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Most agree that internet deepfake (deep learning + fake) content is widespread and may be used to manipulate the public, attack personal rights, infringe intellectual property and cause personal data difficulties. However, little agreement exists as to who is legally liable for internet AI deepfake content.

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This article seeks to provide clarity and context on the different types of AI available in the legal industry today and how the new GPT technology fits into that landscape. More importantly, it will illustrate the potential impact of the next generation of AI on litigation and legal practice as a whole.

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Artificial Intelligence will revolutionize law firm marketing forever. Law firms are now (or should be) leveraging the potential of AI in order to enhance their marketing efforts. By harnessing the capabilities of AI, law firms are able to expand their marketing strategies, boost efficiency, accuracy, and overall client engagement.

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Part Two of a Two-Part Article In Part One, last month, the authors addressed the industries most affected by AI, and began the discussion on U.S. federal and state regulations to expect in 2023. Part Two continues the discussion on potential federal AI regulation and what companies can do to prepare.

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Part One of a Two-Part Article Despite the steady growth of global AI adoption, there is no comprehensive federal legislation on AI in the United States. Instead, the U.S. has a patchwork of various current and proposed AI regulatory frameworks. It is critical for organizations looking to harness this novel technology to understand these frameworks and to prepare to operate in compliance with them.

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IP experts weigh in on a case involving AI-created images based on an original work. The outcome of the case may have a significant impact on AI development and generative art.

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Having an AI policy that outlines acceptable use, and documenting assessments that establish that AI systems are used in a manner consistent with the policy and that the benefits outweigh potential harms, can go a long way in managing legal and reputational risk.

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AI language models are trained on massive amounts of data to function and improve. The more data the model is trained on, the better it gets at detecting patterns, anticipating what comes next, and producing realistic text. Right now, however, there are few controls in place to stop these models from scraping personal and private information from people and business.