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
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 e…
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
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.