A structural framework for AI alignment derived from thermodynamic principles.
Rather than encoding contested moral values directly, this framework defines alignment as an optimization problem grounded in three system properties:
- Irreversible Harm (Hirr) — Minimize outcomes that permanently destroy future options
- Diversity & Optionality Deficit (Div) — Preserve variation and choice for system resilience
- Recursive Corruption Risk (Err) — Ensure alignment remains durable over time
All subject to a non-negotiable Truth Constraint: if a system cannot reliably distinguish what it knows from what it does not, it is disqualified from being aligned.
Status
This framework is applied philosophy, not engineering specification. It articulates what aligned systems should optimize for. How to measure and implement these optimizations remains the central open problem. The value lies in defining the optimization target and exposing measurement gaps — not claiming a deployable solution.