As generative AI transforms how content is created, courts and policymakers are struggling to define authorship, ownership, and infringement. This piece explores the legal, regulatory, and conceptual challenges posed by AI-generated works and the future of copyright in an era of machine-assisted creativity.
Mexico’s sweeping June 30th reforms to its Federal Economic Competition Law have ushered in a new era of antitrust enforcement, creating the powerful Comisión Nacional Antimonopolio (CNA) to challenge Big Tech’s dominance through stricter merger reviews, expanded data access powers, and significantly higher financial penalties.
Recent U.S. court wins for Meta and Anthropic strengthen fair use defenses in AI training, but deepen global copyright tensions. While enabling U.S. firms to accelerate innovation, the rulings raise legal, ethical, and diplomatic risks abroad—fueling debates over data rights, licensing models, and the future of generative AI regulation.
Despite strong data protection laws, UK courts have stymied efforts to enforce privacy rights through class actions, creating a system where rights exist without remedies—leaving individuals unprotected, businesses relieved but exposed, and the UK increasingly isolated from global digital accountability trends.
AI is transforming negotiation from human interaction to algorithmic battle. A professor argues that without regulation—such as public AI tools and data access mandates—automated deal making could increase corporate dominance, erode fairness, and shift the balance from human-to-human persuasion to algorithms.
The landscape for GenAI and copyright is rapidly evolving—and remains fraught with uncertainty for anyone using machine-generated content. While GenAI tools offer key advantages they introduce two core legal risks: lack of copyright protection for AI-generated outputs, and potential infringement tied to training data.