Ekene Chuks-Okeke

🔎 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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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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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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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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From Husch Blackwell: We are currently tracking thirteen privacy and AI-related bills that previously crossed chambers prior to the legislative deadline. With the California legislature closing on August 31, we will be providing weekly updates on the progress of these bills. #dataprivacy #ai #artificialintelligence #california #legislation

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In our latest Future of Privacy Forum blog post, Tatiana Rice and I examine the history-making Colorado Artificial Intelligence Act, the first #law in the US to comprehensively regulate the development and deployment of #AI systems. In particular, we explore the law's broad scope of regulated entities and their role-specific obligations, and we outline how the law establishes a duty of care to mitigate algorithmic discrimination. We also note the law's novel consumer rights and the rulemaking and enforcement authorities it grants to the Attorney General. I also encourage you to read FPF's policy brief on the Colorado law (linked in the blog post). Extra shout-outs to Tatiana Rice, Keir Lamont, and Jordan Francis for publishing this (extremely) helpful resource.

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AI and Copyright The world of intellectual property is grappling with a new frontier: artificial intelligence (AI)-generated art. A recent case in China sheds light on how courts are approaching the question of copyright protection for these creations.  Read the full article in the link below to discover how this would play out in New Zealand. https://lnkd.in/ghHA_Uai

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The USPTO has released a crucial update on #patent #subjectmattereligibility, focusing on artificial intelligence (#AI) inventions. This guidance, effective July 17, 2024, aims to provide clarity and consistency in evaluating AI-related patent applications under 35 U.S.C. § 101. Key takeaways for in-house patent counsel: 1. Enhanced Clarity: The guidance offers additional insights on applying subject matter eligibility criteria to AI inventions, building on previous guidelines. 2. New Examples: Three new examples demonstrate the application of the guidance across various technologies, helping practitioners navigate complex AI patent scenarios. 3. Federal Circuit Alignment: The update incorporates discussions of relevant Federal Circuit decisions on subject matter eligibility. 4. Public Feedback Opportunity: The USPTO is accepting comments on the guidance and examples until September 16, 2024. 5. Broader AI Initiative: This update is part of a larger USPTO effort addressing AI's impact on intellectual property, including recent inventorship guidance for AI-assisted inventions. For in-house counsel, this guidance presents an opportunity to refine AI patent strategies, potentially increasing the likelihood of securing protection for AI innovations. It's crucial to review the full guidance and examples available on the USPTO's AI-related resources webpage. #PatentLaw #ArtificialIntelligence #IPStrategy Thoughts on how this might impact your AI patent portfolio? Let's discuss in the comments! Citations: [1] https://lnkd.in/eUbkGXvG

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Spellbook, the AI copilot for lawyers, announced its integration of content from Thomson Reuters Practical Law. Users of the integration will be able to streamline contract and clause drafting in one place by pairing access to thousands of Thomson Reuters Practical Law’s attorney-editor-created standard documents and clauses with Spellbook’s AI drafting capability, allowing them to rapidly implement tailored content based on specific needs. “AI continues to revolutionize how lawyers everywhere can leverage the latest technology to focus on meaningful, important work," said Joseph Dormani, partner at Thomson Reuters Ventures. "By integrating Practical Law content into Spellbook, we are continuing to push the advancement of the profession." “We’re proud to be working with Thomson Reuters Practical Law to supercharge how our customers draft legal content,” said Spellbook co-founder and CEO Scott Stevenson. “Since Thomson Reuters Ventures invested in us in 2023, we’ve been bullish about the potential of combining our AI drafting tool with the most trusted commercial legal collection of drafting resources in the world.” https://lnkd.in/eh2hmrTm #LegalTechTalk #LegalTech #Legal #Law #LegalAI #Partnership #ProductLaunch

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The UK patents cause list is showing that the judgment on Lenovo's application to obtain a court-forced interim licence from Ericsson (a la Xiaomi v Panasonic reasoning but on different facts) is due to be handed down tomorrow. I'm predicting no licence and the lack of undertaking by Ericsson to be bound by a UK court FRAND decision to be determinative. If I'm wrong and an interim licence is ordered then the UK is surely going to become the de facto jurisdiction for implementers looking to pre-emptively fend off injunctions with an easy playbook: commence proceedings, request and get interim licence from a (protesting) SEP-holder, use interim licence to avoid injunction globally pending FRAND trial. Easy. #SEP #FRAND

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The US Copyright Office calls for new federal law to tackle the “serious threat” of deepfakes, as outlined in their report on copyright and AI. "Copyright and Artificial Intelligence Part 1: Digital Replicas" examines the impact of realistic but false digital depictions. Cynthia Cole of Baker McKenzie praised the report as a “thoughtful and multi-faceted review” of deepfakes. Read the full story here: https://ow.ly/BPT250SR5Hf #AIandCopyright #DeepfakeImpact #CopyrightLaw

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The brain is the new privacy frontier: Responding to developing technologies in the neurotech space, a number of American states have amended their privacy laws to include "neural data" in their definition of sensitive personal information. Some require opt-in consent for its collection, others simply the possibility for a data subject to opt out. Some have included employees' neural data in the definition, others not - with varying implications for privacy protection:

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Innovation jobs in law are undervalued and underpaid. There, I said it. Especially now, when firms critically require talent that is able to: 💥make sense of the #legaltech and legal AI ecosystem, 💥identify use cases, 💥match the right solutions to those use cases, 💥translate between technical / IT teams and lawyers, 💥run time-consuming pilots to test and validate solutions, and 💥drive change management and adoption initiatives. The innovation professionals who can do all of this and also build teams and speak to clients, often developing new opportunities for the firm with those clients, are driving real, long-term value for the firms they work for. They are also most often former practicing lawyers, bringing subject matter expertise to everything they do. They should be paid in line with the top roles at the firm, and yet we're not seeing them being valued anywhere close to that. Law firm leaders: these are the professionals you need to take your firm forward into the future. Compensate them accordingly. #legalinnovation #legal #law #futureoflaw

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As generative AI evolves, so do concerns over copyrighted training data. Explore Danner Kline's latest IP IQ blog post to learn more about the proposed Generative AI Copyright Disclosure Act of 2024, aimed at enhancing transparency while safeguarding innovation and IP rights. [https://bit.ly/4dGlITK]

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Insightful AI Advisory by the USPTO Pinpoints Potential Pitfalls DC IP Lawyers explore the evolving landscape of artificial intelligence (AI) integration in intellectual property (IP) law, noting its growing prominence akin to the once-futuristic tools like spell check in word processing. AI’s application in IP law offers tangible benefits such as increased efficiency and reduced costs in patent drafting and prosecution before the U.S. Patent and Trademark Office (USPTO). While the USPTO acknowledges the positive impact of AI in legal practice, it also underscores potential challenges and cautions practitioners about associated risks. The USPTO’s proactive stance on AI innovation, in alignment with initiatives like the Council for Inclusive Innovation (CI2) and Empowering Women’s Entrepreneurship (WE), emphasizes the need for balanced regulation. A recent notice of rulemaking issued by the USPTO aims to mitigate risks and allay concerns surrounding AI utilization in legal proceedings. In its Practice Guidance, the USPTO clarifies the applicability of existing rules to AI tools, eschewing the need for separate AI-specific regulations. Notably, practitioners are not mandated to disclose the use of AI tools in submissions to the USPTO. However, they bear the responsibility to ensure the accuracy and veracity of AI-generated content, as human verification remains imperative. This includes adhering to signature requirements and upholding ethical standards in patent and trademark filings. AI-enabled solutions hold promise in streamlining various aspects of IP law practice, from prior art searches to document reviews. Nonetheless, human oversight is indispensable to validate AI outputs. The USPTO acknowledges its own utilization of AI tools by examiners, emphasizing the need for robust review mechanisms to prevent inaccuracies or omissions. The Practice Guidance delineates key areas where existing rules govern AI-related activities before the USPTO, emphasizing practitioners’ duty of candor, confidentiality, and competent representation. Failure to meet these standards may result in penalties, including the striking of submissions or disciplinary actions. The Guidance underscores the importance of practitioner diligence in reviewing AI-generated materials before submission, ensuring accuracy and compliance with patentability requirements. In cases where AI systems contribute substantially to patent claims, full disclosure to the USPTO is mandated to uphold integrity and transparency in the patent process. In conclusion, while AI presents transformative opportunities in IP law, it necessitates vigilant oversight and adherence to established regulatory frameworks. DC IP Lawyers advocate for responsible AI integration, emphasizing the paramount importance of human oversight in maintaining legal integrity and upholding patent standards.