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AI Blocks › Hire and look after your people

HR AI use policy writer

Describe how you use AI in hiring. Get a use policy, a bias check and a staff notice. Not legal advice.

HR AI use policy writer is a free AI skill for the job "Hire and look after your people". Give the instructions to an AI assistant that supports the required files and tools, then review its output.

Free · No account · MIT licence · Made by Tuan Duc Tran

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Download the complete instructions and supporting files. Add the material the task needs in an AI that supports those files and tools.

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Made by Tuan Duc Tran. See the original on GitHub; we copied it as it is, with its licence.

What it does

A written rulebook for how your HR team may use AI, plus the notices people need to see. Describe how AI touches hiring and people decisions and get a policy, a bias check plan and a plain-language staff notice. It is not legal advice, so have counsel review it. The skill drafts the policy and requires a person to review any AI-assisted decision with real consequences, such as hiring or firing. It builds a review step to run before any new HR AI tool is adopted and a vendor questionnaire on training data and fairness. It adds an escalation path for people who want to challenge a decision, documentation rules, candidate disclosures and training points for HR staff.

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Full instructions
  • Add it to your AI once: download it and add the folder to Claude, ChatGPT or Codex as a skill.
  • Ask for the job in your own words. Your AI opens the skill when it fits.
Full instruction file

HR AI governance

Helps HR and compliance teams govern the responsible, compliant use of AI tools across the employee lifecycle, from hiring algorithms to performance analytics and employee monitoring.

Supported tasks

  • Drafting an AI use policy for HR processes
  • Assessing bias and disparate-impact risk in AI-driven hiring tools
  • Designing a governance review process for adopting new HR AI tools
  • Writing employee-facing disclosures about AI use in HR decisions
  • Mapping AI-related regulatory requirements relevant to HR (e.g., automated employment decision tools)
  • Designing human-in-the-loop review requirements for AI-assisted decisions
  • Building an AI vendor due-diligence checklist for HR tools
  • Drafting data privacy guidance for AI tools processing employee data
  • Creating training for HR staff on responsible AI use
  • Auditing existing HR AI tools against governance standards
  • Designing escalation processes for AI-related employee complaints
  • Drafting documentation standards for AI-assisted employment decisions

Key prompts

Policy and governance design
  1. "Draft an AI use policy governing how HR may use AI tools in hiring and performance decisions."
  2. "Design a governance review process required before adopting a new HR AI tool."
  3. "Write a human-in-the-loop requirement for AI-assisted hiring decisions."
  4. "Create an escalation process for employees who want to contest an AI-assisted decision."
  5. "Draft documentation standards HR must follow when using AI in employment decisions."
Risk and bias assessment
  1. "Design a bias audit framework for an AI-driven resume screening tool."
  2. "Identify disparate-impact risks in an AI-based candidate ranking system."
  3. "Create a checklist to evaluate an AI vendor's fairness and transparency practices."
  4. "Draft questions to ask an AI hiring tool vendor about training data and validation testing."
  5. "Assess data privacy risks of an AI tool that analyzes employee communications."
Disclosure and training
  1. "Write an employee-facing disclosure explaining how AI is used in the hiring process."
  2. "Draft training content for HR staff on responsible and compliant AI use."
  3. "Create talking points for a manager asked about AI use in performance reviews."
  4. "Summarize regulatory requirements for automated employment decision tools in [jurisdiction]."
  5. "Draft a candidate notice required before using an AI assessment tool in hiring."

Tips

  • Require human review of any AI-assisted decision with material employment consequences (hiring, termination, promotion).
  • Document what data trains and validates any AI hiring tool before adoption, not after a complaint.
  • Disclose AI use to candidates and employees clearly, in plain language, ahead of the decision being made.
  • Reassess AI tools periodically for bias, since model behavior and underlying data can drift over time.

Common mistakes

  • Adopting AI hiring tools without vendor documentation on bias testing or validation studies.
  • Treating AI output as final without a meaningful human review step.
  • Failing to notify candidates or employees that an AI tool is involved in a decision affecting them.
  • Assuming one-time bias testing is sufficient without ongoing monitoring.