Every decision to onboard a client, partner, lateral hire, contractor, consultant or expert witness carries risk. Yet despite the increasing complexity of that risk, many firms continue to rely on onboarding practices that have not kept pace with the digital world in which their clients and people operate. The result is a widening gap between how risk actually manifests today and how it is assessed at the point of onboarding.
Understanding the “not written by people” feature of AI software is the best lens for viewing AI transactions. The fact that an AI is not a legal entity, prompts the proper legal analysis of AI transactions.
A great debate seems to be rearing its head–is it better to conduct document review with traditional machine learning or with generative AI? This article examines traditional machine learning and generative AI in the context of review for production in litigation matters. While each party seeks to improve efficiency and defensibility, they differ meaningfully in workflow, transparency, human involvement, and overall impact on legal practice.
As insurance retreated from AI exposure, contracts began absorbing functions that insurance once performed. Indemnities compressed. In effect, contracts began underwriting elements of AI risk. This shift has significant consequences for lawyers drafting, negotiating and advising on AI-related agreements.
You would not tolerate an associate with uniform confidence for very long. It makes them less useful, not more, because you cannot triage your review. Every assertion demands the same level of scrutiny. Yet this is precisely how every major large language model operates today. And the artificial intelligence industry’s proposed solution — spending billions to marginally reduce hallucinations — fundamentally misunderstands what lawyers actually need.
A series of recent, startling public comments from technology industry leaders should alert governing boards to the potential enterprise risks of artificial intelligence to their own organization. These public comments address two increasingly worrisome aspects of AI: first, the potential for AI to quickly evolve into an autonomous and unpredictable “rogue” technology; and second, the risk of significant economic and social disruption from mass AI-prompted worker displacement.
The modern attorney–client relationship contains an implicit clause: one that demands trust, relationship intelligence and intentional engagement. Neglect it, and even exceptional legal work may not be enough to retain the “forever client.”
Matthew McConaughey secured eight federal trademark registrations covering his voice and iconic catchphrases in a novel legal strategy aimed at combating AI’s unauthorized use of his voice and likeness. The move signals an important evolution in the power dynamics between talent/brands and the companies providing generative AI tools.
A Chapter 7 trustee may pursue any claims or causes of action, including avoidance actions to challenge post-petition transfers of property of the estate, that are property of a debtor’s estate. In a recent decision in the case of In re Genger, the U.S. Bankruptcy Court for the Southern District of New York addressed the distinction between direct claims versus derivative claims in the context of a post-petition release.
A recent decision from the US District Court for the Southern District of New York has generated outsized commentary suggesting that the use of generative AI tools may jeopardize attorney-client privilege. A closer reading shows something far less dramatic.
