# Big AI's Content Dilemma: Exploiting Creators While Avoiding Payment AI giants face legal battles over using copyrighted material without compensation. - **Source:** [www.theregister.com - Articles](https://brifing.si/source/2c34ea50-d341-4a10-925d-12c012a9ad10) - **Published:** 2026-09-27 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/8b00fea5-1a6a-4413-a042-32f907d98128 ## AI's content dependency Large language models require massive amounts of copyrighted material - books, news articles, code, and creative works - for training. Tech companies systematically scrape this content while avoiding payment structures. Microsoft's internal documents acknowledge this practice destroys the content supply chain it depends on, creating what they term a 'doom loop' where AI eliminates the creators it needs. ## NYT vs OpenAI case details Unsealed court documents reveal Microsoft executives describing their content scraping as potentially 'the largest theft of labor in human history.' The New York Times lawsuit highlights how AI companies ingest paywalled content without detection or removal efforts. OpenAI's corporate representative admitted no systems exist to filter paywalled material from training datasets, with executives celebrating workarounds. ## Fair use defense strategy AI companies argue their content use constitutes fair use, claiming it advances public knowledge rather than creating market substitutes. However, internal documents contradict this, showing awareness of content's commercial value. The legal strategy follows a 'take now, argue later' approach, delaying accountability while building profitable products that undermine content creators' revenue streams. ## Code copyright complications Recent court rulings like Doe v. GitHub created narrow interpretations favoring AI companies, but left major copyright questions unresolved. The decision didn't establish that code training is always fair use or that generated code can't infringe copyright. Open source licenses remain legally binding, yet AI tools routinely ignore attribution requirements, creating legal risks downstream for developers using AI-generated code. ## Content industry impact AI's uncompensated content use already affects journalism, fiction writing, and creative fields. By replacing human-generated content while depending on it for training, AI creates a paradox where it eliminates the very industries it needs. Internal documents show companies understand this dynamic but prioritize short-term growth over sustainable content ecosystems, risking model collapse from deteriorating training data quality. ## Legal shift in open source Attorneys note a concerning trend where open source licenses are increasingly litigated as contracts rather than copyright agreements. This approach bypasses fundamental IP questions about ownership and copying. For AI companies, it creates a loophole to avoid license obligations while benefiting from community work. The strategy could fundamentally alter open source's nature if courts accept this interpretation. ## Antitrust implications A new federal lawsuit alleges AI giants coordinated to slow advanced AI development under the guise of safety concerns. While executives publicly call for development pacing, critics see anti-competitive behavior restricting smaller players. However, antitrust law requires proving actual harm, making the case difficult despite suspicious timing of coordinated statements about AI risks from major companies. ## User behavior challenges AI companies exploit users' tendency to accept outputs without verification. OpenAI engineers admit users rarely check sources regardless of prominence. This enables companies to obscure content origins while avoiding attribution. In coding, developers typically don't verify licenses for AI-suggested snippets, creating widespread compliance risks as AI obscures code provenance and licensing terms. ## Systemic content exploitation The pattern shows AI companies systematically bypassing copyright, open source, and competition rules. Creators hear fair use arguments, developers hear 'new code' claims, and competitors hear safety justifications - all benefiting incumbents. Without intervention, this could create a feudal system where AI trillionaires control content markets while original creators lose livelihoods and bargaining power. ## Sources covering this story - https://www.theregister.com/columnists/2026/09/27/big-ais-content-problem-take-the-work-keep-the-money/5299007 — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._