Photo courtesy of Mayer Brown LLP
Trade secret litigation can be complex and challenging, especially when it comes to securing appropriate damages. To maximize your chances of obtaining a favorable outcome, consider these five essential tips:
by Avi Gesser, Jim Pastore, Matt Kelly, Gabriel Kohan, and Jackie Dorward
From left to right: Avi Gesser, Jim Pastore, Matt Kelly, Gabriel Kohan, and Jackie Dorward (photos courtesy of Debevoise & Plimpton LLP)
As the first quarter of 2025 draws to a close and we look ahead to the spring, important changes to the Federal Rules of Evidence (“FRE”) regarding the use of AI in the courtroom are on the horizon. Specifically, the Federal Judicial Conference’s Advisory Committee on Evidence Rules (the “Committee”) is expected to vote on at least one AI-specific proposal at its next meeting on May 2, 2025. The Committee has been grappling with how to handle evidence that is a product of machine learning, which would be subject to Rule 702 if propounded by a human expert.
by Jamillia Ferris, Vinita Kailasanath, Christine Lyon, Jan Rybnicek, and David Sewell
Left to right: Jamillia Ferris, Vinita Kailasanath, Christine Lyon, Jan Rybnicek, and David Sewell (photos courtesy of Freshfields Bruckhaus Deringer LLP)
Freshfields recently hosted a U.S. Fintech Hot Topics Webinar to highlight on-the-ground insights from our Antitrust and Competition, Data Privacy and Security, Financial Services Regulatory, and Transactional teams. The fintech sector has recently seen a return to explosive growth and is expected to continue growing rapidly notwithstanding regulatory and economic headwinds. Our top takeaways from the panel discussion are below, and the full recording is available here.
by Angela Dunning, Arminda Bepko, and Jessica Graham
From left to right: Angela Dunning, Arminda Bepko & Jessica Graham (photos courtesy of Cleary Gottlieb Steen & Hamilton LLP)
This week saw yet another California federal court dismiss copyright and related claims arising out of the training and output of a generative AI model in Tremblay v. OpenAI, Inc.,[1] a putative class action filed on behalf of a group of authors alleging that OpenAI infringed their copyrighted literary works by using them to train ChatGPT.[2] OpenAI moved to dismiss all claims against it, save the claim for direct copyright infringement, and the court largely sided with OpenAI.
by Simon Fondrie-Teitler and Amritha Jayanti
Federal Trade Commission
This blog is part of a series authored by the FTC’s Office of Technology focused on emerging technologies and consumer and market risks, with a look across the layers of technology—from data and infrastructure to applications and design of digital systems.
Over the last several years, artificial intelligence (AI)—a term which can refer to a broad variety of technologies, as a previous FTC blog notes—has attracted an enormous amount of market and media attention. That’s in part because the potential of AI is exciting: there are opportunities for public progress by enhancing human capacity to integrate, analyze, and leverage information. But it’s also, perhaps in larger part, because the introduction of AI presents new layers of uncertainty and risk. The technology is altering the market landscape, with companies moving to provide and leverage essential inputs of AI systems, such as data and hardware – opening a window of opportunity for companies to potentially seize outsized power in this technology domain. AI is also fundamentally shifting the way we operate; it’s lurking behind the scenes (or, in some cases, operating right in our faces) and changing the mechanics by which we go about our daily lives. That can be unsettling, especially when the harms brought about by that change are tangible and felt by everyday consumers.
Photo courtesy of author
Let’s say someone walks into an old-fashioned record store looking for the Bright Eyes song “False Advertising.” Upon finding and buying the album, she’d have little reason to fear that store employees might sneak into her house later and take it back from her. She’d also have no cause to think that the album was counterfeit and not by the band at all. Now let’s say instead that the same song inspires an artist to create a mural depicting the FTC’s greatest false ad cases, and the mural gets displayed in a local gallery. The artist might be surprised if the gallery later shuts its doors and refuses to return the mural . . . or if some other company secretly reuses bits of it to make something else.
When people buy or make digital products, though, it’s not always clear what they really own or control. Such clarity may often depend on intellectual property rights, which are generally beyond the FTC’s consumer protection jurisdiction. But we take note – and can take action – if companies aren’t upfront about what consumers are buying, who made it, how it was made, or what rights people have in their own creations.
by Frank J. Azzopardi, Matthew J. Bacal, David R. Bauer, Pritesh P. Shah, Samantha Lefland, Christopher C. Woller, and Joshua Shirley
Top left to right: Frank J. Azzopardi, Matthew J. Bacal, David R. Bauer, and Pritesh P. Shah.
Bottom left to right: Samantha Lefland, Christopher C. Woller, and Joshua Shirley.
(Photos courtesy of Davis Polk & Wardwell LLP)
The recent rise of consumer and market interest in generative artificial intelligence (GAI) tools has spurred growing interest in GAI assets from strategic acquirers and private equity investors. This article provides a brief introduction to GAI tools and their current uses, as well as an overview of the due diligence, transactional and other commercial considerations for investors and acquirers engaging in related investment and M&A activity.
by Avi Gesser, Matt Kelly, Samuel J. Allaman, Michelle H. Bao, Anna R. Gressel, Michael Pizzi, Lex Gaillard, and Cameron Sharp
Top left to right: Avi Gesser, Matt Kelly, Samuel J. Allaman, and Michelle H. Bao.
Bottom left to right: Anna R. Gressel, Michael Pizzi, Lex Gaillard, and Cameron Sharp.
(Photos courtesy of Debevoise & Plimpton LLP)
Over the past three years, we have observed many companies in a wide range of sectors adopt Artificial Intelligence (“AI”) applications for a host of promising use cases. In some instances, however, those efforts have ended up being less valuable than anticipated—and in a few cases, were abandoned altogether—because certain risks associated with adopting AI were not properly considered or addressed before or during implementation. These risks include issues related to cybersecurity, privacy, contracting, intellectual property, data quality, business continuity, disclosure, and fairness.
In this Debevoise Data Blog post, we examine how the manifestation of these risks can lead to AI adoption “failure” and identify ways companies can mitigate these risks to achieve their goals when implementing AI applications.
by Greg D. Andres, Uzo Asonye, Martine M. Beamon, Robert A. Cohen, Daniel S. Kahn, Tatiana R. Martins, Fiona R. Moran, Paul J. Nathanson, and Patrick S. Sinclair
Top left to right: Greg D. Andres, Uzo Asonye, Martine M. Beamon, Robert A. Cohen, and Daniel S. Kahn.
Bottom left to right: Tatiana R. Martins, Fiona R. Moran, Paul J. Nathanson, and Patrick S. Sinclair.
(Photos courtesy of Davis Polk & Wardwell LLP)
In recent speeches, Deputy Attorney General Lisa Monaco and Principal Associate Deputy Attorney General Marshall Miller laid out how the DOJ uses active corporate criminal enforcement and interdepartmental cooperation to preserve national security and the rule of law, and previewed forthcoming compliance guidance on M&A deals.
by Megan Bannigan, Avi Gesser, Henry Lebowitz, Anna Gressel, Michael R. Roberts, Melissa Muse, Benjamin Leb, Jarrett Lewis, Lex Gaillard, and ChatGPT
Top row left to right: Megan Bannigan, Avi Gesser, Henry Lebowitz, and Anna Gressel
Bottom row left to right: Michael R. Roberts, Melissa Muse, Benjamin Leb, and Jarrett Lewis
ChatGPT is an AI language model developed by OpenAI that was released to the public in November 2022 and already has millions of users. While most people were initially using the publicly available version of ChatGPT for personal tasks (e.g., generating recipes, poems, workout routines, etc.) many have started to use it for work-related projects. In this Debevoise Data Blog post, we discuss how people are using ChatGPT at their jobs, what are the associated risks, and what policies companies should consider implementing to reduce those risks.