Intellectual Property Consulting

Most designers don’t know this. But they own the copyright of the logos they create. While it's very common to have clients who assume that since they have paid for it, they own it but that is not the reality. In India, the creator of the logos, be it a designer or an agency, automatically owns the copyright, unless there’s a written agreement stating otherwise. Without clear ownership, your business might face restrictions on how you use the logo. The designer could limit your usage, or you might need to pay additional fees to use your logo across different mediums. This is what both the designer and the brand need to be careful about: → Always have a written agreement before the design process begins. Ensure that the agreement states who the copyright is assigned to. This document should cover all rights, like reproduction and distribution of the works. → Always include specific intellectual property (IP) clauses in your contract. These should cover who owns the work, the scope of its use and any other limitations. Never assume that paying for a logo automatically grants you ownership. Clarify the ownership upfront to avoid repercussions later. How often do you have this discussion with your clients? #graphicdesigner

🚨 If you're interested in AI COPYRIGHT, the paper "The Heart of the Matter: Copyright, AI Training, and LLMs" by Daniel Gervais, Noam Shemtov, Babis Marmanis & Catherine Zaller Rowland is a MUST-READ. Here's why: ╰┈➤ Since the recent Generative AI boom started in November 2022, with the launch of ChatGPT, the AI copyright lawsuits have been piling up, and various academic papers covering LLM-related copyright infringement have been published, discussing, e.g., if "fair use" can be applicable or who can be covered by Article 3 of the EU copyright directive (I have been covering both the lawsuits and the articles in my weekly AI governance newsletter - make sure to subscribe). ╰┈➤ We are almost two years into the Generative AI wave, and we still do not have a final legal answer for the AI copyright conundrum. As the public debate proceeds (and the pressure from all the AI hype increases), I have recently read opposing arguments coming from the fields of copyright law and data protection law, stating that because there is no "copy" (copyright) or "storage" (data protection) in the traditional sense of these legal terms, the law would not cover the backstage processing that happens during LLM training and fine-tuning. According to these approaches, which support some version of 'Generative AI exceptionalism,' copyright and data protection infringement claims would not make sense in the context of LLMs because "it's different." ╰┈➤ This paper covers the copyright side of the debate and refutes Gen AI exceptionalism. It brings us back to the legal grounds and is ESPECIALLY GOOD at breaking down the technical part of how LLMs work, and how they infringe copyright law during input and output, and when they remove rights management information. If you're interested in AI and copyright, you can't miss it. ╰┈➤ I'll finish with a quote from the paper: "Now the most profound technological change in history is upon us. A technology that can produce commercially competitive content that is likely to displace some human-created works. It can do this because it has absorbed the works of human authors. The stakes could not be higher." ╰┈➤ Read the full paper below. 🏛️ STAY INFORMED: If you're interested in the AI copyright debate, I recommend you join 37,700+ people who subscribe to my AI governance newsletter, where I discuss the latest developments in AI policy, compliance & regulation, including AI copyright lawsuits and papers. If you have friends in this field, tell them to subscribe! (link below). #AI #AICopyright #AIGovernance #AIRegulation #AICompliance #LLMs

AI and Copyright: A Landmark Clarification. The U.S. Copyright Office has published an important report on AI-enhanced creativity, which holds significant implications for artists, musicians, writers, and creators in various fields. 🔹 What’s Copyrightable? If an artist modifies, arranges, or adapts AI-generated content in a way that demonstrates human creativity, that work may qualify for copyright protection. This means AI can be a tool — but not an author. 🔹 What’s NOT Copyrightable? If a work is entirely generated by AI (e.g., typing a prompt into a chatbot or an AI art generator), it cannot be copyrighted. The Office made it clear: machines can assist, but they can’t hold authorship. 🔹 What’s Next? This decision reinforces that human ingenuity remains central in creative works. But there’s still an elephant in the room: AI models trained on copyrighted works without permission. The Copyright Office is working on a separate report to address licensing, liability, and ethical concerns in AI training. 💡 Why This Matters For businesses and creators leveraging AI, this provides clarity: AI is a powerful tool, but copyright still protects original human contributions. If you’re using AI, your creativity must be evident in the final work for it to be protected. 🚀 What do you think? Does this approach strike the right balance between innovation and protecting human creators? #AI #Copyright #Creativity #DigitalTransformation #ArtificialIntelligence

As a young engineer, I was focused on getting #patents for the new products I was developing. Until one day. I was told my latest invention would not be patented, rather kept as a trade secret.   Wait, what?!   You mean just keep quiet about it and hope nobody finds out? Like the secrets we used to share with our best friends in school?   Since then, I have signed many employer agreements promising not to reveal business processes, customer lists, technical know-how and so on. All #tradesecrets. But I would wonder, what happens if these secrets get out?   I found the answer in the #WIPO Guide to Trade Secrets and Innovation (https://lnkd.in/e4DCMZhD), published by my World Intellectual Property Organization – WIPO colleagues András Jókúti, LL.M., Tomoko Miyamoto and their team. It takes you through:   ✔ HOW trade secrets have evolved, since the Babylonian king Hammurabi's time to present day, ✔ its relevance in driving innovation, ✔ WHAT exactly is a trade secret, (something secret, has a commercial value, and reasonable steps have been taken to protect it) ✔ HOW it can be protected, and ✔ WHAT shape does it take in today's #GenAI dominated world.   And the answer to my question?   🔹 Trade secrets are protected by the applicable national laws of the country: common law, contract law, or employment law. 🔹 Confidentiality agreements and non-disclosure agreements that most employees sign provide protection of trades secrets also. 🔹 Unlike patents that provide exclusive rights at the cost of making information public, trade secrets are not exclusive and someone could very well come up with the idea protected independently or reverse engineer a product 🔹 But, if the trade secret is disclosed in a "manner contrary to honest commercial practices," legal action can be taken, or settled amicably through mediation.   Trade secrets can be a powerful way to protect #IP, just look at the recipe for Coca Cola. Kept secret for decades, it is still making money for the company!

The US Copyright Office has just released its Part 3 Report on Generative AI Training, and it addresses the elephant in the dataset: Can AI companies use copyrighted content to train their models without permission or payment? The report says this is not a grey area. Training on copyrighted works is not automatically protected under fair use, particularly when conducted at scale and for commercial use. The report outlines multiple stages that can raise infringement claims from scraping and dataset curation to model training and the generation of outputs. The Office explicitly rejects the idea that “publicly available” content online is free for use in AI training. That position, often relied on by developers, does not hold up under copyright scrutiny. The fair use analysis is direct: 𝐏𝐮𝐫𝐩𝐨𝐬𝐞: The use is commercial, high-volume, and systemic, not limited or research-driven. 𝐀𝐦𝐨𝐮𝐧𝐭 𝐮𝐬𝐞𝐝: Full works and large repositories are routinely copied. 𝐌𝐚𝐫𝐤𝐞𝐭 𝐢𝐦𝐩𝐚𝐜𝐭: AI outputs often compete with the original works and may displace licensed content. 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞𝐧𝐞𝐬𝐬: Using expressive content to generate similar expressive content is unlikely to qualify. The Office states: 𝘛𝘩𝘦 𝘤𝘰𝘱𝘺𝘪𝘯𝘨 𝘪𝘯𝘷𝘰𝘭𝘷𝘦𝘥 𝘪𝘯 𝘈𝘐 𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘵𝘩𝘳𝘦𝘢𝘵𝘦𝘯𝘴 𝘴𝘪𝘨𝘯𝘪𝘧𝘪𝘤𝘢𝘯𝘵 𝘱𝘰𝘵𝘦𝘯𝘵𝘪𝘢𝘭 𝘩𝘢𝘳𝘮 𝘵𝘰 𝘵𝘩𝘦 𝘮𝘢𝘳𝘬𝘦𝘵 𝘧𝘰𝘳 𝘰𝘳 𝘷𝘢𝘭𝘶𝘦 𝘰𝘧 𝘤𝘰𝘱𝘺𝘳𝘪𝘨𝘩𝘵𝘦𝘥 𝘸𝘰𝘳𝘬𝘴. This is a key clarification for the industry. Developers relying on generic fair use claims will have to prove that their specific training methods and outputs meet the legal threshold but most won’t. The report also addresses and rejects common defenses: 📌AI training is not a “non-expressive” use. 📌Public access is not the same as permission. 📌Training on infringing datasets attracts stricter scrutiny. While the report stops short of policy prescriptions, it identifies extended collective licensing as a possible solution where voluntary markets fall short. It also notes legal and operational barriers that would need to be addressed for such a system to work. The report can be accessed at: https://lnkd.in/gD8fn-jA #copyright

#GenerativeAI & #IntellectualProperty: Navigating the Deep Waters of New Tech 🤖 The rise of generative AI has redefined discussions on technology's potential impacts: job displacement, misinformation, security threats, and amplifying societal biases, to name a few. But, amidst all these, a unique challenge arises - its intersection with Intellectual Property (#IP). 🖋️ IP encompasses human intangibles: inventions, creative expressions, logos. Intellectual Property Rights (IPR) ensures creators have exclusive rights to these treasures. Now, with generative AI's increasing influence, we're witnessing: 🔵 Training Data Risks: Lawsuits allege use of copyrighted material in AI model training without approval. Fair use defense? Still in debate. 🔴 Model Output Risks: Generated content by AI might infringe upon IP rights. Where's the line? Legislation and litigation might decide. 🟢 Software Licensing Risks: AI-generated code might carry licensing from training data, possibly forcing your proprietary software to be open source. 🟡 Data Leakage Risks: Using confidential inputs on generative AI can risk data breaches, as seen with ChatGPT incidents. 🟣 Inventorship Risks: If AI aids invention, can it be a co-inventor on a patent? Current mandates lean towards human-only inventors. Generative AI's IP quandary isn't just a developer's problem. Even 'out-of-the-box' AI solutions pose risks. As we stand on this tech frontier, balancing protection with innovation is key. Deloitte's IP practice is geared for this very challenge, assisting organizations to sail these waters with confidence. Interested in managing your AI's IP risks? Reach out to Deloitte. Let's innovate, responsibly! ✨ https://lnkd.in/eVc4ruz7 #AI #Risks #TechChallenges

Use of Copyrighted Content for A Competing AI Tool is not Fair Use – US District Court of Delaware In a case recently decided by the  US District Court of Delaware involving the use of copyrighted legal content for an AI tool, the Court concluded that the use of the content amounts to infringement and not fair use. Here is a short note on the case:   - Brief Facts: The dispute arose between Thomson Reuters and ROSS Intelligence. ROSS sought to license Westlaw’s content to train its AI-based legal research tool, but Thomson Reuters declined due to competition concerns. Subsequently, ROSS collaborated with LegalEase, which provided approximately 25,000 "Bulk Memos" derived from Westlaw headnotes to train ROSS's AI. - Copyright Protection: The Court stated that Westlaw’s headnotes and Key Number System are original works protected under copyright law. - Copyright Infringement: The Court found that ROSS's use of materials derived from Westlaw’s headnotes to develop a competing product constituted unauthorized reproduction of protected content, amounting to infringement. - Fair Use Analysis   - Purpose and Character of the Use: The Court determined that ROSS’s use was commercial and intended to develop a competing legal research tool, which weighed against fair use.   - Nature of the Copyrighted Work: The Court acknowledged that Westlaw's headnotes are factual and less creative, which favored fair use.   - Amount and Substantiality: The Court stated that ROSS used only portions of the headnotes, and since the output did not reproduce the copyrighted material, this factor favored fair use.   - Effect on the Market: The Court held that ROSS’s product directly competed with Westlaw, potentially affecting its market share, which negatively impacted the market for the original work and weighed against a fair use finding.   - Conclusion: The Court granted partial summary judgment in favor of Thomson Reuters, determining that ROSS’s actions did not qualify as fair use and constituted copyright infringement. The case is attached for your reading and sharing. Case Citation: Thomson Reuters Enter. Ctr. GmbH v. ROSS Intelligence Inc., No. 1:20-cv-613-SB (D. Del. Feb. 11, 2025). #CopyrightLaw #FairUse #AIandLaw #IntellectualProperty #LegalTech #AI #CopyrightInfringement #LegalResearch

Branding without trademarking is like building a house on land you don't own. When I launched Business Class, the first thing I did wasn't design the curriculum — it was lock down the trademark. Here's what most founders get wrong about intellectual property protection: 🎯 Trademarks are context-specific: You don't trademark a name "in general." You trademark it by class: → Business Class is in Class 41 (education/digital courses) → If I launch merch? That's Class 25 (apparel) → mobile app? Class 9 (software) This is why two companies can have the same name and coexist — if they're in different classes and not causing market confusion. 🔍 How to research your mark: Use the USPTO TESS database to check availability by class, not just globally. Someone might own "Business Class" for travel booking, but that doesn't automatically conflict with my education business. Context matters. 📝 Two types you need: - Word mark: Protects the name regardless of how it looks - Design mark: Protects your logo/visual identity You want both. ⚠️ Where most applications eie: - Similarity isn't just spelling. - The USPTO evaluates: → How it sounds → How it looks → Whether average consumers could confuse the two "Confusingly similar" kills more trademark applications than anything else. 🛡️ Use it or lose it: Once it's yours, defend it aggressively. If your mark becomes generic (like Aspirin did for Bayer), you lose exclusive rights. A trademark isn't permanent if you treat it as optional. The bottom line: IP is leverage. If you're building a brand you want to scale, protect the asset before you promote it. Because if you don't — someone else will. For founders in the comments: What's the biggest IP mistake you've seen (or made)? Join my Substack for more wisdom & war stories: sophiaamoruso.substack.com

From Idea to Global Impact: Why Startups Can’t Ignore Patents Every startup begins with an idea. Some grow into global brands—others fade away. Here’s the difference nobody talks about: patents. ▶️ A founder in a co-working space patents her AI tool—not just in India, but also in the US & Europe. Investors lean in. ▶️A SaaS startup files early, creating a shield against copycats. Suddenly, they have leverage in partnerships. ▶️A health-tech company protects one breakthrough device—and that single patent becomes their ticket to global expansion. Patents aren’t just paperwork. They’re business assets that: ✔ Attract investors ✔ Build customer trust ✔ Open global markets The question is: Are you protecting just locally—or are you thinking global from Day 1? Your innovation is your future. Protect it like it matters—because it does. 👉 Startup founders: Ready to turn ideas into global advantage? Let’s talk IP strategy. #startups #invention #innovation #ipstrategy #patent #trademark #global #business #investors #funding

Businesses and organisations need strong IPR (Intellectual Property Rights) strategies to protect and monetize their IP. Consider these key IPR strategies: 1- IPR strategy includes fostering innovation and R&D: Businesses should encourage employees to create new ideas, inventions, and works and provide R&D resources. A strong innovation ecosystem may help businesses build a pipeline of valuable intellectual property assets that boost competitiveness and market advantage. 2- IP Protection: IPR strategies focus on IP protection. This requires understanding the organization's IPR (such as patents, trademarks, and copyrights) and taking appropriate legal steps to protect them. Apply for patents, register trademarks and copyrights, and protect commercial secrets. Working with IP legal specialists is essential to ensure proper filing and navigate IP legislation. 3- IP Portfolio Management: Businesses should be proactive in IPR portfolio management. This requires periodic audits to identify and assess IP assets, categorising them by strategic importance, and prioritising resources for their preservation and use. It involves monitoring IP rights' validity and usefulness, making strategic decisions on filing new applications or releasing old assets, and aligning the IP portfolio with corporate goals. 4- Commercialization and licencing: IP licencing works well. Businesses can licence IP to other parties for royalties or other financial benefits. Licencing lets businesses enter new markets, expand, and make money without investing in manufacturing or distribution. Proper licencing negotiations and commercial agreements are essential. 5- International IP Considerations: Global businesses must consider international IP. Understanding IP laws in different countries, registering for global IP protection, managing global trademark portfolios, and resolving cross-border IP enforcement issues are all part of this. Businesses should engage IP specialists or foreign IP lawyers to navigate these issues. 6- Education and Training: Businesses need IPR awareness and training. This involves training staff on IP protection, fostering a culture of IP respect, and ensuring they understand their IP protection and use responsibilities. Partners, suppliers, and customers may get IP training to better collaboration and comply with IP laws. 7- Defensive IP Strategies: Businesses may manage risks, deter infringement claims, and protect their IP assets with defensive IP strategies. This includes strategic patenting, defensive patent portfolios, patent pools, and cross-licensing. Defensive IP measures help organisations avoid lawsuits and improve negotiation positions. It's important to note that IPR strategies should be tailored to the specific needs and goals of each organization. Consulting with IP experts can provide valuable guidance in developing and implementing effective IPR strategies. #ipstrategy #intellectualproperty #ipmanagement #businessadvisory #consultancy