インシデント 852: translated-ja-Alleged Fake Citations Undermine Expert Testimony in Minnesota Deepfake Law Case
概要: translated-ja-In a legal case defending Minnesota’s deepfake election misinformation law, Stanford misinformation expert Professor Jeff Hancock's affidavit allegedly cited non-existent academic sources, potentially generated by ChatGPT. The reportedly fabricated citations appear to have undermined the credibility of his testimony.
Editor Notes: Copy of expert declaration: https://storage.courtlistener.com/recap/gov.uscourts.mnd.220348/gov.uscourts.mnd.220348.23.0.pdf (CASE 0:24-cv-03754-LMP-DLM Doc. 23)
Alleged: OpenAI と ChatGPT developed an AI system deployed by Jeff Hancock, which harmed Jeff Hancock , Mary Franson , Keith Ellison , Christopher Kohls と Chad Larson.
インシデントのステータス
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