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The New York Times and the Chicago Tribune have filed separate lawsuits against Perplexity AI, alleging that the company's search engine unlawfully scrapes and distributes copyrighted content. The lawsuits claim that Perplexity's AI generates responses that substitute for the original reporting, threatening the publishers' business models. Additionally, the plaintiffs allege that the AI system produces 'hallucinations' and falsely attributes this fabricated information to the newspapers, causing reputational damage and potential trademark infringement.
On December 5, 2025, The New York Times sued Perplexity, alleging the company used copyrighted Times articles without permission to train its AI system and generated outputs that reproduced Times content or falsely attributed fabricated information to the newspaper. The suit claims the conduct harmed the Times's business and brand. Perplexity denies wrongdoing.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
AI systems capable of creating economic or cultural value, including through reproduction of human innovation or creativity (e.g., art, music, writing, coding, invention), destabilizing economic and social systems that rely on human effort. The ubiquity of AI-generated content may lead to reduced appreciation for human skills, disruption of creative and knowledge-based industries, and homogenization of cultural experiences.
Also classified as
The AI system generates fabricated information ('hallucinations') and falsely attributes it to reputable news organizations, spreading misinformation.
Perplexity's AI search engine reproduces and abridges original journalistic work, directly competing with publishers and devaluing the human effort and financial investment required to produce news.
AI system
Due to a decision or action made by an AI system
Unintentional
Due to an unexpected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The reputational and trademark risks are caused by the AI system generating hallucinations and abridged content post-deployment, which is an unintentional outcome of its synthesis goals.
Added categories peak at 3: Substantial (Epistemic Harm, Inferred)
The lawsuits against Perplexity AI highlight minor national security concerns, primarily centered on economic challenges to the media sector and the degradation of the information ecosystem through AI hallucinations. The incident is a commercial and legal dispute manageable within existing judicial frameworks, posing no immediate threat to critical infrastructure or state sovereignty.
The reports describe Perplexity AI as an AI-powered search engine and chatbot that retrieves, synthesizes, and displays information in response to user queries, acting as an assistant to help users find answers.
Limited Risk: The system is a chatbot and search engine that generates content, which falls under the transparency obligations of Limited Risk (Level 3) systems under the EU AI Act.
The system is designed to scrape the web in real-time to answer user queries and synthesize search results into direct answers.
The reports provide clear, consistent details about the lawsuits filed by the New York Times and Chicago Tribune against Perplexity AI, detailing the specific claims of copyright infringement, trademark violation, and hallucinations. The legal and technical context is well-documented across multiple reputable news sources.
The incident could be viewed purely as a commercial/copyright dispute rather than an AI safety issue, but the inclusion of AI hallucinations and trademark dilution directly links it to AI system limitations.
Technology
AI Model Hallucinations
The model generated fabricated information falsely attributed to publishers.
Verbatim Output Generation
Search engine generates outputs strikingly similar to original copyrighted text.
Bypassing Web Blockers
AI crawlers bypassed web standards used by publishers to block scraping.
Data Inputs
Unauthorized Web Scraping
Crawlers scraped millions of copyrighted articles without permission.
Scraping Paywalled Material
The AI system scraped and copied content behind publisher paywalls.
Lack of Source Verification
Insufficient filtering allowed scraping of protected trademarked data.
Human Factors
User Misinterpretation
Users mistook AI hallucinations for actual newspaper reporting.
Lack of Trust in AI Firms
Publishers distrust AI firms due to historical internet disruption of news.
Process and Methods
No Licensing Agreements
Perplexity built commercial products without securing content licenses.
Inadequate Content Filtering
Lack of mechanisms to filter out famous registered trademarks from outputs.
Ignoring Cease and Desist
Startup continued using content despite receiving a cease and desist notice.
Management
Prioritizing Growth Over Compliance
Aggressive market strategy prioritized data acquisition over IP compliance.
Dismissive Stance on IP Claims
Communications head dismissed lawsuits as standard resistance to new tech.
Refusal to Compensate Publishers
Management failed to negotiate agreements with publishers for content use.
Regulatory Environment
Ambiguous Fair Use Boundaries
AI companies exploit unclear legal limits of fair use for training data.
Unresolved Copyright Standards
Lack of clear legislative guidelines on GenAI and copyright protection.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
