HUR governance
Responsible AI Position
Last updated: 8 August 2026
HUR supports practical, proportionate, and human-governed use of AI in HR and PeopleOps. AI should strengthen analysis, access, documentation, and productivity without displacing accountable judgement in decisions that affect people.
Core principles
- Purpose first: define the approved use case, user, data, benefit, affected people, and potential harm before selecting or deploying a tool.
- Human accountability: name who reviews the output, what they must verify, what evidence they require, and who owns the final decision.
- Data minimization: use only authorized, necessary information and do not enter confidential employee data into unapproved tools.
- Transparency and traceability: document higher-consequence uses, material assumptions, review, changes, decisions, and escalation as appropriate.
- Fairness and challenge: create a meaningful route to question, correct, or pause an inappropriate output or use.
- Monitoring: review accuracy, adoption, incidents, drift, changing risk, and whether continued use remains justified.
What HUR can support
HUR can support readiness assessment, use-case prioritization, AI use-case and risk registers, human-oversight matrices, acceptable-use guidance, confidentiality protocols, requirements, vendor-evaluation support, prompt and workflow libraries for approved tasks, adoption workshops, and implementation review.
What HUR does not claim
HUR does not currently provide algorithmic bias certification, legal certification, penetration testing, cybersecurity assurance, custom AI model development, technical model validation, or autonomous employee-selection systems. Qualified specialists are required where those services are necessary.
Framework use
HUR may use the NIST AI Risk Management Framework functions—Govern, Map, Measure, and Manage—to structure work. Reference to NIST does not mean HUR or a client system is certified, approved, or endorsed by NIST. Methodology will adapt as authoritative guidance changes.