human-in-the-loop-nlp

Overview

This repository presents a human-in-the-loop NLP governance architecture focused on auditability, role stability, and ethical safeguards for conversational AI systems.

The project emerged from a real-world analysis of conversational AI failure modes, including role drift, authority ambiguity, and post-hoc response instability. Full analysis available in docs/whitepaper.md.

This repository contains a governance-first draft. Canonical reference anchored at Git tag v0.1.

Core Principles

• Human authority is non-negotiable
• AI systems must remain assistive, not directive
• All decisions must be auditable
• Ethical constraints are architectural, not optional

Scope

This repository is intended for:

• NLP engineers
• AI governance researchers
• Safety and ethics reviewers
• Multi-agent system architects

What This Is Not

• Not a benchmark
• Not a chatbot demo
• Not a marketing artifact

This is a governance-first technical exploration.

License

Apache License 2.0 — see LICENSE file.

Ethical Use Notice

See ETHICAL_NOTICE.md for restrictions and intent.