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A new lawsuit against Perplexity AI claims responses generated by the artificial intelligence platform violate the trademarks of Encyclopaedia Britannica and Merriam-Webster by attributing false information to their widely esteemed brands. The complaint alleges Perplexity’s generative AI “answer engine” violates the plaintiffs’ copyrights and also cites them as sources of false or incomplete information.
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The continued, rapid advancement of artificial intelligence technologies comes with increasing risks for businesses, demanding that they navigate such issues more carefully than ever. Considering recent privacy class action trends detailed in this article, companies that utilize AI in their business operations should immediately review and modify their compliance programs as necessary to mitigate legal risk and liability exposure.
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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.
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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.
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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.
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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.
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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.
Features
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.
Features
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.
Features
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.
