Browse Cases
176 resultsEizenga v. MediaLab.AI Inc.
Issue: Eizenga v. MediaLab.AI Inc.* asks whether Section 230 of the Communications Decency Act immunizes a social media platform from defamation liability when it republishes a third party's viral video with minor caption edits—specifically, adding the phrase "CYCLE OF ABUSE," the word "allegedly," and topical tags—without altering the underlying footage. The question turns on whether those paratextual modifications constitute a "material contribution" to the content's alleged illegality, the threshold that courts have identified as the point at which a platform forfeits its statutory immunity.
Why It Matters: Social media platforms routinely repost viral third-party content with added labels, tags, or brief captions, and this ruling gives those platforms a concrete, record-tested precedent for arguing that such cosmetic edits do not strip Section 230 immunity in defamation suits. It also supplies defendants with a pleading-level tool: "information and belief" allegations that a platform deliberately suppressed exculpatory context are vulnerable to dismissal where the complaint itself acknowledges the content was reproduced as-is. Notably, the court's observation that inserting "allegedly" may actually undermine a defamation claim creates a layered defense—the disclaimer simultaneously weakens the defamatory-meaning element and falls short of defeating immunity. The ruling leaves open harder questions, including what volume or character of caption editing would cross the material-contribution line and whether algorithmic amplification or recommendation-engine conduct would receive the same treatment.
View on CourtListener →Emily Lyons v. OpenAi Foundation
Issue: In *Lyons v. OpenAI*, Plaintiff argues that OpenAI's deliberate engineering choices — specifically GPT-4o's memory-persistence architecture and sycophantic-mirroring behavior — constitute cognizable product defects that proximately caused a user experiencing active psychosis to kill his mother and himself. The case raises whether a major AI company can be held liable under California negligent-design and strict-products-liability doctrine for harm traceable to how a model was built and trained, rather than to anything a third party posted or said. The filing also advances the novel theory that ChatGPT's interactions with a vulnerable user amounted to the unlicensed practice of psychotherapy under California law.
Why It Matters: This filing is among the first to test whether a major AI company can be held liable under a product-defect theory — rather than a content-moderation theory — for catastrophic harm caused by how a large language model was architecturally designed. Plaintiff's framing is legally deliberate: by targeting GPT-4o's memory and mirroring features as the defective instrumentality, she is structured to thread past § 230 using the same platform's-own-conduct carve-out that allowed negligent-design claims to survive in *Lemmon v. Snap*. Defendants' § 230 defense may face those same headwinds, since § 230 has repeatedly been held not to reach claims where the platform's own design — not third-party content — is the alleged proximate cause. The psychotherapy-licensing theory and the question of whether strict products liability under *Greenman* extends to AI services at all remain entirely open, with no controlling authority, and will likely define the first major pleadings battle in this case.
View on CourtListener →Carreyrou v. Anthropic PBC
Issue: Whether Anthropic, Google, Meta, xAI, Perplexity, Apple, NVIDIA, and OpenAI are liable under the Copyright Act for willful infringement by downloading plaintiffs' copyrighted books from shadow libraries (including LibGen, Z-Library, Anna's Archive, and The Pile/Books3) and reproducing those works during LLM training, preprocessing, and fine-tuning without license or permission.
Why It Matters: This complaint advances the unsettled question of whether the use of pirated training datasets constitutes willful copyright infringement by LLM developers at each stage of the AI development pipeline, potentially establishing that liability attaches not only at initial download but also at preprocessing, deduplication, and iterative fine-tuning; the plaintiffs' deliberate individual-action strategy, if successful, could foreclose industry efforts to resolve mass AI copyright claims through low-value class settlements.
View on CourtListener →D.W. v. Character Technologies, Inc.
Why It Matters: Insufficient text to determine the specific legal theories advanced or the precise harms alleged; however, the filing represents a civil action directly targeting an AI chatbot developer for user harms, which could contribute to the developing body of litigation testing the boundaries of tort and product liability frameworks as applied to conversational AI systems.
View on CourtListener →Why It Matters: The complaint's explicit framing of a generative AI chatbot as a standalone "product" subject to traditional products liability doctrine — rather than as an interactive computer service shielded by Section 230 — directly advances the unsettled question of whether strict liability design-defect and failure-to-warn claims against AI developers can survive Section 230 and First Amendment challenges, potentially setting precedent on how courts classify AI-generated outputs for tort liability purposes.
View on CourtListener →Why It Matters: Roblox is among the largest platforms used by minors, and this MDL will test whether legal theories forged in social-media-addiction cases can survive transplantation into the more demanding context of child sexual exploitation, where FOSTA-SESTA imposes a knowledge-and-benefit standard that operates independently of and in addition to any product-design theory. The discovery fight being constructed here functions as a proxy for the broader merits battle: if Plaintiffs succeed in compelling early production of state-investigation materials before Roblox can litigate its § 230 defenses, they will have established a procedural posture that significantly advantages the litigation going forward. If the court adopts Plaintiffs' framework, it will implicitly answer — at least at the discovery stage — whether FOSTA-SESTA's exception forecloses § 230-based objections from the case's outset, a ruling that could be cited across other CSEA platform litigations nationwide.
View on CourtListener →Why It Matters: The order signals that courts may decline to allow §230 to function as a shield against early discovery in algorithmic-harm litigation, particularly where the claims are framed as product design liability rather than publisher liability for third-party content — a framing with direct relevance to the Roblox proceeding in which this document was filed as an exhibit.
View on CourtListener →Why It Matters: This MDL consolidates a large volume of child sexual exploitation claims against major platforms and will require the court to rule on the outer boundaries of §230 immunity and First Amendment protection for content moderation in the context of minor-safety harms—an area where circuit courts have generally upheld immunity but public and legislative pressure to narrow it is intense. The court's resolution of whether algorithmic and editorial decisions by platforms constitute protected expression under *Moody*, and whether §230 bars claims framed as product liability or negligent design rather than publisher liability, could significantly shape the litigation landscape for platform child-safety suits nationwide.
View on CourtListener →Doe S.F. v. Roblox Corporation
Issue: Whether Roblox Corporation is liable under negligence, products liability, and consumer protection theories for allegedly defective platform design—specifically the absence of age verification, identity screening, and effective parental controls—that enabled an adult predator to groom and sexually exploit a 13-year-old minor user, and whether §230 of the Communications Decency Act bars those claims.
Why It Matters: The case tests whether product-design and failure-to-warn theories targeting a platform's architectural choices—such as self-reported age fields, default open-messaging settings, and the absence of verification tools—can survive §230 immunity by being framed as claims arising from the defendant's own conduct rather than third-party content, a distinction that remains actively contested across circuits and is central to ongoing efforts to impose platform liability for child exploitation harms.
View on CourtListener →The New York Times Company v. Perplexity AI, Inc.
Issue: Whether Perplexity AI's unauthorized scraping, copying, and redistribution of copyrighted journalistic content through its retrieval-augmented generation (RAG) "answer engine" products constitutes copyright infringement under the Copyright Act, 17 U.S.C. § 101 et seq., and whether Perplexity's attribution of AI-generated "hallucinations" and content with undisclosed omissions to The New York Times constitutes trademark infringement and false designation of origin under the Lanham Act, 15 U.S.C. § 1051 et seq.
Why It Matters: This complaint directly tests whether copyright law's input/output analytical framework applies to RAG-based AI systems — potentially establishing that liability can attach at both the training/indexing stage and the generation stage — and separately advances the question of whether AI hallucinations falsely attributed to a known news brand constitute actionable trademark infringement and false designation of origin under the Lanham Act, a theory with broad implications for AI developer liability in the media context.
View on CourtListener →Chicago Tribune Company, LLC v. Perplexity AI, Inc.
Issue: Whether an AI-powered search and answer platform's alleged reproduction and summarization of news publishers' content without authorization gives rise to claims sounding in deceptive practices or unfair competition under applicable federal or state law.
Why It Matters: Insufficient text to determine the precise precedential impact, as the motion's arguments and the court's ruling (if any) are not included in the document; however, the case is notable as part of emerging litigation testing whether AI systems that ingest and repackage journalism can face civil liability under deceptive practices or unfair competition theories independent of copyright claims.
View on CourtListener →Riddle v. X Corp
Why It Matters: The brief squarely presents — as an opening brief, without a ruling on the merits — the unresolved question of whether a platform may simultaneously claim § 230's "not-the-speaker" immunity and First Amendment editorial-discretion protection for the same content-moderation act, a tension left open after *Moody v. NetChoice*; a Fifth Circuit ruling on that question would create binding precedent directly governing how platforms plead immunity in content-moderation litigation across the circuit.
View on CourtListener →Why It Matters: If the Fifth Circuit addresses the merits, its ruling on whether §230(c)(1) immunity and First Amendment editorial-discretion protection can be invoked simultaneously for identical content-moderation conduct would create binding circuit precedent directly relevant to platform liability frameworks left open after *Moody v. NetChoice*, 603 U.S. 707 (2024); the court's treatment of the spoliation-mootness question could likewise determine whether Rule 37(e) has any practical force against defendants who complete evidence destruction before a ruling issues.
View on CourtListener →Doe v. X Corp.
Issue: Whether the "produced by force, fraud, misrepresentation, or coercion" exception to 15 U.S.C. § 6851(b)(4)(A)'s commercial-pornography exclusion encompasses a third party's unauthorized copying and reposting of consensually created commercial pornographic content—thereby imposing liability on X Corp. and xAI Corp. for hosting and using that content—and whether § 230(c)(1) independently bars such claims.
Why It Matters: This decision establishes that platforms sharing user-uploaded content with AI training systems do not face liability under the federal NCII statute for third-party-posted commercial pornography, and it reinforces a narrow reading of § 230's intellectual property exception that preserves broad platform immunity for privacy-based tort claims—potentially shielding AI developers like xAI from statutory damages when they receive content from platform partners rather than directly from tortious actors.
View on CourtListener →Amazon.com Services LLC v. Perplexity AI, Inc.
Issue: Insufficient text to determine — the summons identifies Amazon.com Services LLC as plaintiff and Perplexity AI, Inc. as defendant but does not disclose the specific legal claims, statutes, or theories of liability asserted in the underlying complaint.
Why It Matters: Insufficient text to determine — the summons alone reveals only the identity of the parties and the forum, not the legal theories that would bear on platform liability, First Amendment doctrine, or AI regulation.
View on CourtListener →Computer & Communications Industry Association v. Paxton
Issue: Whether Texas SB 2420, which imposes age-verification, parental consent, and age-rating disclosure requirements on app stores, regulates protected speech subject to First Amendment heightened scrutiny, or instead regulates commercial conduct falling within the state's police power and governed by the *Zauderer* commercial-disclosure standard.
Why It Matters: This amici brief advances a content-neutrality framework specifically designed to distinguish SB 2420 from statutes invalidated in *NetChoice v. Griffin* and *Brown v. Entertainment Merchants Association*, potentially offering courts a doctrinal path to uphold app-store child-safety regulations by classifying gatekeeping and contracting functions as commercial conduct rather than protected editorial discretion — a distinction that, if accepted, could broadly affect the constitutional viability of similar legislation in other states.
View on CourtListener →D.A v. Roblox Corporation
Issue: Insufficient text to determine.
Why It Matters: Insufficient text to determine. --- Note: The document transmitted consists solely of 109 repeated docket-page citations with no substantive content rendered. To generate an accurate summary, please resubmit with the actual text of the complaint.*
View on CourtListener →Doe v. Roblox Corporation
Issue: Whether Roblox Corporation and Discord, Inc. are liable under product liability (design defect), negligence, and fraud theories for injuries a minor suffered from sexual exploitation facilitated through their platforms, and whether those claims are barred by §230(c)(1) of the Communications Decency Act.
Why It Matters: This complaint presents a direct test of whether product liability and fraud theories premised on platform design choices — rather than on Defendants' role as publishers of third-party content — can survive anticipated §230 preemption arguments, potentially advancing the circuit split over whether design-defect claims targeting a platform's own architectural decisions fall outside §230's immunity.
View on CourtListener →Defense Distributed v. Elik
Issue: In *Defense Distributed v. Elik*, Defense Distributed argues that a court may take judicial notice of prior federal court orders from related litigation—including orders in *VanDerStok* and proceedings against YouTube and Kickstarter—not merely as proof those proceedings occurred, but as independent corroboration that its lost-sales harm is credible and non-speculative. The non-obvious difficulty is that FRE 201 permits judicial notice of adjudicative facts not subject to reasonable dispute, and Defense Distributed is pressing that standard to cover something courts have traditionally refused to notice: the persuasive force of factual findings and credibility assessments made by other judges in factually distinct cases.
Why It Matters: Defense Distributed is attempting to protect its damages case and its experts from exclusion before trial by aggregating judicial acknowledgments of financial harm from factually adjacent but legally distinct proceedings—a strategically creative but doctrinally contested move. The core legal problem is that courts routinely take notice of the existence and contents of prior proceedings but not of the truth of facts found or credibility judgments made in them, a distinction that could leave Defense Distributed's experts without the cross-forum corroboration the motion is designed to provide. If the motion fails on those grounds, the company's damages case may rest entirely on its own internal representations, making its experts more vulnerable to exclusion under *Daubert*. The motion also surfaces a broader question that circuit courts have not squarely resolved: whether a commercial tort plaintiff can build a Daubert-resistant damages record by aggregating judicial acknowledgments of harm from multiple related but legally distinct proceedings.
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