How the Center for Investigative Reporting is handling the lawsuit against OpenAI as one of the few nonprofits with the resources to take on a yearslong suit
This story isn't just about copyright. It's about the imbalance between tech giants and the public interest — and how journalism is being mined, not supported. — 🔗 www.niemanlab.org/2025/06/what... … Andrew Deck / @andrewdeck : “It is critical to not let journalism be chewed up and spit out by technologies yet again.” — A year into its OpenAI litigation, CIR is one of the only journalism nonprofits to take an AI company to court. I asked CEO @monikab.bsky.social and the CIR legal team why. — www.niemanlab.org/2025/06/what...
Context & Ripple Effects
CIR’s case sits within a widening publisher challenge to AI training practices. Earlier coverage framed these suits as a possible test of copyright and fair use—or as leverage for licensing arrangements—a debate over whether litigation will reset AI copyright rules or drive deals.
The distinctive issue here is institutional capacity: CIR is pursuing a prolonged case as a nonprofit, while OpenAI and Microsoft have already argued in court that scraping news for LLM training should not sustain publishers’ claims in their defense of news-scraping claims.
First-order effects
- CIR must devote legal and organizational resources to sustaining a multiyear challenge, making its capacity—not just the merits—a central factor in whether the case proceeds.
- OpenAI faces another newsroom-originated claim challenging how journalistic material is used in AI development, alongside its stated fair-use and opt-out defense OpenAI’s earlier fair-use response.
Second-order effects
- Other nonprofit and smaller publishers gain a concrete example of the resource hurdle involved in litigating against major AI companies, potentially increasing the appeal of collective action or negotiated licensing.
- The case adds pressure to clarify the boundary between training access, opt-outs, and compensation, because individual publishers may be unable to rely on litigation as a practical remedy.
Third-order effects
- If only unusually well-resourced nonprofits and large publishers can litigate, court-led rulemaking may reflect a narrow set of claimants even though AI training draws on a much broader publishing ecosystem.
- The broader market may increasingly resolve content disputes through licensing or access controls rather than merits rulings, unless litigation produces clearer copyright guidance.
The trend: AI-content disputes are becoming as much a contest over publishers’ legal staying power as over the legal status of model training data.