Description: A litigant in person (LiP) in a Manchester civil case presented false legal citations generated by ChatGPT. It fabricated one case name and provided fictitious excerpts for three real cases, misleadingly supporting the LiP's argument. The judge, upon investigation, found the submissions to be inadvertent and did not penalize the LiP.
Entities
View all entitiesAlleged: OpenAI developed an AI system deployed by Unnamed Manchester litigant, which harmed Unnamed Manchester litigant , Manchester court system and General public.
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
AI
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
A litigant in person tried to present fictitious submissions in court based on answers provided by the ChatGPT chatbot, the Gazette has learned.
The civil case, heard in Manchester, involved one represented party and one unrepresented: pro…
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
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