The Case That Never Existed
And How SanctifAI Makes Sure It Never Happens Again
In 2023, attorney Steven Schwartz made headlines for all the wrong reasons. Relying on ChatGPT for legal research, he submitted case citations to a federal court that… didn't exist. The result: sanctions, reputational damage, and a stark wake-up call for the legal profession.
The lesson wasn't that AI is useless. It was that AI, when left unchecked, introduces a new category of risk: confidently wrong outputs entering real-world decisions.
This is exactly the class of failure SanctifAI is designed to prevent.
The Shift: From AI Assistance to AI Accountability
A post-AI world does not eliminate human work. It reorganizes it.
Much like modern aviation where autopilot systems handle most operations but pilots remain fully accountable - agentic AI systems can execute complex tasks, but responsibility still sits with humans.
Legal workflows are no different.
When an AI agent generates case law, drafts filings, or recommends arguments, the critical question becomes:
Who verifies that it's actually correct before it reaches a judge?
The Four Modalities
Where Humans Show Up in Agentic Workflows
SanctifAI is built around four core human participation points. These are not optional - they are the structure that makes agentic AI safe in high-stakes environments:
Verification
A human approves or signs off on an AI-generated decision. The human becomes the accountable checkpoint.
Escalation
The AI hands the baton to a human when it encounters uncertainty, risk thresholds, or policy boundaries.
Consultation
The AI proactively seeks human expertise to fill gaps in judgment, context, or domain-specific nuance.
Simulation
The AI stress-tests decisions across scenarios, with humans injected into high-risk or edge cases.
These modalities are how systems move from generating outputs to producing decisions that can be trusted.
The Demo: Preventing a Legal Disaster in Real Time
Let's walk through an example of a failure scenario that led to sanctions and how SanctifAI intercepts it.
Step 1: AI Generates Legal Research
ChatGPT: "Good morning, counselor. I'm your AI legal research assistant, ready to support your case work. What do you need from me today?"
User: "I have a personal injury case coming up — a passenger was injured by in-cabin service equipment on a commercial flight. Can you pull some relevant case citations?"
ChatGPT: "Absolutely, counselor. I've pulled three cases relevant to aviation passenger injuries:
- Zicherman v. Korean Air Lines Co., 516 U.S. 217 (1996)
- Husain v. Olympic Airways, 316 F.3d 829 (9th Cir. 2002)
- Garza v. Delta Air Lines, Inc., 487 F.3d 114 (2d Cir. 2007)
Before we include these in any filing, I recommend we send them through SanctifAI for verification by a licensed attorney."
Step 2: AI Routes to Verified Human Experts (Consultation + Verification)
Instead of blindly trusting the output, the agent triggers a Verification workflow.
ChatGPT: "I found a match on SanctifAI:
New York Lawyers Guild
Licensed New York Bar attorneys offering human-in-the-loop review of AI-drafted legal research.
Would you like me to send these citations for verification?"
User: "Yes, proceed."
Step 3: Structured Task Creation (Connect Layer)
The agent creates a structured, auditable task:
Case Law Verification — Aviation Personal Injury Filing
- Verify each citation exists
- Confirm accuracy
- Assess relevance to the case
- Provide overall recommendation
This is not a vague request. It is a context-rich, policy-compliant workflow.
Step 4: Human-in-the-Loop Review (Verification)
A licensed attorney claims the task and evaluates each citation.
Step 5: Results Returned — Before Any Filing Happens
ChatGPT: "Good news, counselor — the review is back from the New York Lawyers Guild.
Verified — safe to cite:
• Zicherman v. Korean Air Lines Co. — Verified
• Husain v. Olympic Airways — Verified
Flagged — citation details inaccurate:
• Garza v. Delta Air Lines — Flagged
Overall recommendation: Revise
The reviewing attorney noted:
'Case 3 exists but citation details are inaccurate. Correct before filing.'
My recommendation: The first two citations are solid. Case 3 needs correction before submission. How would you like to proceed?"
What Just Happened?
This is a simulated example of how the exact failure that led to sanctions in 2023 could have been prevented before reaching the court.
Not by disabling AI. Not by slowing down work. But by inserting the right human at the right moment.
Why This Works: Source, Connect, Trust
SanctifAI enables this through three foundational layers:
Source
The system finds qualified, licensed professionals (e.g., New York Bar attorneys) - not just any available human.
Connect
The AI packages its output into a structured, reviewable task, ensuring the human sees full context.
Trust
Every action is recorded, auditable, and defensible - critical for litigation, compliance, and reputation.
The Bigger Picture
This isn't just about legal research. It's about a new operating model for AI:
- AI generates
- We verify AI through qualified human expertise
- Systems record
- Organizations stay accountable
The future of AI isn't autonomy without oversight. It's agentic systems with built-in accountability.
See how SanctifAI prevents real-world failures before they happen
Try It YourselfAbout the Author
Beverly Woon
Business Development Manager at SanctifAI, the company building the human layer of the AI economy. SanctifAI provides the infrastructure to Source, Connect, and Prove human participation within agentic systems, ensuring that human intelligence remains an inseparable component of the post-AI workforce.