XLSCOUT is an SOC2 Type II compliant integrated innovation & patent monetization platform at the forefront of the global innovation and IP industry, harnessing the potential of advanced Al technologies like Large Language Models (LLMs) and Generative Al for idea validation, optimizing ideation, creating high-value patents, and monetizing innovation.
MarqVision is an AI-powered platform that helps brands protect themselves from online counterfeits, unauthorized sales, and other forms of brand infringement across various online platforms.
ScaleIP, formerly known as LicenseLead, is a company that uses AI and IP transaction data to help businesses identify and connect with potential partners for licensing, selling, or collaborating on patents. It aims to streamline the process of finding suitable businesses and individuals for IP-related deals. ScaleIP helps IP teams save time, generate revenue, and make informed patent decisions by identifying and engaging with the most likely IP partners.
Black Hills AI provides automated Intellectual Property legal support services from its offices in the US. Its legal support services include intellectual property docketing, paralegal, proofreading, analytics and annuity management services.
Questel, a company specializing in intellectual property (IP) management and innovation. Questel provides software and services to help businesses manage their IP assets, including patents, trademarks, designs, and copyrights.
Tradespace works with leading innovators to generate, manage, and commercialize their IP portfolios. We are the only platform supporting organizations across the entire innovation cycle, including disclosure collection & evaluation, IP management, analytics and scouting, and commercialization.
This Perspective by Ben Chester Cheong (Singapore University of Social Sciences & Cambridge) offers a comprehensive legal–ethical review of transparency and accountability challenges in AI systems governing human wellbeing . It structures the discussion into four pillars—technical explainability methods, regulatory frameworks, ethical safeguards, and multi‑stakeholder collaboration—highlighting how each area plays a vital role in ensuring trust and societal resilience. Legal professionals will appreciate its actionable framework that bridges tech, ethics, and governance, making it a timely resource amid emerging regulations like GDPR “right to explanation” and EU AI Act mandates. By offering strategic clarity and policy cohesion, this article equips lawyers, compliance leaders, and policymakers with tools to embed transparency and accountability into AI systems that shape lives—making it a must‑read for anyone advising on responsible AI deployment.
This essay by Margot E. Kaminski and Meg Leta Jones explores how current legal frameworks actively construct AI-generated speech, rather than being passively disrupted by it. It introduces the “legal construction of technology” method—analyzing how laws like the First Amendment, content moderation, risk regulation, and consumer protection actively interpret and shape AI speech. This analysis matters to legal professionals because it reveals that existing institutions and norms already provide structured pathways for meaningful oversight, shifting the conversation from reactive problem-solving to proactive values-based policy design. By demonstrating that law and AI co-evolve through these intentional constructions, this piece empowers lawyers and policymakers to craft more effective, principled governance—prompting deeper engagement with the field.
This article by Graham H. Ryan analyzes how generative AI challenges the legal immunity conferred by Section 230 of the Communications Decency Act—and why that protection may crumble under new judicial scrutiny. Ryan argues that generative AI systems “create or develop content” and thus likely fall outside Section 230’s existing scope, exposing providers to increased liability for design decisions and algorithmic contributions. It matters for legal professionals because emerging case law may redefine liability standards—from co-authoring content to design-based claims—signaling a pivotal shift in AI governance and internet law that practitioners need to monitor closely. By framing generative AI as a catalyst for reevaluating the legal foundations of internet speech, the article urges lawyers to proactively reassess risk strategies and regulatory compliance in this evolving landscape.
This insightful analysis explores how China’s August 15, 2023 regulations on generative AI reflect a strategic choice to slow AI progress for social and political control. It reveals a key finding that Beijing’s cautious regulatory approach contrasts sharply with the innovation-first strategies of the U.S. and EU, granting other jurisdictions essential breathing room to develop responsible AI policies. Legal professionals will find this article timely and compelling, as it provides practical insight into how geopolitical AI maneuvering reshapes cross-border legal strategy, compliance, and tech governance. By positioning China’s policy as a global pivot point, this piece equips lawyers and policymakers with a nuanced understanding of how AI regulation is being shaped on the international stage—prompting further investigation and dialogue.
This analysis by Matt Blaszczyk, Geoffrey McGovern, and Karlyn D. Stanley explores how U.S. copyright law grapples with AI-generated content, addressing whether AI-assisted works qualify for protection and how training datasets are treated under both U.S. and EU doctrines. It highlights a key insight: U.S. law requires human “authorial contribution” for copyrightability, while the EU allows rights holders to challenge commercial AI training—underscoring a growing legal divide. Timely hearings in Congress and updates from the U.S. Copyright Office make this discussion urgent for legal professionals managing copyright risks in generative AI projects. The analysis empowers practitioners with a clear roadmap for navigating emerging policy debates, licensing strategies, and litigation landscapes around AI-authored content—making it essential reading for IP counsel advising on innovation-driven initiatives.
This expert analysis from Dentons partners Jennifer Cass, Anna Copeman, Sam Caunt, and David Wagget examines the unresolved IP challenges arising from generative AI in 2024 and the legal “cliffhangers” heading into 2025. It highlights key issues like copyright infringement during AI training, ownership of AI-generated works and inventions, and emerging litigation—such as Getty Images v. Stability AI. Legal professionals will find value in its forward-looking take on 2025 reforms, including licensing trends, contractual risk strategies, and pending court rulings. Written with practical insight, this piece equips lawyers with proactive tools to guide clients through rapidly evolving AI‑IP terrain.