Name: AI for Federal Labor Relations Specialists Course (Self-Paced)
Price: 675.0 USD
Availability: InStock

This course includes

4 hours of project-based training from experts
Answers from real instructors
Retake for free within 1 year
Verified digital certificate of completion
Learn at an accredited institution

This course is self-paced. For live online instruction, take AI for Federal Labor Relations Specialists.

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.

This course has a prerequisite

Participants should have completed Federal Labor Relations Course (Basic) and ideally Federal Labor Relations Course (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.

Tuition

Full Tuition

$675
Due before the class starts

This course includes

4 hours of project-based training from experts
Answers from real instructors
Retake for free within 1 year
Verified digital certificate of completion
Learn at an accredited institution

Learning Experience Highlights

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AI for Federal Labor Relations Specialists Course (Self-Paced) Curriculum

What You'll Learn at a Glance

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

Course Syllabus

Download Syllabus PDF

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

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