# AI for Federal Labor Relations Specialists Course (Self-Paced) Canonical URL: ## Overview This self-paced course helps federal labor relations professionals understand how generative AI can support high-stakes LR tasks without replacing expert judgment, legal review, or agency-specific requirements. Participants will learn how to use AI to analyze collective bargaining agreement language, research grievance and arbitration issues, compare ULP fact patterns, and create reusable prompt workflows while protecting sensitive information. Through structured lessons, demonstrations, practice prompts, and applied exercises, participants will learn how to sanitize inputs, evaluate AI-generated summaries, identify hallucinated citations, and verify outputs using authoritative federal labor relations resources. The course is designed for professionals with prior LR experience who want a flexible way to explore responsible AI use for daily labor relations work. ## What you'll learn - Recognize responsible AI use cases for federal labor relations specialists - Apply confidentiality and privilege guardrails when preparing AI prompts - Use AI to extract, summarize, and compare CBA clauses from sanitized examples - Create first-draft outlines for grievance responses and related LR documents - Compare ULP scenarios to analogous fact patterns while maintaining human verification - Build a reusable prompt library for CBA, grievance, arbitration, and ULP workflows ## Prerequisites Participants should have completed [Federal Labor Relations Course (Basic)](/courses/federal-employee-relations-basic) and ideally [Federal Labor Relations Course (Intermediate)](/courses/federal-labor-relations-intermediate), or have equivalent federal LR/ER experience. They should understand 5 U.S.C. Chapter 71, including management rights, representation rights, ULPs, grievance procedures, Weingarten rights, bargaining subjects, information requests, and FLRA resources. ## Curriculum #### Module 1: AI Foundations and Compliance for Labor Relations - Understand what generative AI is and how it can support federal labor relations work - Review responsible AI use considerations based on OPM and OMB guidance - Identify labor relations-specific guardrails for confidentiality, privilege, and pre-decisional content - Learn what information should not be entered into AI tools, including employee names, case numbers, and draft management positions - Recognize hallucinated citations and other common AI risks in legal-adjacent work - Evaluate sample LR scenarios to determine whether AI use is appropriate, appropriate with caution, or not appropriate #### Module 2: CBA Analysis with AI - Build effective prompts for contract analysis using role, context, constraints, and output format - Practice sanitizing collective bargaining agreement language before using AI tools - Use AI to extract specific clauses, such as official-time provisions, from a sample CBA - Compare grievance procedure language across two sample CBAs - Review AI-generated summaries for accuracy against the original contract language - Identify risks such as missed cross-references, inaccurate paraphrasing, and misread terms like “shall” and “may” #### Module 3: Grievance Research with AI - Explore how AI can support grievance research, arbitration summaries, and fact-pattern timelines - Use AI to summarize an arbitration decision excerpt and identify the controlling rationale - Draft a Step 2 management response outline using a sanitized grievance scenario - Apply AI to information request analysis, including particularized-need considerations under §7114(b)(4) - Identify AI risks such as fabricated FLRA decisions, misstated outcomes, and oversimplified procedural history - Verify every cited case, quoted statute, and referenced source against authoritative materials #### Module 4: ULP Comparison and Capstone - Use AI to compare sanitized fact patterns to existing unfair labor practice case law - Draft fact-pattern comparisons, position statement outlines, and witness-prep question lists - Review AI outputs for tone, bias, accuracy, and unintended admissions - Build a personal prompt library of vetted prompts for recurring labor relations tasks - Complete a capstone exercise using a realistic LR scenario, such as refusal to bargain, interference, formal discussion, or Weingarten allegations - Verify all AI-generated citations and self-assess the final output using a review checklist ## Pricing **Tuition:** $675