Posts Tagged: "artificial intelligence"

The past few years saw a meteoric rise of artificial intelligence (AI) products, services, and applications. AI has evolved from merely a buzzword or a cool new idea to a substantively used tool in a variety of applications, including autonomous driving, natural language processing, drug development, finance and cybersecurity among others. Companies, universities, and inventors world-wide noted the importance of AI and began seeking to patent various aspects of AI technology. Until 2018, these patent applications identified a human inventor who invented a particular aspect of the AI technology. Then, Dr. Stephen Thaler filed a patent application for a food container and a light emitting device that identified an AI, known as DABUS, as an inventor.

With the forecasted growth of global Artificial Intelligence (AI) market size, it is evident that AI is quickly becoming the solution to most software and service needs. AI has even infiltrated our homes—for example, we are increasingly seeing smart home systems that incorporate Internet of Things (IoT) technology along with a master AI virtual assistant. Undoubtedly, the technology has made space in the intellectual property-based service sector as well. For instance, to support patent searching, there are quite a few AI-based automated patent search tools available. Although many of these are still in their training stage, these tools are likely to mature. Thereafter, the question looming over innovators is whether to take advantage of affordable AI patent search tools or invest in outsourced manual patentability searches.

The England and Wales Court of Appeal has upheld lower rulings that two patent applications designating an artificial intelligence called DABUS as the inventor were deemed to be withdrawn. (Thaler v Comptroller General of Patents Trade Marks And Designs [2021] EWCA Civ 1374.) However, the three judges were split, with the two patent specialists on the panel taking different views. Dr. Stephen Thaler filed two UK patent applications in October and November 2018 for a “Food Container” and “Devices And Methods For Attracting Enhanced Attention” respectively. Parallel applications have been filed in many other jurisdictions, as reported previously by IPWatchdog.

On August 16, the National Highway Traffic Safety Administration (NHTSA) announced that it had opened a probe into Tesla’s driver-assistance technologies after it identified 11 crashes since 2018 in which a Tesla vehicle had struck an emergency-response vehicle. All Tesla vehicles involved had been using the automaker’s Autopilot feature at the time of the crashes, which enables the vehicles to steer, accelerate, and brake automatically. The crashes have attracted the scrutiny of lawmakers and regulators of Autopilot and similar technologies. With increased attention being paid to AV safety, AV companies are shifting their research and development and IP strategies toward technologies designed to address consumers’ real-world safety concerns.

On September 2, the U.S. District Court for the Eastern District of Virginia issued a decision granting a Motion for Summary Judgment for the United States Patent and Trademark Office (USPTO) and upholding the Office’s view that AI algorithms cannot be listed as inventors on U.S. patents. The court pointed to the Administrative Procedures Act’s (APA’s) strong deference to final agency decisions, barring any egregious errors. DABUS generated outputs corresponding to (1) a fractal design for food container surfaces that may help prevent stacked containers from sticking together and (2) a technique for controlling the timing of flashing warning lights to help attract attention. Dr. Stephen Thaler (DABUS’s creator and owner) filed patent applications on these inventions that were filed around the world, listing Thaler as the applicant and listing only DABUS as the inventor.

Artificial Intelligence (AI) is the latest buzzword across all sectors. Every tech and non-tech company is vigorously filing, strategizing or planning to enter the AI patent domain. However, the journey is not as easy as it may seem. While drafting AI-based patent applications, drafters often face challenges in formulating the right strategy for writing claims and identifying the correct scope of the application. Thus, it’s important to know the challenges in detail and to develop practical solutions for drafting a patent-worthy application.

With South Africa’s patent office having recently granted the first patent to an AI inventor, and an Australian court ruling in favor of AI inventorship, it’s time to review how we got here—and where we’re going. The number of artificial intelligence (AI) patent applications received annually by the United States Patent and Trademark Office (USPTO) grew from 30,000 in 2002 to more than 60,000 in 2018. Further, the USPTO has issued thousands of inventions that utilize AI. According to a 2020 study titled “AI Trends Based on the Patents Granted by the USPTO”, the total number of AI-related patents granted by the USPTO per year increased from 4,598 in 2008 to 20,639 in 2018. If AI-related patent applications and grants are on the uptick, what was the problem with DABUS?

In response to articles on implementing AI into our patent system, and specifically to the suggestion that we should consider developing AI to replace some aspects of human decision making in the patent space, we have received a number of comments and even objections to the idea. A common objection: it is likely impossible and impractical for us to advance AI to the point where it can make reliable subjective decisions (e.g., infringement and obviousness), let alone reliably replace human decision making. At the outset, we challenge the presumption of this argument.  

The Federal Court of Australia on Friday ruled in Thaler v Commissioner of Patents [2021] FCA 879 that an artificial intelligence (AI) system can be an inventor under the Australian Patents Act. The Honorable Justice Beach, in a very thorough judgment, set aside the decision of the Deputy Commissioner of Patents that patent application no. 2019363177 did not comply with reg 3.2C(2)(aa) of the Patents Regulations 1991 (Cth), which “requires that the applicant, who in this case is Dr Stephen Thaler, must provide the name of the inventor of the invention to which the application relates.” The Deputy Commissioner of Patents said that Thaler could not name an inventor because an AI simply cannot be an inventor under the Act. But Justice Beach said “that position confuses the question of ownership and control of a patentable invention including who can be a patentee, on the one hand, with the question of who can be an inventor, on the other hand.”

Twenty years ago, the U.S. Supreme Court ruled for the first time that plants could be protected with utility patents. J.E.M. Ag Supply, Inc., v. Pioneer Hi-Bred International, Inc. 534 U.S. 124 (2001). Forty-one years ago, the U.S. Supreme Court ruled for the first time that living organisms were patentable. Diamond v. Chakrabarty, 447 U.S. 303 (19080). Before these landmark cases, plants and living matter were not protectable with patents. The rationale of the Supreme Court in J.E.M. and Chakrabarty supports patent protection for inventions by non-humans, i.e., artificial intelligence inventors.

South Africa’s patent office has granted the first patent for an invention conceived by an artificial intelligence (AI) inventor, DABUS. The country does not have a substantive patent examination system, and thus the significance of the grant may not be as great as it would be in other jurisdictions—but the DABUS team is celebrating. The patent is for “a food container based on fractal geometry,” and was accepted by South Africa’s Companies and Intellectual Property Commission on June 24. The notice of issuance was published in the July 2021 Patent Journal.   

Artificial intelligence (AI) is everywhere, touching nearly every aspect of our daily lives, including how we work, communicate, shop, travel and more. The term “AI” is generally understood to encompass computerized systems that perform tasks ordinarily perceived as requiring some form of human intelligence. Many AI-based systems are able to recognize trends, patterns and connections, test hypotheses using available data sets, and continuously improve decision trees based on user input. As such, AI has been shown to have near endless applications, driving a surge of inventions and related patent application filings.

One of the major challenges when licensing, transacting, or managing Standard Essential Patents (SEPs) is that there is no public database that provides information about verified SEPs. Standard-setting organizations (SSOs) such as ETSI (4G / 5G), IEEE (Wi-Fi), or ITUT (HEVC/VVC) maintain databases of so-called self-declared patents to document the fair, reasonable and non-discriminatory (FRAND) obligation. However, SSOs do not determine whether any of the declared patents are essential, nor are the declarants required to provide any proof or updates. As a result, in the course of licensing negotiations, patent acquisitions, or litigation, the question about which patents are essential and which are not is one of the most debated when negotiating SEP portfolio value, royalties, or infringement claims. Artificial Intelligence (AI) solutions have started to support the process of understanding how patent claims relate to standards to assess larger SEP portfolios without spending weeks and months and significant dollars on manual reviews by technical subject matter experts and counsel.

Historically an esoteric area of law, in recent years, antitrust policy is drawing broader attention as a tool to curb the exercise of monopolistic market power, especially by big tech behemoths. Congressional reports on both Democratic and Republican sides of the aisle, multiple legislative initiatives to reform U.S. antitrust law, and a recent book by Senator Amy Klobuchar (D-MN), Chair of the Senate Judiciary Subcommittee on Competition Policy, Antitrust, and Consumer Rights, are some indicators of this trend. Along these lines, broad outcry broke out against rumored Department of Justice (DOJ) Antitrust Division leadership appointments of candidates representing big tech interests, such as Karen Dunn (Apple, Amazon), Renata Hesse (Google, Amazon), Susan Davies (Facebook), and against Deputy Attorney General Lisa Monaco’s (Apple, Google) involvement in deliberations over the nomination of a DOJ Assistant Attorney General (AAG) for Antitrust.

In response to our recent article on artificial intelligence (AI) reducing transactional costs to help determine infringement and invalidity determinations, a commenter made an interesting counterpoint, paraphrased as the following: AI provides useful tools that should be used as an aid to human thinkers, not as a replacement to human thinking. Moreover, when it comes to AI making subjective determinations, such as obviousness or novelty, we should be skeptical of relying on AI, either legally or practically. We appreciate the counterpoint and we wanted to address it in this follow-up article.