Description: In Fletcher v. Experian Information Solutions, Inc., the Fifth Circuit found that attorney Heather Hersh had used generative AI to draft a substantial portion of a reply brief that contained fabricated legal support and factual representations. The court first issued a show-cause order and later imposed a $2,500 sanction, linking the filing errors to unverified AI-generated output.
Editor Notes: Timeline notes: The incident seems to have occurred sometime in early September 2025. The incident ID date of 12/18/2025 refers to the Fifth Circuit having issued a show-cause order. On 02/18/2026, the court imposed the fine. The incident ID was created 04/18/2026.
Entities
View all entitiesAlleged: Large language model developers developed an AI system deployed by Heather Hersh, which harmed United States Court of Appeals for the Fifth Circuit , Judicial integrity , James Fletcher , Experian Information Solutions and Epistemic integrity.
Alleged implicated AI system: Large language models
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
3.1. False or misleading information
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Misinformation
Entity
Which, if any, entity is presented as the main cause of the risk
Human
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline
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Feb 18 (Reuters) - A federal appeals court on Wednesday expressed frustration that lawyers continue to submit briefs containing AI-generated fictitious case citations and other hallucinated material, saying the problem "shows no sign of aba…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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