The Algorithmic Perjury: Economic, Legal, and Reputational Liabilities from AI Hallucinations
The Algorithmic Perjury
A Comprehensive Analysis of Economic, Legal, and Reputational Liabilities Arising from Generative AI Hallucinations
In This Report
Executive Summary
The integration of Large Language Models into global infrastructure has precipitated a crisis of epistemic integrity. While Generative AI offers unprecedented efficiencies, its probabilistic architecture renders it susceptible to "hallucinations"—confabulations that have evolved into significant vectors of professional liability, financial loss, and reputational ruin.
Critical Finding
The "human-in-the-loop" defense is calcifying into a doctrine of strict liability. Courts and regulators increasingly hold professionals absolutely liable for AI output.
1. The Crisis in Jurisprudence
Mata v. Avianca, Inc. (S.D.N.Y. 2023)
LANDMARKThe "Patient Zero" of Legal AI Malpractice
Attorney Steven Schwartz used ChatGPT for legal research. The brief cited multiple fabricated judicial decisions including Varghese v. China Southern Airlines and Petersen v. Iran Air.
When asked to confirm cases were real, ChatGPT "hallucinated" validation. Judge Castel characterized submissions as "bogus judicial decisions with bogus quotes and bogus internal citations."
Sanction
$5,000 fine on attorneys. Court found "bad faith" for failing to withdraw fake citations once questioned.
Park v. Kim (2nd Cir. 2024)
APPELLATEAttorney cited non-existent decision from ChatGPT. Second Circuit stated this "falls below basic obligations of counsel" and referred attorney to Grievance Panel—escalating from fines to licensure review.
AI hallucinations often confirm user bias, providing the "desired" answer when actual law doesn't support it—the "Sycophancy Trap."
2. The Procurement Paradox
The Exdrog Case (Poland)
€3.7M LOSSExdrog bid lowest on a road maintenance contract. Their 280-page justification cited tax rulings that did not exist—AI hallucinations.
Poland's National Appeal Chamber ruled failure to verify AI output constituted "misleading the contracting authority." Bid rejected. Entire €3.7 million contract lost.
Precedent
Unverified AI output is indistinguishable from fraud in procurement officials' eyes.
3. Corporate Liability
Moffatt v. Air Canada
CONSUMER LAWCustomer queried chatbot about bereavement fares. Bot promised retroactive refund—contradicting actual policy. Air Canada argued chatbot was a "separate legal entity."
Tribunal rejected this as "remarkable" and ruled: Companies cannot deploy AI to reduce costs without accepting full liability for AI output.
Google Bard Launch
$100B LOSSBard claimed James Webb Telescope took "first pictures of exoplanet"—actually taken by VLT in 2004. Stock dropped ~9%, wiping $100 billion in market cap in one day.
"Hallucination risk" is now a material risk factor for public tech companies.
4. Conclusion: Zero Trust Imperative
Generative AI shifts cost of production to cost of verification. The "human-in-the-loop" is strictly liable—"the bot did it" is no longer valid defense.
Zero Trust Requirements
- No Blind Filing: Line-by-line verification required
- Mandatory Disclosure: AI use must be disclosed
- Verification Tooling: Detect hallucinations before submission
The era of "move fast and break things" is over for Generative AI. If you use AI to break the truth, you will pay for the pieces.
| Entity | Incident | Impact |
|---|---|---|
| Alphabet | Demo Hallucination | $100B Market Cap Drop |
| Exdrog | Bid Hallucination | €3.7M Contract Lost |
| Air Canada | Chatbot Policy | Strict Liability Precedent |
| Levidow Firm | Legal Citations | $5,000 Sanction |
| Deloitte AU | Report Errors | $290K Refunded |
Disclaimer: This report is for informational purposes only and does not constitute legal or professional advice.
Copyright © 2025 Aliff Capital. All rights reserved.
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