Michel Jaccard

For a long time, regulation around data has been designed to restrict sharing—through data protection laws, statutory secrecy obligations, and related legal constraints. More recently, and especially in the European Union, the focus has shifted: new frameworks now aim to enable access and reuse (think of the #DGA, #DataAct, #EHDS, ...). So, what is the current status of data exchange rules in Switzerland? I explore this question in my latest article, just published in sic!. The piece builds on research our firm id est avocats carried out for the Swiss Federal Institute of Intellectual Property IGE IPI, which also led to the creation by the IPI of a public index of data sharing regulations: www.data-sharing.ch. The article examines: 🔹 the consequence of the absence of ownership rights in non-personal data for data sharing and the reliance on contracts and technical measures 🔹 new data sharing models, such as open data licenses, data trusts, data intermediaries, and trusted data spaces 🔹 business-to-business (#B2B), government-to-business (#G2B), and business-to-government-to-business (#B2G2B) data flows 🔹 Swiss policy developments, including a forthcoming federal framework on data reuse 📖 The full article is available in sic! 9/2025. #datasharing #tech #research #law #opendata #datatrust #dataspace

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🎯IP Management Pulse #44 – New Edition Out Tomorrow! The latest IP Management Pulse newsletter is here with key insights from the IP world: 1️⃣ IP in Technological Obsolescence – the shift from traditional IP to data-driven models, including platform licenses and trade secrets. 2️⃣ IP Roadmaps - Making Strategy Actionable – 😎 Alexander Johann Bjørnå explains how to implement business strategies through IP roadmaps. 3️⃣ Copyright & AI Training Data – 😎 Dr. Barry Scannell highlights a $1.5 billion settlement over AI training data usage. 4️⃣ Systematic Trade Secret Management – 😎 🔑Maria Boicova-Wynants shares why proper management is essential for trade secrets. 5️⃣ Timing of Patent Filings – 😎 Maier Fenster explains the crucial balance of filing patents at the right time. 🌟 Deep Dives: BHS Corrugated Case Study – 😎 Maria Boicova-Wynants dives into how BHS turned IP into a competitive strength. Explainable AI in the Courtroom – 😎 Til Martin Bußmann-Welsch from Anita Legal explains how AI transforms legal practices. Additional topics include IP strategies in the service economy and Adobe’s Creative Cloud success. When you want to know whom to follow on LinkedIn, then look at Amelia Skelding, IP Director at Swindell&Pearson, and Wouter Pors Partner at Windt Le Grand Leeuwenburgh. 📝 Thought Leadership by 😎 Giulia Donato – Giulia discusses how IP experts can leverage publishing for visibility and trust in the market. 📬 Subscribe now and catch all this and more in the next IP Management Pulse — out this Thursday! I'll give you the link in the comments 👇 🤗 Thanks to our sponsors: Patent Cockpit; uptoIP® | ABP PATENT NETWORK GmbH; infoapps GmbH; Bösherz Goebel Patentanwälte; Connor 🙏 Thanks to our co-authors - without whom this newsletter would not be possible: Amr Eldakak; Archana Pandit; Dr. Benjamin DELSOL (PhD, LL.M); David Durand; David Kalow; David Perkins — Software Patent Expert; Donal O'Connell; Dr. Dominique Christ, Erdem KAYA; Eric Stasik; Henry K.H. Wang; Dr. Ines Duhanic, LL.M. (Stockholm); Ivan Gauci; Dr. Jörn Plettig; Martin Schweiger; Mustafa Cakir, RTTP, QPIP; Magnus Hakvåg, 🔑Maria Boicova-Wynants; Philipp Hammans; Prof. Kelvin Willoughby; Ricardo Cali; Udo Gennari _____________ 🚀 Hi, are you an IP expert? We're looking for IP subject matter experts for the entire innovation chain of companies. Want to work with firms in Europe to protect their innovation results and strengthen their innovative capacity? I'll give you the Link to the Call 2025 in the comments 👇 - and just send me a direct message here on LinkedIn.

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Legitimate interest is a possible legal basis for the development of AI systems, subject to taking strong guarantees, says France CNIL - Commission Nationale de l'Informatique et des Libertés in new guidance. What are we discussing with our clients? 🔹 Some processes are still "no go" for LI, like targeted advertising based on the profiling of minors or places where consent is legally required (e.g. Gatekeepers under the DMA). Reasonable expectations are key! Things that are Not expected: 🔹 Using private exchanges between two people using an online virtual meeting service for the development or improvement of an AI model for summarizing meetings 🔹 Not excluding from collection sites that clearly oppose harvesting through robots.txt exclusion protocols or CAPTCHAs. 🔹 Developing an open-source image classification model, which would then be used to classify people based on their sexual orientation. Possibly expected: Chatbot provider reusing users' FUTURE conversations with the AI ​​system to improve the AI ​​model subject to: robust privacy notice including warning of all the risks + right to object+ excludes personal data + psedonymization + risk mitigation for memorization and regurgitation. To do: (1) At development: 🔹 measures and procedures that ensure transparent development of the AI ​​system, in particular to enable the auditability of the AI ​​system during the deployment phase (2) Limit the collection of personal data 🔹 prompt anonymization; measures to limit memorization and regurgitation (3) Allow individuals to retain control over data 🔹 right to object / delete 🔹 data subject rights 🔹 ensure this is respected downstream (4) transparency 🔹 robust disclosure including the risks 🔹 DPIA 🔹 media campaigns for education pic by ChatGPT https://lnkd.in/ekvnhVRh

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#AI system or not #AI system? That's the question! 📣📢The European Commission’s recent Guidelines on AI System Definition under the AI Act, issued on 6 February 2025, aimed to clarify what qualifies as an AI system under the AI Act. However, instead of resolving uncertainty, the Guidelines created even more additional questions: 📌Spacious AI systems definition, while was meant to reflect complexity and diversity of vast array of AI systems, raises concerns that some inherently non-AI software may inadvertently fall under its scope due to overlapping characteristics. 📌Additionally, the Guidelines fail to establish consistent prerequisites, as all 7 elements are not required to be present throughout the entire AI lifecycle (some may only appear during specific phases). 📌A significant gap may exist in the lack of distinction / relation between vague concepts of AI system, AI model, AI technique, AI method, AI algorithms, AI solution, foundational models, Gen. AI, general purpose AI, AGI, AI technologies, leaving room for regulatory ambiguity. A wise course of action to clarifying the ambiguities would be addressing the peripheral concepts. 👉With these lingering uncertainties, businesses must navigate AI compliance with caution!!! https://lnkd.in/dJawrYyB

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☝ Need help to map all relevant #digitalregulation that applies to the #LSHC industry? 💥 Great news! A brandnew comprehensive and practical version of the CMS #Digital #Regualtion tracker has just been launched! Visit the Digital Regulation Tracker Tool here: https://lnkd.in/dMKGAPHg CMS Life Sciences & Healthcare Sector; CMS Technology, Media and Communications sector   #CMSlaw #law #digital #technology #regulatory #lifesciences #healthcare  

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📣 Stay updated and compliant: The Luxembourg Data Protection Authority 🇱🇺 (the "CNPD") has just released its recommendations on potential risks associated with DeepSeek AI. Key concerns: - Data privacy and GDPR compliance - Transparency in AI-generated content - users rights and privacy https://lnkd.in/eNGnGnvg #AIRegulation #TrustworthyAI #GDPR

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📢Partnership Announcement: Mathys & Squire x SSA ❗ 🎉 We’re excited to announce our partnership with Mathys & Squire LLP, a leading European IP law firm with a dedicated Swiss startup team! With over 110 years of experience and a network rooted in Europe’s largest IP hubs, Mathys & Squire is committed to helping startups protect and commercialise their ideas on a global scale. Their team of over 110 qualified attorneys brings deep technical and scientific expertise, offering tailored support in German, French, and English! 🤝 At the Swiss Startup Association, we’re proud to work with partners who help founders safeguard their innovations and scale confidently. 👉 Learn more about how Mathys & Squire supports Swiss startups: https://hubs.li/Q03bSjjg0 #SwissStartupAssociation #IPProtection #StartupSupport #Innovation #SwissStartups #Partnership

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Switzerland just did something remarkable that should catch every lawyer's attention: they released Apertus, an AI model that actually respects copyright law. Unlike the major AI companies that scraped the internet first and asked permission later, the Swiss built their model using only data from websites that explicitly allowed crawling. No stealth operations, no legal gray areas. This matters because it proves you can build competitive AI without the copyright infringement lawsuits that are piling up against OpenAI and others. The model performs comparably to Meta's Llama 3, suggesting that respecting intellectual property rights doesn't mean sacrificing capability. Apertus offers something invaluable: a model built to comply with EU regulations from day one, not retrofitted after regulatory pressure. The entire codebase, training data, and development process are publicly available - transparency that's unheard of in an industry where "trust us" has become the standard response to legal scrutiny. https://lnkd.in/eKzkcYyu #AI #tech #law #wolftheiss

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🚨 ALERT ! Switzerland’s AI Regulation: A Blueprint for Innovation & Trust 🇨🇭 Switzerland just unveiled its regulatory approach to AI, striking a balance between innovation and responsibility. Unlike broad, one-size-fits-all AI laws, Switzerland is opting for a sector-specific strategy, ensuring that AI strengthens its position as a global business hub while keeping risks to society in check. 🔹 Key Focus Areas 1️⃣ Council of Europe AI Convention → Swiss Law • This will primarily apply to state actors, ensuring AI aligns with fundamental rights and governance principles. 2️⃣ Sector-Specific AI Regulation • Instead of sweeping AI laws, Switzerland will regulate finance, health, media, and transport individually, ensuring tailored oversight where it’s most needed. • Cross-sectoral rules will only apply to critical areas like data protection and fundamental rights. 3️⃣ Beyond Legislation: Industry-Led AI Governance • AI regulation won’t just be about laws—Switzerland is pushing for self-regulation and industry-led measures like transparency frameworks and voluntary commitments. 🎯 Why This Matters Switzerland’s AI approach is built on three pillars: ⚡ Reinforcing Switzerland as an AI and business hub ⚖️ Protecting fundamental rights while preserving economic freedom ✅ Boosting public trust in AI By the end of 2026, Switzerland will finalize: 📜 A legislative proposal defining transparency, data protection, non-discrimination, and AI oversight. 📌 A non-legally binding AI governance plan, ensuring alignment with Switzerland’s key trading partners. 🚀 A Model for AI Regulation? Switzerland’s targeted, flexible, and innovation-friendly approach stands in contrast to more rigid AI laws emerging elsewhere. Instead of overregulating, it’s coordinating with international partners while keeping businesses competitive. ❓ Should more countries follow Switzerland’s lead in sectoral AI regulation and industry-driven governance? Let’s discuss. ⬇️ #AIRegulation #Switzerland #AIGovernance #Innovation #ResponsibleAI __________________________________ Did you like this post? Connect or Follow 🎯 Jakub Szarmach, AIGP, CIPM Want to see all my posts? Ring that 🔔

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Almost all widely used AI services rely on cloud computing. Particular AI models can run independently on local devices but have a very limited capacity and utility. The German Federal Office for Information Security (BSI) has developed the Cloud Computing Compliance Criteria Catalogue – C5:2020 (https://lnkd.in/df8p6KvF) setting internationally recognized security standards adhered to by many global corporations such as Google, Amazon, and IBM. The criteria envisaged by the Catalogue largely intersect with other international information security standards set by the ISO 27001 and CSA Security Guidance for Critical Areas of Focus in Cloud Computing but also differ from them in certain areas. AI models that run on the cloud require a more tailored approach and the consideration of various aspects that can be unique to them. Therefore, in 2021, BSI published the Artificial Intelligence Cloud Services Compliance Criteria Catalogue (AIC4), covering AI-based services developed and operated in a cloud environment. It is worth noting that ISO 42001, as well as the NIST AI Risk Management Framework, include AI security and safety requirements, but don’t fully cover all cloud-related matters. AIC4 establishes particular audit methods and requirements divided into 8 AI-specific criteria areas: ✅ Preliminary Criteria (PC) ✅ Security & Robustness (SR) ✅ Performance & Functionality (PF) ✅ Reliability (RE) ✅ Data Quality (DQ) ✅ Data Management (DM) ✅ Explainability (EX) ✅ Bias (BI)

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🤖⚒️Color me confused: what's the conflict between the AI Act and the GDPR that the European Parliament? The below document from the European Parliamentary Research Service is making the rounds. It sharply analyses the overlap between article 10 AI Act and article 9 GDPR, on the topic of using special personal data for bias prevention. The #AIAct drafters sought to allow bias mitigation measures for high-risk AI systems. This requires so-called special personal data, such as on ethnic origin or sexual preference, as you can't check for discrimination on ethnic origin if you do not have that data. Article 10(5) AIA creates a specific legal regime that permits this. How does that relate to the GDPR? Article 9(2)(g) allows an exception to the prohibition on processing of such data if "necessary for reasons of substantial public interest". Recital 70 AI Act declares bias mitigation to be such a reason, and the AI Act is Union law, which is enough to trigger the exception. Often forgotten however is that avoiding the prohibition is not enough under GDPR: you still need a ground for processing (art. 6 GDPR). In my book 📘The Annotated AI Act I argue the ground is the legal necessity (6(1)(c) GDPR), as bias mitigation is mandatory under the AIA (art. 10(2)(f) and (g). The paper below skips around that issue, but does note that you cannot do bias checks unless you _have_ the special personal data. But how could you ever collect it? Few would respond to a checkbox "Please collect my gender, ethnicity and sexual preference to detect bias in your AI". Then, and here's where it goes wrong, the paper states "The act clarifies that, when the AI Act and the GDPR collide, the GDPR prevails, and states explicitly that its provisions must not affect the GDPR's application." The argument then is that article 9 GDPR prohibits the use while 10(5) AIA permits it, which is a form of collision therefore the GDPR prevails and article 10(5) goes out the window. This is a misreading of article 2(7) AI Act, which does say that the GDPR remains unaffected but does add that this is "without prejudice to Article 10(5)". In law, when A is without prejudice to B, this means that A applies except when B does. So here, article 10(5) *does* apply regardless of what the GDPR has to say on the matter. I therefore do not see the conflict.

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