Posts Tagged: "artificial intelligence"

Earlier this year, the World Intellectual Property Organization (WIPO) received hundreds of submissions commenting on the Draft Issues Paper on Intellectual Property Policy and Artificial Intelligence. Contemporaneously, the notable DABUS cases were rejected by the EPO, UKIPO, and USPTO on the ground that AI cannot be named as inventor. The uncertainty in the ownership/inventorship of AI technology could impede investment and development of AI technology. This article aims to look into the WIPO submissions and arguments for addressing AI inventorship. Considering balancing the incentive of fostering AI technology and genuine inventorship, this article suggests seeing AI as a tool, or a pet, and that requiring the applicant to disclose any AI technology involved is the better resting place.

For the past 60 years, scientists have been able to utilize artificial intelligence (AI), machine learning, and other technological advances to “promote the general science …”. U.S. courts have increasingly come under pressure to not only allow AI-directed applications as patentable subject matter, but also from a small yet determined and growing contingency of IP professionals, to recognize the AIs themselves as the inventors. The EPO recently handed down guidance that AI could not be recognized as inventors on patent applications. The purpose of this piece is not to debate the merits of whether or not AI should be given inventor status on applications which, it has been argued, they are rightly due—nor should it be. It is important, however, to peek beyond the looking glass into a future where AI are given status in the United States that has, as of the writing of this piece, been reserved for human beings. Let’s explore a few main issues.

Technology innovation in artificial intelligence (AI) is accelerating at a breakneck pace, and the ability to innovate, adopt and integrate AI techniques to evolve business models will separate those businesses that recover from the COVID-19 pandemic from those that will fail. Four artificial intelligence technologies are poised to lead the global economy out of the pandemic-induced recession. Applications for these technologies across verticals abound. Smart strategic and financial investors are scouring the market for new ways to digitally disrupt established businesses. Throughout the COVID-19 pandemic, the importance of sharing critical information across countries about the spread of coronavirus has been emphasized. However, much remains unsaid about how COVID-19 could have been managed more efficiently by using advanced data technologies that have transformed businesses. Here are four areas where AI could change the face of the post-COVID economy

Last week, the United States Patent and Trademark Office (USPTO) issued a decision refusing to vacate a Notice of Missing Parts in U.S. Patent Application No.: 16/524,350 (the ‘350 Application), titled “Devices and Methods for Attracting Enhanced Attention”, for failure to “identify each inventor by his or her legal name” on the Application Data Sheet (ADS). The ADS listed a single inventor with the given name DABUS and the family name as “Invention generated by artificial intelligence.” DABUS stands for “Device for the Autonomous Bootstrapping of Unified Sentience”. The Application listed Stephen L. Thaler as the Assignee, Applicant and the Legal Representative. The USPTO denied the petition to vacate the Notice of Missing Parts.

Part I of this article provided an overview of the Federal Circuit’s understanding of the patent venue statute after the Supreme Court’s decision in TC Heartland, and especially the meaning of In re: Google LLC, 949 F.3 1338 (Fed. Cir. 2020) (“SIT”) in this analysis. Part II of the article will address the impact that “machines” may be considered a factor in the analysis of whether venue in a patent infringement can be asserted in a particular location, as raised by the court in Personalized Media Communications LLC v. Google, Netflix, 2:19-CV-00090-JRG (Lead Case). As more and more companies move at least part of their operations online, especially now in response to the COVID-19 crisis, companies, as part of this process, should consider whether this will increase the chances that they will be sued in a district that they regard as unfavorable.

Patent applications filed at the European Patent Office (EPO) rose 4% to 181,406 in 2019, driven by substantial increases from Chinese, Korean and U.S. applicants, according to a report published by the Office yesterday. The United States was the number one country of residence of applicants, with 46,201 applications—a rise of 5.5%. This accounted for 25% of all European patent applications. The U.S. was followed by Germany and Japan. Applications from the People’s Republic of China increased by 29.2% to 12,247 putting the country in fourth place, while those from the Republic of Korea grew by 14.1%.

Twenty-two member states of the World Intellectual Property Organization (WIPO), more than 100 organizations, and over 100 individuals have submitted comments and suggestions in response to WIPO’s Draft Issues Paper on IP Policy and AI. The submissions have been posted in the form and in the languages in which they were received on WIPO’s website. The comments will feed into a revised issues paper for discussion at the second session of the WIPO Conversation on IP and AI, which takes place in Geneva in May 2020.

The European Commission is seeking feedback on its new strategy for data and has also launched a public consultation on a White Paper on Artificial Intelligence. Both measures were announced yesterday (February 19) by Commission President Ursula von der Leyen; Executive Vice-President for A Europe Fit for the Digital Age Margrethe Vestager; and Commissioner for Internal Market Thierry Breton.

Earlier this month, the U.S. Copyright Office and the World Intellectual Property Organization (WIPO) held a joint event titled, “Copyright in the Age of Artificial Intelligence” (AI) at the Library of Congress in Washington, DC. The event explored how global copyright law and intellectual property law, as well as broader policy, may currently address AI technology, and included dialogue about changes that may be needed. Panelists also shared how AI is being utilized now and what future technology deployment and innovation may look like. The event was part of a series of conversations organized by the U.S, Copyright Office and WIPO both in the United States and Europe, with the next conversation scheduled for May 11 and 12 in Geneva, Switzerland. The summit illustrated that AI presents unique opportunities for innovation, assuming intellectual property rights are respected, but questions remain in several areas, including whether machine learning is producing “original” work and whether the product of such software is inherently reproductive, derivative or the result of a system or process devoid of human action.

Much has been written about how artificial intelligence (AI) and machine learning (ML) are about to transform the global productivity, working patterns and lifestyles and create enormous wealth. Gartner projects that by 2021, AI augmentation will create $2.9 trillion of business value and $6.2 billion hours of worker productivity globally. McKinsey forecasts AI potentially could deliver additional economic output of around $13 trillion by 2030, boosting global GDP by about 1.2 percent a year. Companies around the globe are all racing to adopt and innovate AI and ML technologies. Indeed, by any account, much progress has been made and the adoption and innovation rates are quickening. But who is winning or leading in the race? A quick review of U.S. patent data may provide a glimpse into the state of the race.

Earlier this month, the European Patent Office (EPO) and the UK Intellectual Property Office (UKIPO) each rejected two patent applications that designated an artificial intelligence named DABUS as the inventor. While the UKIPO published a decision setting out its reasoning, the EPO simply stated at the time that the applications did “not meet the requirement of the European Patent Convention (EPC) that an inventor designated in the application has to be a human being, not a machine.” Now, the EPO has released more detail about the grounds for its decision. In the EPO press release today, the Office explained: “The EPO considered that the interpretation of the legal framework of the European patent system leads to the conclusion that the inventor designated in a European patent must be a natural person. The Office further noted that the understanding of the term inventor as referring to a natural person appears to be an internationally applicable standard, and that various national courts have issued decisions to this effect.”

When discussing patentable inventions with data scientists, I often hear them dismiss their inventions under arguments such as these: “We’re using the same tools as everyone else,” “Augmenting data for the training set is well known,” “A similar thing has been done for car-bumper design” (said by the designer of a churro-making machine), “Configuring the neural-network hyperparameters is trivial,” and worst of all, “It’s obvious.” Data scientists often believe that their accomplishments are not patentable, but in-depth exploration of their work often uncovers patentable ideas. I am referring to data scientists that use machine-learning (ML) tools to uncover intrinsic relationships within a large corpus of data. Other data scientists design and improve these ML tools, and their work may also result in patentable ideas, which is a topic for discussing another day.

The European Patent Office has refused two European patent applications that designated an artificial intelligence called DABUS as the inventor, following a non-public hearing on November 25, 2019. The applications are for a “food container” (number EP3564144) and “devices and methods for attracting enhanced attention” (number EP3563896). They were filed by the Artificial Inventor Project, which has so far filed patent applications for the inventions via the Patent Cooperation Treaty (PCT) in the United States, United Kingdom, Germany, Israel, China, Korea and Taiwan.

Contemporary AI technology of the kind one has increasingly heard about in recent years is based on machine learning and deep learning methodologies. These use large amounts of computing power to crunch thousands of sample input-output pairs to train adaptable data structure models. Eventually, they are able to produce their own correct outputs when presented with an nth + 1 input. These can be thought of as questions and answers. If an AI model is given, say, 10,000 sample questions with correct answers, it will be able to correctly answer the 10,001st question by itself. Once trained, computing requirements are low. Due to the nature of the methodology, AI is appropriate for situations that involve repetitive decision-making processes. For one thing, many existing examples of correct decisions must be available during the training. Further, after the training phase, a system is applied to similar situations over and over again. Because of this, the application space for AI is sometimes overblown. However, once understood, this limitation usefully directs our attention to instances of decision-making that can be automated or made more efficient using AI. If we consider patent portfolio management in terms of constituent decision-making processes, we might be able to identify which of them are appropriate for the application of AI.

This week in Washington, D.C., the Senate Subcommittee on Intellectual Property holds a hearing to look at ways to reduce the number of fraudulent trademark application filings that have been making their way to the U.S. Patent and Trademark Office. Other Senate committee hearings will focus on legislative proposals to protect consumer data privacy and promote the availability of wireless spectrum for 5G networks. Over in the House of Representatives, the Artificial Intelligence Task Force will convene a hearing to look into concerns related to the use of artificial intelligence technologies in the financial services industry. Elsewhere in D.C., both The Brookings Institution and the Information Technology and Innovation Foundation will host events discussing the use of facial recognition technology in the public and private sectors.