IPWatchdog Unleashed

IPWatchdog Unleashed

By Gene Quinn

Each week we journey into the world of intellectual property to discuss the law, news, policy and politics of innovation, technology, and creativity.  With analysis and commentary from industr

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Best of IPWatchdog Unleashed

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  1. Number 1: Patent Blame Game: Are 70% of U.S. Patents Really Defective?

    Send us Fan Mail This week on IPWatchdog Unleashed I do not have a guest. Instead I want to take this opportunity to share my thoughts on the complex intersection between patent quality, patent examination and the Patent Trial and Appeal Board (PTAB). My interest in speaking today about these issues is triggered by the confirmation hearing last week for John Squires, who is President Trump’s nominee to be the next Under Secretary of Commerce for Intellectual Property and Director of the United States Patent and Trademark Office. During the hearing, Squires said his focus will be on making sure patents are, in his words, “born strong” because the PTAB has shown that 68% of issued patents are defective. This response from Squires has caused great concern for some who understood him to be saying that he believes the U.S. patent system is suffering from the issuance of low-quality patents. The reason this is so concerning is because the debate surrounding patent quality in the United States has historically focused on the notion that the Patent Office is letting too many bad patents slip through, a notion that has been promoted by a cast of characters and high-profile companies that have championed the very existence of the Patent Trial and Appeal Board, as well as the creation and use of various procedures that have made it ever more easy to strip patents away from patent owners. The problem with the low-patent quality narrative is that it just isn’t true. But does Squires believe the Patent Office is really issuing low quality patents and that is the problem? Does he believe the PTAB is doing a good job and is correct to find 70% of patents completely defective? Or does he believe the PTAB is aggressively overactive and should focus on error correction only where there is obviously a mistake and stop engaging in second guess of patent examiners? These are important questions, which didn’t get asked or answered as too many Senators used his hearing as an opportunity for scoring political points with the DOJ nominees who were having their hearing alongside Squires. Visit us online at IPWatchdog.com. You can also visit our channels at YouTube, LinkedIn, X, Instagram and Facebook.

    25min
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  2. Number 2: IP and the Wild West Landscape of AI

    Send us Fan Mail This week on IPWatchdog Unleashed I speak with Allison Gaul who serves as legal counsel for Boston Consulting Group. She is responsible for evaluating digital products with an eye towards intellectual property strategy, value creation, and legal risk. She is also a recovering, or at least former patent attorney. She does still advise BCG on patent issues, but she is not drafting and prosecuting patent applications at this point. We begin our conversation with me asking about what she believes are the biggest legal issues in the IP world today. Gaul did identify several things that stay top of mind for her, with various issues relating to data front and center as the top issue. The second area identified by Gaul was open source, and how many of the AI companies promoting “open source” are really not truly open source because often the model, weights and/or training data are not made available, which makes it seem like these companies are racing to gain market share and ultimately “doing a little bit of a switcheroo.” The third and final thing that Gaul identifies as being constantly top of mind is the overall speed of AI development. We also discuss how the future will likely have a handful of very large companies that provide the backbone of future AI tools. These large AI giants will be very good at machine learning and very good at digesting massive amounts of information. Then we will likely see silos of expertise established. These silos or niches will be dominated by small companies that operate within a niche industry that they know really well. Indeed, we are already seeing small companies developing specific tools that are much better for a specialized purpose because they understand what that specific industry of subset needs. We go on to discuss fair use, particularly discussing the legal troubles facing Meta, and ethics around AI development and use, as well as the importance of prompts and how it is frustrating—to say the least—that AI companies do not seem interested in helping users learn how to get better at prompting AI tools to get better results. Visit us online at IPWatchdog.com. You can also visit our channels at YouTube, LinkedIn, X, Instagram and Facebook.

    56min
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  3. Number 3: The Existential Threat of AI Consciousness

    Send us Fan Mail This week on IPWatchdog Unleashed we explore whether Artificial Intelligence (AI) technology has progressed to the point where it has already achieved consciousness. In a nutshell, the answer is our panel of technologists do not believe AI is very close to achieving consciousness, but that it is indeed possible for AI to reach the point of consciousness, and to even reach the point of self-reflection, which would pose an existential threat to humans. Our conversation this week is from a panel presentation titled “Artificial Intelligence Today: A Discussion of the Technical Landscape of AI.” I moderated this conversation, which was between Jason Alany Snyder, who is Chief AI Officer for Momentum Worldwide, Malek Ben Salem, an AI expert, technologist and consultant, Dustin Raney, who is Head of Industry Strategy for Acxiom, and Dina Blinksteyn, who is partner and co-chair of the AI Practice Group at Haynes Boone. We begin by asking whether AI has become sentient, and if not when we can expect AI will become sentient, which is a question I’ve asked Jason Alan Snyder each of the previous two years we have hosted an AI specific conference at IPWatchdog Studios. Two years ago, he predicted AI would become sentient within 15 years. Last year he predicted AI would become sentient within 14 years. Predictably perhaps, he agreed with his previous predictions and this year said, “13 years is probably a good guess,” said Snyder. As the conversation unfolded, we spoke about whether hallucinations continue to be a problem for AI, whether the Turning test remains relevant with respect to defining AI, and fundamental aspects of what it means to be human. And we wrap up at the point where Snyder and Ben Salem discuss how AI could become an existential threat to humanity. Visit us online at IPWatchdog.com. You can also visit our channels at YouTube, LinkedIn, X, Instagram and Facebook.

    38min
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  4. Number 4: AI, Quantum and IP: Are We Ready for What’s Next?

    Send us Fan Mail This week on IPWatchdog Unleashed we have a special conversation that was recorded at the end of our AI 2025 program in front of a live studio audience. Joining me were Stephanie Curcio, Clint Mehall, and John Rogitz, who along with Wen Xie, make up the new IPWatchdog Advisory Committee. Each of these people have been long-time attendees at our events, they often speak on panels, they often written articles for us, and now they will help advise me with respect to programs and continue to provide content for IPWatchdog.com. We begin our conversation by asking the panel if there was anything that they heard during our AI program that was surprising. Rogitz said it was a concerning change in tone from technologist Jason Allen Snyder who in years past was pumping the breaks on worry about AI, but this year talked about it using terms like "existential threat." Mehall also picked upon predictions from the technologists panel that AI could achieve consciousness in 13 to 15 years. Meanwhile Curcio focused in on quantum computing, which seems to be the future, but is difficult to grasp and may face an uncertain patent landscape. After spending time discussing patent prosecution strategy for AI, we next turn to data protection and trade secrets, which I personally think we didn’t spend enough time on this year and plan to spend more time on next year. To jumpstart this part of our conversation I set the table by saying that not all data is created equally. There is the data that is collected and imported into AI tools and processes, and what is particularly valuable is the insights from that data, which is a different form of data itself. So, I asked: What should do companies be doing? What are the best practices for identifying and protecting valuable data in the AI age? Visit us online at IPWatchdog.com. You can also visit our channels at YouTube, LinkedIn, X, Instagram and Facebook.

    55min
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  5. Number 5: AI and the Law: How Companies Can Navigate IP Risk and Seize Opportunity

    Send us Fan Mail This week on IPWatchdog Unleashed we have a conversation with two shareholders from Wolf Greenfield. Ed Rassavage and John Strand were both speakers on our recently concluded AI 2025 program. As the program was concluding, and in front of a live studio audience, we sat down to discuss the current state of the industry from a client’s perspective. “It’s a lot of wait-and-see unfortunately,” Strand said. “The companies that have come to us for risk assessments mostly are mid-sized to larger companies that are very data heavy driven companies that are looking to use AI to enhance their data and extract value from it in some new way.” For Russavage, who is a patent attorney with 30 years of experience working in the software industry, the question for many clients relates to patent strategy, which can be extremely important given that so many AI companies are small companies, but the industry has some very large players. “We just tell folks file early file often and try to file something good. We use a lot of provisionals these days. Filing them within the matter of weeks or months not not years…So, it's it's a little bit more aggressive than it was for just typical software companies in the AI realm.” Our conversation then pivoted to trade secrets, and the role of trade secrets for AI companies given that the data and insights gained from data can be extremely valuable. From here we proceed to discuss trademarks and the problems presented by an immature industry that hasn’t yet settled on what terms are generic and how that will impact trademark selection (and retention) and whether and to what extent AI platforms will face copyright infringement liability for using training data without permission and for the outputs from generative AI tools. Visit us online at IPWatchdog.com. You can also visit our channels at YouTube, LinkedIn, X, Instagram and Facebook.

    43min
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