OneRange Vero

Fact-Checking & Verifying AI Output

Learners develop a repeatable process to catch errors, hallucinations, and outdated information before acting on AI output. The course covers sourcing and citations, cross-checking facts, recognizing where models are likely to be wrong, and knowing when to escalate to a human expert. The result is confident, accurate use of AI without blind trust.

What this course covers

Learners develop a repeatable process to catch errors, hallucinations, and outdated information before acting on AI output. The course covers sourcing and citations, cross-checking facts, recognizing where models are likely to be wrong, and knowing when to escalate to a human expert. The result is confident, accurate use of AI without blind trust.

The course runs across 6 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.

  • The Anatomy of AI Output: Confidence vs. Accuracy — Examine why AI models sound highly convincing even when they are incorrect. Learn to separate authoritative tone from factual correctness and identify the cognitive biases that lead to blind trust.
  • Spotting Hallucinations and Common Error Patterns — Identify the high-risk zones where AI models are most likely to hallucinate, such as generating statistics, inventing citations, or synthesizing outdated information.
  • Sourcing and Citations: Verifying AI-Generated Links — Master the process of hunting down, verifying, and validating sources and citations provided by AI. Learn how to handle 'ghost' references that do not exist.
  • Cross-Checking Facts: Building a Verification Workflow — Establish a repeatable, multi-step workflow to cross-reference AI-generated facts against trusted external databases, primary sources, and authoritative search engines.
  • When to Escalate: Knowing Your Limits — Define clear thresholds for when an AI output cannot be verified with standard tools and must be escalated to a human subject matter expert to mitigate risk.
  • Comprehensive Verification Challenge — Apply your end-to-end verification workflow in a simulated, high-stakes scenario. Review an AI-generated report, spot the errors, verify the sources, and make escalation decisions.

Skills you build

Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick. This course maps to Fact-Checking, Critical Thinking, AI Output Interpretation, Fact-Checking & Source Evaluation, AI Risk Management, Understanding AI Limitations, Working with AI Tools, Fact Verification.

  • Fact-Checking
  • Critical Thinking
  • AI Output Interpretation
  • Fact-Checking & Source Evaluation
  • AI Risk Management
  • Understanding AI Limitations
  • Working with AI Tools
  • Fact Verification

Who it is for

All employees. The material is pitched at beginner level, and takes roughly 90 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

It sits in the Foundation track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.

How it is delivered and assessed

Delivery is conversational and interactive, including branching scenario, guided lab exercises. There is no video to sit through and no slide deck to click past.

Understanding is checked with a lab assessment of 5 items, with a pass mark of 70%.

Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Related

Course code FND-106.