Kohls v. Ellison sits at the intersection of two AI problems: deepfakes as the subject of litigation and AI-generated errors inside the litigation itself. That makes it a powerful case study for modern legal AI risk.

Quick Answer

Kohls v. Ellison matters because an expert declaration in a deepfake-related case included AI-hallucinated citations. The decision shows that expert credibility, evidentiary reliability, and AI verification are now tightly connected.

Why This Story Matters

The case is useful because it shows that AI risk can enter litigation through expert work, not only attorney briefing. Declarations, reports, and supporting citations can all be affected.

It also highlights the special sensitivity of AI-related cases. When the dispute itself involves synthetic media or AI harms, courts may be especially alert to the reliability of AI-assisted submissions.

Main Points From the Source

• The dispute involved a challenge to a law regulating certain election-related deepfakes.
• An expert declaration contained citations that were allegedly generated or affected by GPT-4o and could not be verified as real sources.
• The court emphasized the need for lawyers and experts to verify AI-assisted content submitted in litigation.
• The affected declaration was excluded, showing that AI errors can have direct evidentiary consequences.

What It Means for Legal AI and Law Firms

For legal teams, Kohls expands the AI governance conversation beyond lawyers. Experts, consultants, vendors, and litigation support professionals may all use AI. Their work can enter the record, and their mistakes can affect admissibility.

A mature firm policy should therefore cover outside contributors. If an expert uses AI in preparing a declaration or report, the team should understand what was used, how it was used, and how sources were verified.

Risk Patterns to Watch

The Expert Reliability Gap

An expert uses AI to draft, research, or polish work product, but no one verifies whether the supporting materials are real and accurately cited.

The AI-on-AI Litigation Problem

When a case is about AI harms, AI-generated errors inside the case can become especially damaging to credibility.

The Vendor and Consultant Blind Spot

Law firm AI policies often focus on lawyers while ignoring outside experts and consultants whose work may become evidence.

A Mindful AI Governance Lens

Mindful AI governance means expanding the circle of attention. It is not enough to ask whether attorneys used AI. The better question is whether any person or system contributing to the record used AI in a way that must be verified.

Practical Next Steps

• Ask experts whether and how AI tools were used in preparing declarations or reports.
• Require source verification for expert citations and supporting literature.
• Include AI-use questions in expert engagement letters and litigation support protocols.
• Document verification steps before submitting AI-assisted expert materials.

CounselCore Takeaway

Kohls v. Ellison shows that AI governance must reach the full litigation ecosystem. Expert materials, citations, and evidentiary submissions need the same source discipline as attorney filings.

CTA: If your firm is evaluating generative AI, start by mapping where confidential information, prompts, outputs, logs, and citations actually go. CounselCore is built around that question: how can lawyers use AI while keeping legal work controlled, grounded, and defensible?

Request a confidential CounselCore briefing or read the original source.

This article is an educational summary and is not legal advice.