The Woulard case signals that AI’s “wild west” phase may be nearing its end. Independent artists have drawn a clear line: no matter how powerful the technology, it cannot function above the law.

Woulard v. Uncharted Labs – A Critical Turning Point in the AI Copyright Wars

by ChatGPT-4o

I. Introduction

The lawsuit Woulard et al. v. Uncharted Labs, Inc. marks a significant escalation in the legal challenges facing generative AI companies. Filed on October 15, 2025, in the U.S. District Court for the Northern District of Illinois, the case is brought by a group of independent artists, led by David Woulard and Attack the Sound LLC, against Uncharted Labs (d/b/a Udio), a prominent AI music-generation platform launched by former Google DeepMind researchers.

What distinguishes this case is not just its breadth—with 14 counts ranging from direct copyright infringement to violations of biometric privacy laws—but its sharp focus on the specific harms suffered by independent artists, a community often overshadowed by high-profile lawsuits from major record labels. The plaintiffs allege that Udio systematically ingested their copyrighted recordings and lyrics to train its commercial AI models without consent or compensation, all while undermining the economic value of their work.

II. Grievances

The plaintiffs bring forth a comprehensive set of allegations against Udio:

1. Unauthorized Copying of Copyrighted Works: Udio allegedly downloaded, ingested, and retained vast amounts of copyrighted recordings—including the plaintiffs’ works—without licenses, claiming fair use as a defense.

2. Massive Dataset Built via Stream-Ripping: Plaintiffs assert Udio used illegal stream-ripping methods (notably bypassing YouTube’s rolling cipher encryption) to obtain music from platforms where creators had uploaded their content with DRM protections in place.

3. Lyrics Scraping and Tokenization: Udio reportedly scraped lyrics from sites like Genius, AZLyrics, and Lyrics.com using Common Crawl and processed them for model training without securing required display or reproduction licenses.

4. Removal of Copyright Management Information (CMI): Udio systematically stripped metadata (e.g., song titles, artist names, licensing info) from files during its ingestion process—a potential violation of the DMCA’s CMI provisions under § 1202(b).

5. Biometric Privacy Violations: Udio is alleged to have captured and commercialized voiceprints and vocal identifiers without consent, in breach of the Illinois Biometric Information Privacy Act (BIPA).

6. Violation of Publicity Rights: By using distinctive vocal signatures and producing outputs mimicking real artists, Udio is accused of infringing the Illinois Right of Publicity Act (IRPA).

7. Contributory and Vicarious Infringement: Udio allegedly encouraged users to create AI tracks mimicking known styles, benefitting financially while ignoring the rights of original artists.

8. Market Harm and Unjust Enrichment: Plaintiffs argue that Udio’s outputs flood sync, streaming, and production music markets, leading to direct substitution and devaluation of human-created music.

III. Quality of Evidence

The complaint is meticulously detailed and legally sophisticated, notably for a filing on behalf of independent artists. Its strength lies in:

• Specificity of Copyrighted Works: The plaintiffs provide registered work details (e.g., titles, registration numbers, distribution platforms).

• Technical Breakdown of Udio’s Pipeline: The complaint describes Udio’s ingestion, training, and output mechanisms, including how files are anonymized, segmented, and processed—demonstrating not just harm but intention and systemic practice.

• Supporting Admissions: Udio’s own promotional language, public statements, and investor comments are cited to show that they knew the model depended on massive copyrighted data ingestion.

• Market Impact: The plaintiffs explain substitution and dilution across numerous well-defined economic use cases—streaming, commissions, lyric licensing, sync, and derivative works.

The evidence presented strongly links Udio’s business model to systematic infringement and economic harm to a specific class of creators. While it lacks forensic output-to-training data matching (e.g., “this output resembles this track”), it argues convincingly that the offense occurred at the point of reproduction, not generation.

IV. Potential Outcomes

Several scenarios are possible:

1. Motion to Dismiss Rejected: Given the complaint’s depth and plausibility, it is unlikely to be dismissed outright. The court may allow discovery to assess the contents of Udio’s training data and pipelines.

2. Settlement with Terms: Like recent Anthropic and OpenAI cases, this may result in a confidential settlement involving payment, deletion of infringing data, and/or licensing terms—especially if discovery uncovers damning internal documentation.

3. Landmark Judgment: If this proceeds to trial, and plaintiffs prevail, it could set a precedent regarding whether ingestion of copyrighted sound recordings for training AI models without consent constitutes fair use.

4. Parallel Enforcement Actions: The inclusion of BIPA and IRPA violations may invite attention from the Illinois Attorney General, especially given the local plaintiffs and alleged biometric harms.

5. Impacts on Other Cases: As the 54th U.S. copyright suit against AI companies, this case may influence litigation tactics and judicial interpretations across sectors (literature, visual arts, etc.).

V. Could Udio Have Prevented This?

Absolutely. Udio’s risks were foreseeable, and several mitigations could have been taken:

1. Obtain Licenses or Exclude Infringing Data: Udio could have negotiated licenses or explicitly excluded known copyrighted and DRM-protected content (e.g., YouTube-hosted songs with copyright tags).

2. Use Opt-In Datasets: Like Stability AI’s recent pivot, Udio could have sourced content from openly licensed, creator-consented databases—reducing liability while preserving innovation.

3. Maintain Attribution and Metadata: Retaining CMI would have enabled downstream attribution and licensing, helping avoid DMCA violations.

4. Implement Data Deletion and Audit Protocols: Rather than hoarding persistent corpora, Udio should have implemented deletion timelines, usage logs, and internal controls.

5. Transparency: Disclosing training data sources and enabling opt-out mechanisms would’ve demonstrated good faith and mitigated reputational harm.

6. Avoid Voiceprint and Likeness Replication Without Consent: Given the known legal sensitivities around biometric data and artist identity, these features should have required explicit opt-in or contractual terms.

VI. Broader Lessons for AI Makers

This case underlines a critical truth: innovation cannot be built on disregard for rights. AI developers must:

• Build licensing into their core model pipeline;

• Respect IP, privacy, and likeness laws from design to deployment;

• Engage creators as stakeholders, not mere data points;

• Anticipate legal, ethical, and market risks before scaling globally.

VII. Conclusion: Toward Accountability in the AI Era

The Woulard case signals that AI’s “wild west” phase may be nearing its end. Independent artists have drawn a clear line: no matter how powerful the technology, it cannot function above the law. This lawsuit forces the courts to confront a fundamental question: Can AI companies extract and monetize the creative work of others without permission or compensation under the guise of innovation?

Regardless of its final outcome, the case provides a blueprint for future plaintiffs and regulators. It demands that AI firms adopt ethical licensing frameworks, data accountability, and respect for creator rights—not as an afterthought, but as core infrastructure.

If AI is to coexist with the arts, it must learn to collaborate rather than cannibalize.