Frank Gerratana

🔎 Quick highlights from the draft of the American Privacy Rights Act (APRA) ➡ Covered data is now defined as "information that identifies or is linked or reasonably linkable, alone or in combination with other information, to an individual or a device that identifies or is linked or reasonably linkable to 1 or more individuals." ➡ APRA covers data that can be derived or inferred. Currently, only California and Oregon address this. ➡ APRA uses "Individuals" instead of "Consumers" (which most state privacy laws use Consumers). The devil is in the definition 👿 ➡ APRA's applicability extends beyond the business-to-consumer context and includes nonprofit organizations. ➡ Exemptions are provided for government entities and their service providers, small businesses with less than USD40 million in rolling three-year average gross revenue that handle the data of fewer than 200,000 individuals or do not broker data, and publicly available information. ➡ Employee information exempt to the extent it is provided for publicly available "business contact information" that is made available on a website or online service to all members of the public, including the name, position or title, business telephone number, business email address, or address of the employee. #privacy #APRA #dataprotection #individuals #employees #organizations #smallbusinesses #governmententities #publicinformation

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Earlier today, the California Privacy Protection Agency Board voted to advance the new draft CCPA regulations to formal rulemaking. We thought it might be helpful to provide a series of short high-level summary webinars on the new rulemaking topics, starting with automated decisionmaking technology (ADMT). If you missed the Board meeting, the draft ADMT rules were a source of many comments and concerns, including their impact on artificial intelligence. There can be no doubt that the ADMT regulations will generate many proposed revisions. https://lnkd.in/guW-BJPc

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Avoid the dark side, you must. As noted in Luis’s summary, according to the CPPA Deputy Director Macko, “[d]ark patterns aren’t about intent, they’re about effect.” This follows on increased scrutiny of dark patterns by the FTC and other authorities. #ccpa #privacylaw

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When AI is trained with unlicensed copyrighted material, the question of infringement versus fair use remains unresolved. Many copyright holders assert that this use violates their rights, and are litigating to address the issue. In light of this, is it premature to require AI companies to disclose which copyrighted works are used to train their generative AI systems? #ai #trainingdata

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The USPTO has proposed a new rule that could significantly impact inventors seeking patent protection. The proposal introduces a steeply graduated fee system for terminal disclaimers, which are used to address non-statutory double patenting issues. While the USPTO argues that this change will make the patent examination process more efficient, it could also impose higher fees on inventors, potentially hindering innovation. As a patent practitioner, I am concerned that these changes may disproportionately impact individual inventors, small businesses, and non-profits, who are already navigating high costs in securing patent protections. The proposed fee increases seem unnecessary, especially since patent examiners can issue 103 rejections at a time. It's important for all players in the innovation ecosystem, large and small, to have access to the patent system. I encourage others in the community to voice their concerns during the public comment period. Let's ensure that the patent system continues to support innovation for all. #USPTO #Patents #USPatent #USPatentProsecution #TechLawyer Source: https://lnkd.in/grAvbiZz

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The law for design patent obviousness may change in the upcoming months when a decision is issued from the Federal Circuit Court of Appeals from February 2024 en banc rehearing of LKQ Corp. v. GM Global Technology Operations LLC. Although the law has not yet changed, the application of the current law has recently changed at the United States Patent & Trademark Office (USPTO). With the use of AI-assisted searching, design patent examiners appear to be issuing more obviousness rejections under the current law. While we await any change to the law, practitioners should be prepared to address AI-assisted design patent rejections and should develop strategies for maintaining a design patent portfolio while the law and procedure evolve. Learn more about this trending IP topic from Brooks Kushman P.C. attorney Michael Turner. Read more: https://lnkd.in/epms2vAJ #designpatents #ai #intellectualproperty

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I’m interested in how AI is impacting law practice. The U.S. Patent and Trademark Office has issued guidance on how to determine inventorship when AI was involved in creating the invention. In 2022, in Thaler v. Vidal, the Federal Circuit held that “only a natural person can be an inventor, so AI cannot be.”  So, how can something developed by AI be patented? ·      The guidance reaffirms the Federal Circuit decision: Named inventors must be “natural persons.” A non-human, such an AI system, cannot be listed as inventor, even if it was “instrumental” in creating the invention. ·      A person named as inventor must make a “significant contribution” to any AI-assisted invention. ·      This is determined by existing inventorship law: The inventor must contribute in some significant way to the invention’s conception or reduction to practice. ·      USPTO gives an example: A person who merely 1) recognizes the need for a new design to solve a specific problem, 2) prompts an AI system to create a design, and 3) reviews the design outputted by the AI system, has not made a significant contribution. ·      On the other hand, a significant contribution “could be shown by the way the person constructs the prompt in view of a specific problem to elicit a particular solution from the AI system.” ·      These distinctions could be difficult to make in practice. It will be interesting to see how this plays out in real world examples as AI develops and its use in creating inventions increases. ·      The USPTO guidance tells us that inventors using AI should be prepared to demonstrate, with supporting documentation, the specific things they did to contribute to the invention and how AI was used to assist. https://lnkd.in/g6gx_eTV #artificialintelligence #technology #AI

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Many software inventions are about user interaction flows. It's good patent drafting practice to focus on method claims for these. They typically have less "clutter" than apparatus claims, and make it easy for the examiner to understand the gist of the invention. Are you on team "method claim" or team "apparatus claim"? #patentingAI #softwarepatent #UX #UI #AI #IP

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➡️ All IP people, this is a list to follow! Mustafa Cakir, RTTP, QPIP makes a weekly wrap up of top IP posts in LinkedIn. This week I got to the list too! Easy way to keep up interesting and relevant IP topics! Thanks for sharing Mustafa!

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🤖📜Breaking news in the world of AI regulation! 🤖📜 California Governor Gavin Newsom has vetoed SB 1047, which aimed to impose safety regulations on large-scale AI models, but signed AB 2013 into law, requiring transparency from generative AI developers. The future of AI regulation in California remains dynamic, as this decision will influence both developers and regulators. ⚖️🔍 Thank you to my co-authors for their insights and contributions on this topic: Leigha Beckman, Minna Naranjo , and Andrew Gray! 🙌💡 Read the full article for more details on what this means for AI safety and transparency moving forward. 🚀🤝 #AI #AIsafety #GenerativeAI #Transparency

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Dion Bregman is way better at using emojis than I am, so a re-post it is! Check out this article for insights into some California AI bills that were passed / vetoed over the weekend. And, if you're in the GenAI space, make sure you know what public disclosures you may need to make by January 2026! #wearemorganlewis

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On April 17, Colorado Governor Jared Polis signed HB 1058 into law, which means it is time to update our chart comparing the various definitions of sensitive data in consumer data privacy laws. Here's some more context: 1️⃣ HB 1058 amends the Colorado Privacy Act to add biological data (and through it neural data) as a category of sensitive data in the Colorado Privacy Act. 2️⃣ The true impact of the amendment is debatable as the definition of biological data states that the data must be "used or intended to be used, singly or in combination with other personal data, for identification purposes." 3️⃣ Colorado is the first state to add biological/neural data to its state privacy law. This continues the trend over the last two legislative sessions of state lawmakers expanding the types of data covered as sensitive data. Given the constant expansion, at some point it may be easier to define what is not sensitive data rather than what is. 4️⃣ California is also considering a bill to add neural data to the CCPA's definition of sensitive personal information. 5️⃣ Colorado isn't done. The legislature is still considering two other bills to amend the Colorado Privacy Act, dealing with the treatment of biometric data and minor's data. 6️⃣ Here's a link to the Colorado bill for those interested: https://lnkd.in/gE7KPyY9

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American Privacy Rights Acts - A surprise development Few important highlights of the Act: - The American Privacy Rights Act (APRA) represents a significant development in the U.S. federal privacy landscape, surprising many with its emergence amidst prior stagnation. - Spearheaded by key figures in Congress, including Chairpersons Cathy McMorris Rodgers and Maria Cantwell, the bill enjoys bipartisan and bicameral support, enhancing its potential for enactment. - Its broad applicability extends to both commercial entities and nonprofits, with exceptions carved out for small businesses meeting specific revenue and consumer data criteria. - Noteworthy provisions include the introduction of a private right of action, empowering individuals to enforce certain aspects of the law, a departure from previous federal privacy bills. - The APRA aims to streamline privacy regulation by preempting state laws, providing a unified national standard enforced primarily by the Federal Trade Commission (FTC) and state attorneys general. - Data minimization principles underpin the bill, requiring entities to justify the collection, processing, and retention of personal data, with stringent consent mechanisms ensuring individual control over their information. - Extensive categories of sensitive data, encompassing health, financial, biometric, and other personal information, are subject to heightened protection and affirmative consent requirements. - Special obligations target entities based on their size and nature of operations, such as large data holders, high-impact social media companies, and data brokers, imposing additional compliance measures. - Executive responsibility and operational governance requirements mandate the appointment of designated privacy and security officers within covered entities, fostering a culture of accountability and compliance, with annual certifications reinforcing organizational commitment to privacy.

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A new LTH Product Briefing dropped this morning! Often, these serve to demonstrate a new product, or a new release or feature from an established provider. Sometimes they highlight services offered to the market. Cognia Law, an alternative legal services provider, offers both, and COO Peter Hall highlights how Cognia's contract management solution helps legal departments simplify and standardize the contract management process for busy and overwhelmed legal teams, often leveraging Cognia's proprietary contracting platform. The result? 💥 Streamlines contract workflows, 💥 Reduces complexity, 💥 Enhanced visibility, 💥 More effective and efficient contract management, and 💥 More cost-effective operations. Read more about this unique offering in the LTH Product Briefing linked below, and make sure to scroll down to see the associated demo video. #legaltech #contracting #contractservices #corporatelegal Janet Taylor-Hall https://lnkd.in/e2ukXaM8

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Great article by Marisa Woutersen at WIPR - World IP Review on Nvidia's rise to be the world's most valuable company. She looks at the relevance of their patent portfolio and compares Nvidia's patent portfolio with other Big Tech companies. The article is behind a paywall but my key takeaways are: - It's very difficult to compare a company like Nvidia that basically has one product (monster graphics cards - yes I know they do a bit more) and tech companies like Samsung who have 100s of products. Inevitably Samsung has way more patents. - AMD is probably their most similar competitor, and Nvidia is ahead here in terms of overall patent filings. - Nvidia is clear playing catch-up with patent filings. They have more pending applications than any other company listed. This suggests there is a realisation that the patent portfolio hasn't kept pace with the company value. Of course, it might also reflect the fact that the suddenly have a lot more cash! - Clearly the value in the portfolio will depend on what and where they invest. The article notes that while AI applications represent core value, where else they invest to diversify beyond AI will be key. The brilliant charts in the article provided by Andrew Samm at Patently. EIP - Better, different.

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Please see the article we prepared on the Mallinckrodt decision, a must read for those in the IP and pharma space.

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Check out this resource from my favorite legal AI expert.

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