This week, Digital Future Daily is dedicating 5 days to the fast-moving landscape of generative AI and the growing conversation about how and whether to regulate it — from pop culture to China to the U.S. Congress. (Read yesterday's edition on the collision course between AI and the music industry's biggest stars here.) Alexandria, VA — Today the National Inventors Hall of Fame Museum — headquarters of the U.S. Patent and Trademark Office — was packed with lawyers, academics and corporate executives arguing about whether AI systems should patent their creations. Well, maybe not argue, exactly. This was the first of two "listening sessions" held by the USPTO to decide whether its rules governing who can patent an invention need to change to accommodate innovations made with the help of artificial intelligence. The USPTO is now firmly at the center of this emerging debate. On Monday, the U.S. Supreme Court declined to review a case that challenged existing laws about human inventorship — leaving in place an earlier ruling by the U.S. Court of Appeals for the Federal Circuit that an inventor listed on a patent must be a natural person. The case involved two patents filed by Dr. Stephen Thaler, who listed an AI system called “DABUS” as the sole inventor of a food container and an emergency light beacon. The USPTO did not grant DABUS the patents, saying only humans can receive a patent. But the open questions around AI-driven innovation have grown bigger than Thaler. And if the U.S. inventorship rules are going to change — the Patent Office will be the one to do it. And any changes to inventorship rules would trigger a chain reaction in the American innovation landscape — ideas hatched by a generative AI model, for instance, could belong in part to the AI model itself or to its creators, setting up a more complex web of intellectual property "ownership" in the future. Back at the USPTO headquarters, surrounded by examples of groundbreaking human innovation, Dr. Bijan Tadayon, CEO of Z Advanced Computing argued that even the powerful generative AI models dominating headlines this year are essentially blackbox statistical machines that don’t really understand the innovations they produce. They require human guidance to come up with something novel enough to be worth filing a patent for. Multiple speakers at today’s listening session could agree that AI systems should remain, at best, co-inventors on a patent. But Tadayon and others also noted that AI models — and the humans guiding them — are getting better, teeing up the ultimate question at the heart of the debate: When a machine conceives a new idea independently of its human creators, should it get the credit? And how would changing USPTO policies around human/AI inventorship impact the socio-economic incentives people need to keep innovating? And to be clear, machines inventing things semi-independently from humans is not just a hypothetical — it’s reality. Novartis’ JAEGAR is one example of a generative AI model coming up with novel active compounds for new antimalarial drugs. Corey Salsberg, the head of IP affairs for Novartis laid out the biopharma company’s approach to drug discovery with the help of powerful AI models. “It’s a multi-stage process,” Salsberg told me. The base AI model often comes from outside universities or companies, he said, which pharmaceutical companies like Novartis then bring in-house for customization, which means training the AI model on proprietary compound libraries. And scientists still need to screen and test whatever novel active compounds the custom AI model spits out. That’s a pretty long invention chain. And tracing human inventorship all the way up that chain under current law can be a flawed approach when trying to find out who should ultimately hold a patent. Salsberg said current law grants equal credit to all listed co-inventors — meaning that if AI model developers were listed as co-inventors, the patent process would reward the software developers who ultimately had no hand in the downstream process of creating a new drug or technology deserving a patent. Lolita Darden, one of the speakers at today’s session, called on the USPTO to mandate disclosure whenever AI systems are used in the invention process. And lobbing the ball back to the patent office, Morgan Reed, president of the App Association, recommended that USPTO patent examiners be equipped with AI tools to screen an incoming “gold rush” of AI-generated patent filings. As for how revenue from a lucrative, patented innovation should be distributed to its various inventors — whether they be human, AI, or simply humans who make powerful AI models — that would fall into the legal arena of patent licensing agreements, a USPTO spokesperson said. For now, the USPTO is listening — and if today is any indication, IP stakeholders have a lot of feelings about how the issue of AI-enabled inventorship should be handled. And some USPTO officials at the listening session said Director Kathi Vidal has the appetite to resolve the human vs. AI inventorship question this year.
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