About this session
AI can produce information that sounds remarkably convincing even when something inside it is wrong. A fabricated citation can look professionally formatted.
An incorrect number can appear beside several correct ones. A summary can faithfully reproduce most of a source while quietly losing the qualification that changes its meaning.
Confidence of presentation is not the same as reliability of evidence.
Participants begin by understanding the different ways AI-assisted information can fail. Some outputs contain invented facts.
Others mix real information with incorrect details, rely on outdated knowledge, overgeneralize from limited evidence or remove context during summarization. The challenge is not simply knowing that mistakes are possible.
It is learning how to identify the parts of an output that deserve scrutiny.
The session then develops a practical verification discipline. Participants learn to isolate checkable claims, match verification effort to consequence, trace claims back to appropriate evidence and verify citations, quotes, dates, numbers and summaries.
They also learn why asking the same AI system whether its previous answer was correct is not the same as independent verification.
Finally, participants examine misinformation and synthetic content in the modern workplace. AI can help create or transform images, audio, video and documents, while misleading material can also circulate without having been generated by AI at all.
Participants develop a measured approach: inspect provenance and context, seek corroborating evidence and escalate where the consequences are significant or authenticity cannot reasonably be established.
The goal is informed skepticism — not automatic trust and not automatic disbelief.
What your people take away
- Recognize common ways AI-generated information can become wrong, incomplete or misleading
- Separate checkable claims from opinion, interpretation and creative content
- Match verification effort to the potential consequence of getting something wrong
- Verify citations, sources, quotes, dates, numbers and summaries using appropriate external evidence
- Recognize warning signs in synthetic or manipulated content without assuming unfamiliar content is automatically fake
- Build a repeatable verification workflow that keeps useful AI assistance without outsourcing factual responsibility
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What each length covers
30 minutes
30 Minutes — Key Points: Recognize How AI Gets Things WrongA focused 30-minute session on three key points from Recognize How AI Gets Things Wrong: plausible does not mean true, look for mixed-accuracy answers and watch for missing context & overgeneralization.
- Plausible does not mean true
- Look for mixed-accuracy answers
- Watch for missing context & overgeneralization
Covers 3 of 4 points in Recognize How AI Gets Things Wrong.
60 minutes
Know What to Check Before You Trust ItA focused introduction to AI reliability. Participants identify common failure patterns, isolate claims that deserve verification and practice checking a citation, factual claim, number or summary using appropriate external evidence.
- AI hallucinations
- Plausible-but-wrong answers
- Mixed accuracy
- Missing context
- Outdated information
- Claim isolation
- Risk-based verification
- Source checking
- Citation checking
- Numerical verification
- AI Verification Check
- Live Q&A
Covers 1 of 4 parts: Recognize How AI Gets Things Wrong.
90 minutes
From AI Answer to Verified InformationThe extended session follows the complete verification process from identifying likely error patterns through claim triage, source selection, citation checking, numerical verification, summary comparison and synthetic-content assessment.
- AI error patterns
- Hallucinations
- Unsupported claims
- Missing context
- Date and version risk
- Claim triage
- Source quality
- Primary and secondary evidence
- Triangulation
- Fabricated citations
- Quote verification
- Numerical checking
- Summary verification
- Synthetic media
- Provenance
- Uncertainty
- Live Q&A
Covers 2 of 4 parts: Recognize How AI Gets Things Wrong and Verify the Claims That Matter.
3 hours
Covers 3 of 4 parts: Recognize How AI Gets Things Wrong, Verify the Claims That Matter and Check Sources, Numbers & Summaries.
Full day
AI Verification & Misinformation LabA hands-on full-day workshop covering all four modules. Participants investigate realistic AI outputs containing different reliability problems and build a repeatable verification workflow for claims, citations, numbers, summaries and synthetic content.
- Module 1 — Recognize How AI Gets Things Wrong
- Module 2 — Verify the Claims That Matter
- Module 3 — Check Sources, Numbers & Summaries
- Module 4 — Navigate Misinformation & Synthetic Content
- AI Error Spotting Exercise
- Mixed-Accuracy Output Review
- Claim Isolation Lab
- Verification Priority Matrix
- Source Selection Exercise
- Independent Corroboration Practice
- Fabricated Citation Challenge
- Quote Verification
- Numerical Verification Lab
- AI Summary Comparison
- Synthetic Content Scenario
- Provenance Investigation
- Uncertainty Communication Practice
- Live Q&A
Covers all 4 parts.
Also available as a 4-week or 8-week program, for change that lasts. Ask us about it.
What’s covered
Recognize How AI Gets Things Wrong
Every length- Plausible does not mean trueAI systems can generate fluent, detailed answers without having established that each statement is factually correct.
- Look for mixed-accuracy answersMany problematic outputs are not completely false.
- Watch for missing context & overgeneralizationAn AI answer can be technically based on real information while still becoming misleading because limitations, populations, dates, exclusions or uncertainty have disappeared.
- Recognize outdated or version-sensitive informationPolicies, regulations, product features, leadership roles, prices, research findings and technical specifications can change.
Verify the Claims That Matter
90 minutes and longer- Isolate the checkable claimParticipants separate factual claims from recommendations, interpretation, opinion and creative language.
- Match the check to the consequenceAn internal brainstorming suggestion does not require the same verification effort as information entering a customer proposal, executive recommendation, financial analysis or employee decision.
- Go to the source that can actually answerParticipants distinguish sources that merely repeat a claim from sources positioned to establish it.
- Triangulate when one source is not enoughSome questions cannot be resolved through a single authoritative document.
Check Sources, Numbers & Summaries
3 hours and longer- Verify citations before you use themAI-generated references may contain real-looking authors, article titles, journals, reports, URLs or document details that do not exist or do not support the claim attributed to them.
- Check quotes against the originalA quotation should be verified against the original source rather than another AI-generated response or a page repeating the quotation.
- Recalculate the numbersAI can make arithmetic, unit, percentage, spreadsheet-logic and data-interpretation errors while presenting the result confidently.
- Compare the summary with the sourceSummaries can omit exceptions, reverse emphasis or merge separate findings.
Navigate Misinformation & Synthetic Content
Full day only- Distinguish error from misleading useParticipants distinguish an AI model generating an incorrect answer from a person using AI-generated or manipulated material to create a misleading impression.
- Inspect context & provenanceScreenshots, images, audio clips and videos can be genuine, edited, synthetically generated or presented outside their original context.
- Slow down high-impact sharingContent designed to create urgency, outrage, fear or surprise can move quickly through organizations and social channels.
- Know when evidence is not strong enoughSometimes a claim cannot be verified quickly or authenticity remains uncertain.
Tools and materials
- AI Reliability Scan
- Error Pattern Guide
- Claim Isolation Guide
- Verification Priority Matrix
- Source Quality Review
- Evidence Triangulation Planner
- Citation Verification Checklist
- Source Support Test
- Quote Verification Guide
- Number & Calculation Check
- False Precision Review
- Summary Fidelity Review
- Synthetic Content Review
- Provenance Check
- AI Verification Workflow
Who it’s for
- Employees using AI assistants to research, summarize, draft or analyze workplace information
- Managers reviewing AI-assisted recommendations, reports and decision materials
- HR, Learning & Development and People teams using AI-generated research or workplace content
- Sales, marketing and communications teams producing externally shared AI-assisted material
- Customer service and professional teams where incorrect AI-generated information could affect customers or clients
- Teams that want practical verification habits without treating every AI-assisted task as a full research exercise
How booking works
- Book online. Create a free Workbliss profile, then pay with session credits, by card or by invoice.
- Pick a date. Choose a date at least 14 days ahead, or book now and set the date later. Need it sooner? Email hello@workbliss.ai and we’ll see what we can do.
- Choose your expert. Within 3 working days, we send you profiles of the experts available for your date.
- We deliver it. Your expert is briefed on your people and goals, then runs the session live online or at your site.
Questions about Check Before You Trust: Spotting AI Mistakes & Misinformation
How long is Check Before You Trust: Spotting AI Mistakes & Misinformation?
Check Before You Trust: Spotting AI Mistakes & Misinformation runs as 30 minutes, 60 minutes, 90 minutes, 3 hours or full day. You choose the length when you book. A 30-minute session covers three key points from Recognize How AI Gets Things Wrong: plausible does not mean true, look for mixed-accuracy answers and watch for missing context & overgeneralization. A 60-minute session covers Recognize How AI Gets Things Wrong in full, with a live Q&A. A 90-minute session adds Verify the Claims That Matter. A 3-hour session adds Check Sources, Numbers & Summaries. A full-day session adds Navigate Misinformation & Synthetic Content. It is also available as a 4-week or 8-week program.
Can Check Before You Trust: Spotting AI Mistakes & Misinformation be delivered online or in person?
Yes, both. It runs live online, so every office can join at the same time, or in person at your site, in any country.
How do we book Check Before You Trust: Spotting AI Mistakes & Misinformation?
Create a free Workbliss profile with your work email, then open Check Before You Trust: Spotting AI Mistakes & Misinformation to see the price for each length and book it. You can pay with session credits, by card or by invoice, and choose a date at least 14 days ahead, or set it later. Need it sooner? Email hello@workbliss.ai and we’ll see what we can do.
Who leads the session?
A vetted Workbliss expert, briefed on your people, culture and goals before the session. After you book, we send you profiles of the experts available for your date within 3 working days, so you can choose who leads it.
Can it be tailored to our company?
Yes. Every session is shaped around your goals, your people and the benefits you already offer, and delivered by experts in your people’s languages.