AI on Trial?
AI on Trial?
The legal profession is at a pivotal crossroads as artificial intelligence (AI) transforms both the substance and practice of law. Courts are now the battleground for defining AI’s legal boundaries, especially in copyright infringement, privacy violations and the reliability of AI-generated evidence. Simultaneously, law firms harness AI-powered tools to streamline litigation workflows, analyze vast data and predict case outcomes. This article delves into recent landmark cases shaping AI litigation and explores how legal technology is addressing longstanding pain points in the courtroom.
Copyright Battles? Defining Fair Use in the Age of AI
One of the most contentious legal arenas involves AI’s use of copyrighted works for training large language models (LLMs) and generative AI systems. These cases probe whether AI companies’ ingestion of vast copyrighted datasets constitutes infringement or qualifies as fair use under U.S. copyright law.
1. Kadrey et al. v. Meta
- Filed in July 2023 in the Northern District of California, Kadrey and other authors sued Meta for using millions of copyrighted books and texts without licenses to train its LLaMA AI model.
- Plaintiffs argue Meta’s wholesale copying nullifies any fair use defense, emphasizing the commercial nature of Meta’s AI and the market harm to original authors.
- Meta contends the training is transformative and protected by fair use. After an initial dismissal, the court allowed amended complaints focusing on direct harm and fair use factors.
- As of early 2025, the case features extensive amici briefs supporting the plaintiffs, signaling judicial scrutiny of AI’s data practices.
2. Brave Software v. News Corp.
- Brave Software, which operates the Brave browser and Brave Search engine, faces allegations from News Corp and others for indexing paywalled content to fuel its search engine, which AI chatbots like Perplexity use.
- Brave asserts its indexing is fair use and accuses the plaintiffs of anti-competitive tactics to stifle new entrants. Though not directly about LLMs, this case’s outcome will influence AI’s access to web content and the viability of open data sources for AI training.
3. UMG Recordings v. Suno and UMG v. Uncharted Labs
- In June 2024, major record labels sued AI music generators Suno and Uncharted Labs for allegedly training their models on copyrighted sound recordings without authorization.
- These cases mark the first major copyright infringement suits involving AI-generated music, raising questions about derivative works and the scope of copyright protection in AI outputs. Discovery disputes continue, underscoring the complexity of proving infringement in AI-generated content.
4. OpenAI Copyright Class Actions
- Multiple consolidated class actions against OpenAI allege unauthorized use of copyrighted books, code and videos in training datasets, with claims including direct and vicarious infringement, DMCA violations and unfair competition.
- Courts have dismissed some claims but allowed others to proceed, reflecting ongoing judicial efforts to balance innovation with copyright owners’ rights. The cases also spotlight the opacity of AI training data and the challenges in defining “transformative use” in AI contexts.
Privacy and Civil Rights?
AI’s deployment in law enforcement and housing has triggered lawsuits exposing systemic risks of bias and constitutional violations.
1. Facial Recognition Misidentification
- Cases like Randal Reid v. Jefferson Parish Sheriff and Murphy v. Macy’s highlight wrongful arrests and detentions caused by facial recognition AI errors.
- Plaintiffs allege violations of Fourth Amendment rights against unreasonable searches and seizures, as well as false imprisonment.
- Studies show facial recognition error rates disproportionately impact people of color, raising concerns about racial bias and due process in AI-driven policing.
2. AI-Driven Housing Discrimination
- The SDNY v. Algorithmic Equity Group settlement revealed that AI tenant screening tools perpetuated racial discrimination, echoing historic redlining practices.
- These cases underscore the need for regulatory oversight to ensure AI systems comply with civil rights laws and do not exacerbate inequality.
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How AI Works in Litigation Practice?
While courts wrestle with AI’s legality, law firms increasingly adopt AI to enhance litigation workflows.
- Document Overload: NLP summarization condenses lengthy transcripts and filings into concise briefs, saving time and reducing fatigue.
- Cost Uncertainty: Predictive analytics provide probabilistic outcomes, helping clients budget and make informed settlement decisions.
- Human Error: Automated cite-checking and fact verification reduce risks of malpractice and sanctions.
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- Rapid deposition analysis with speech-to-text and contradiction detection, accelerating case preparation by up to 60%.
- Hallucination prevention through integrated PACER and ECF verification, ensuring all citations and facts are court-verified.
- Judge-specific insights across 2,400+ federal rulings, enabling tailored legal strategies.
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