A federal judge in the Northern District of California granted preliminary approval on September 25 to a $1.5 billion settlement between Anthropic and a class of authors who alleged that the artificial intelligence company used their copyrighted works to train its chatbot Claude without their consent. The settlement is the largest copyright settlement of all time, covering 482,460 works and paying authors slightly more than $3,000 per work infringed.
As AI becomes more embedded in everyday life and business operations, companies are facing a growing regulatory maze at the intersection of state privacy laws and emerging AI standards. This article explores the privacy laws that impact the use of AI and automated decision making and offers a practical guide for business leaders that aligns AI innovation with privacy expectations.
Stop running pilot after pilot with different tools but failing to move beyond testing. Start with business outcomes. Redesign processes and guardrails. Rethink pricing models. And then, with clarity of purpose, choose the tools that enable the future of legal work.
As AI becomes more sophisticated at detecting fakes, it is not just changing how brands protect themselves — it has the potential to change the legal framework for determining when platforms themselves might be held responsible for the counterfeits sold on their sites.
How are copyright holders to prove their works were used to train AI models if the details about the vast data sets used for such training are kept secret? That’s a dilemma that surfaced in late August when a federal judge dismissed a claim of direct infringement raised by a group of authors.
As AI becomes more sophisticated at detecting fakes, it is not just changing how brands protect themselves — it has the potential to change the legal framework for determining when platforms themselves might be held responsible for the counterfeits sold on their sites.
Stop running pilot after pilot with different tools but failing to move beyond testing. Start with business outcomes. Redesign processes and guardrails. Rethink pricing models. And then, with clarity of purpose, choose the tools that enable the future of legal work.
How are copyright holders to prove their works were used to train AI models if the details about the vast data sets used for such training are kept secret? That dilemma surfaced when a California federal judge recently dismissed a claim of direct infringement raised by a group of authors.
Artificial Intelligence (AI) is permeating every phase of construction — redefining how buildings and projects are designed, managed, and maintained. This article offers practical analysis, sample clauses, and insights into how AI-specific contract terms can mitigate risk and facilitate responsible innovation.
Two judges in the Northern District of California recently issued groundbreaking summary judgment rulings regarding whether an artificial intelligence company’s scraping and ingestion of copyrighted works to train its LLMs qualified as fair use. Both decisions carry potentially seismic importance for AI companies and intellectual property litigators.
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