Answer first: As AI systems increasingly train on vast copyrighted works without authorization, creators and legal scholars call for a new 'learnright' intellectual property right. This proposed law would require AI companies to license content for training, ensuring fair compensation and preserving incentives for human creativity.…
Litigation context for IP teams
In 2026, the creative community has united in protest against AI companies using copyrighted works without permission to train their models. Artists, writers, and actors have voiced concerns that AI training practices undermine human creativity and threaten livelihoods. The Creators Coalition on AI emphasized that technology should enhance rather than diminish creative expression, while the Human Artistry Campaign launched a “Stealing Isn’t Innovation” initiative. Nearly 10,000 writers contributed to the publication of Don’t Steal This Book, a textless volume listing authors’ names to symbolize the potential erasure of original content if AI training remains unchecked.
By March 2026, there were 87 copyright lawsuits filed against AI companies in the United States, reflecting escalating legal tensions. However, litigation and protests alone are insufficient to address the fundamental challenges posed by AI’s unprecedented capacity to ingest and replicate creative works at scale.
Key takeaways for learnright law AI copyright
- Confirm how the development affects litigation ownership, enforcement, licensing, or portfolio records.
- Separate confirmed facts from legal interpretation before advising business teams.
- Map deadlines, affected assets, contracts, and evidence files to the responsible internal owner.
- Use the issue as a prompt for monitoring, filing strategy, dispute preparation, or member education.
Practical analysis
Traditional copyright law distinguishes between copying and learning: unauthorized copying is prohibited, but learning from works is permitted. This distinction was based on human cognitive limits, where no individual could instantly memorize or reproduce thousands of works. AI systems disrupt this paradigm by processing millions of articles, books, and images rapidly, then generating content that competes directly with original creations. This dynamic threatens the economic incentives that sustain creative industries.
To address this, a new intellectual property right termed “learnright” has been proposed. This would add a seventh exclusive right to copyright law, requiring AI companies to obtain licenses before using copyrighted content for training. Licensing fees would compensate creators through market-driven mechanisms.
The learnright framework aims to benefit both creators and AI developers. While licensing may increase costs for AI companies initially, failure to compensate creators risks eroding the incentives essential for ongoing artistic production. The proposal envisions licensing systems akin to existing models such as ASCAP, which collects and distributes royalties for music performance.
Under learnright, clearinghouses or specialized brokers could manage licensing negotiations across different creative sectors, including news, fiction, and visual art. Examples of emerging entities in this space include ProRata.AI and Tollbit. Creators would select brokers to represent their interests, and pricing would reflect supply and demand dynamics. Large AI firms like Google and OpenAI would pay proportionally higher fees, while smaller startups would incur lower costs, promoting equitable distribution of AI-generated revenues.
Enforcement mechanisms would include mandatory audits of AI training datasets focused on input sources, whistleblower reward programs to incentivize internal compliance, and meaningful penalties exceeding mere licensing fees to deter unauthorized use.
Support for learnright is growing among plaintiffs in ongoing lawsuits and advocacy groups such as the Creators Coalition Against AI. Small-scale artists, authors, and all stakeholders invested in preserving original creative works have a vested interest in this legislative approach.
Importantly, learnright offers a market-based solution that avoids government price-setting or heavy-handed regulation. Creators would opt in to protect their works, preventing system overload from unclaimed content. This opt-in design fosters a balanced framework acceptable to both content owners and AI developers.
Some legal scholars express skepticism about collective licensing’s complexity, but precedent exists for effective compensation schemes in other technological contexts. Additionally, the legal doctrine of unjust enrichment supports compensation claims, as AI companies profit from copyrighted works without remunerating creators.
As AI regulation gains political traction, the learnright proposal represents a pragmatic path forward to reconcile AI innovation with the protection of creative rights.
Related IIPLA reading
Experts Propose 'Learnright' Law to Address AI Training and Copyright Challenges As AI systems increasingly train on vast copyrighted works without authorization, creators and legal scholars call for a new 'learnright' intellectual property right. This proposed law would require AI companies to lice... Read the full IIPLA blog post: https://iipla.org/blog/experts-propose-learnright-law-to-address-ai-training-and-copyright-challenges