuss.