Rule-Governed Systems in Adaptive Environments: An HF-Grounded Framework for LLM Alignment

A working draft, problem-space proposal, and call for collaboration:Contemporary large language model (LLM) alignment frameworks are predominantly structured around machine learning optimization, policy-layer rule sets, and compliance-oriented legal risk management. Such approaches are architecturally insufficient for systems designed for sustained, high-stakes interaction with human beings, because they do not incorporate the adaptive, context- aware, and error-tolerant design principles established by decades of research in human factors engineering, resilience engineering, and ecological psychology.