Patent protection is the best mechanism to encourage innovation

Third, we reason that patent protection of AI-made inventions would boost efficiency in research and development, leading to more innovation in useful products and processes. The investors are encouraged by economic returns via licensing and sales from the exclusive patent rights in AI-made inventions. “[The] wealth-generating characteristics of innovation fundamentally justify a broad interpretation of patentable subject matter.” In the pharmaceutical industry, the best-selling drug Humira for treating arthritis made almost 2 billion for its patent owner in 2018. . Every time a news outlet reported that a drug may treat COVID-19, the holder of the drug patent would have an astonishing jump in its asset valuation The pharmaceutical companies desire the financial yield from patent rights to compensate for the expensive and long drug development process—the process usually cost billions and require 10–12 years before the drug is even placed on the market. The highly lucrative market and the efficiency boost by the AI technology would encourage the industry to engage in more AI strategies to make new inventions.

On the other hand, the labor theory provides that an inventor has an inherent right to the fruits of his labor and the patent right is awarded for the hard work that the inventor contributes to his creation. To develop an AI system, the substantial amount of work by AI professionals (including programmers, data suppliers, trainers, data scientists, etc.) deserves patent rights. The AI programmer drafts algorithms as the AI building block. The data supplier provides the AI system with data to learn from. The trainer teaches and corrects the AI system in the learning process. The data scientist assists data supplier and trainer to sort out data suitable for the AI function. A successful AI system may require labor from a large group of collaborative professionals and their consistent work through the lifetime of the system. We note the difference between rewarding patent rights and the designation of inventorship or ownership. Even with a grant of patent rights to the invention, the inventorship may not necessarily flow to the AI professionals if their contribution is not creative.

The patent protection of creative AI systems (including AI algorithms and AI trained models) and AI-made inventions would incentivize innovation and reward labor. Not only do we propose the new patent track model to incorporate wider scope of patent protection for AI inventions, we also recommend the following rules for the new track model.

B. Change of the POSITA Standard

The POSITA standard may not be applicable in the obviousness assessment for AI inventions under both the motivation test and the “obvious to try” analysis. The Federal Circuit has many factors to evaluate the skill level possessed by a POSITA; however, as Ryan Abbott alleges, the court may have ignored an important factor—technologies used by active workers which is highly relevant to the active workers’ skills. If the use of AI is a standard skill in the AI industry, the POSITA who is “presumed to be aware of all the pertinent prior art” according to the Federal Circuit standard should also know how to use an ordinary AI tool that is routine and by itself not creative. We propose that the POSITA standard under the AI patent track model characterize “a skilled person using an ordinary AI tool in the art”. We identify the ordinary AI tool as an AI system that has already been disclosed in the prior art and by no means cover the AI creativity machine that can invent by itself.

The previous concerns under the obviousness requirement are based on the motivation test and the “obvious-to-try” analysis in which a person skilled in the art may lack motivation to address complex problems that AI tools are good at or the person might not certainly try a seemingly unanticipated AI solution generated. The current POSITA standard might render an AI invention satisfying the nonobviousness requirement too easily just because the invention is intended to address the intricate problems in a seemingly unforeseen way. To resolve the implication of the obviousness requirement in respect to AI inventions, our proposed the POSITA standard of “a skilled person using an ordinary AI tool in the art” would help a professional understand the complexity of the AI algorithm, the versatility of the AI system, and the complication of the problem in the pending patent application. With the proper understanding of the AI invention, a skilled person could have an equitable perspective in assessing the obviousness criterion.

It is particularly appealing to enabling a POSITA to use an ordinary AI tool in evaluating AI inventions in the age of a pandemic. As an ordinary person may need time to understand the sudden predicament, an ordinary AI tool empowers a skilled artisan to extrapolate the new field quickly and efficiently. The patent examination demands such adaption to better effectuate the finding of fresh solutions during the coronavirus crisis and for future unpredictable situations.

C. Expedited Patent Examination

The time it takes to acquire a patent is crucial in the COVID-19 urgency. In light of the temporal constraints of the patent system, the long wait period for patent examination may discourage organizations from investing in researching a cure for the virus. By the time a COVID-19 drug patent is granted, a pharmaceutical company may have already missed the peak in demand for the drug and therefore may not be able to reap the highest rewards. On May 8, 2020, the USPTO announced a COVID-19 Prioritized Examination Pilot Program that endeavors to speed up the deposition of COVID-19 patent application. However, the effect of the pilot program can only be limited, since merely a small portion of patent applicants—small or micro entity status filing for product or process claims subject to FDA approval— can participate in the pilot program. Neither does it solve the delay problem of patenting posed to large entities such as the “Big Pharma” companies that have the most resources to develop the COVID-19 cures, nor would it promote many patent matters that do not require FDA approval such as disease forecasting or tracking.

Above we discussed the post hoc bias arising from the lengthy review time for patent applications and that is why we argue for an expedited patent examination for AI inventions. Not only does the expedition address the hindsight problem, but it also aims to avoid administrative backlogs that the patent office may encounter. “The AI boom is happening all over the world and it’s accelerating quickly.” In 2017, there were over 10,000 AI related publications and over 130,000 AI patent families in U.S. If not examined in a fast fashion, the AI patent applications may pile up quickly. The lapse of time during examination may also allow competitors to grow, and by the time of patent’s grant, the technology may not be so advanced or useful as it was previously.

Even though the USPTO has a prioritized patent examination program (Track One), the program charges a high fee and is not specific to any type of technology. In contrast, Singapore recently launched the Accelerated Initiative for Artificial Intelligence (AI2), a fast track specific for AI related patent applications that are firstly filed in Singapore. AI2 is expected to grant an AI patent in a fast as 6 months. We urge the USPTO to set up a new patent track model specific for AI inventions. If such an expedited track model is not adopted, the U.S. risks the outward flow of investment and innovation to other countries, where the patent systems that are more favorable to AI patents.

D. Use of AI for Patent Examination

We advise the use of AI tools for patent examination to review the difficult algorithms and vast amounts of data which may be overwhelming for humans to handle, as the AI tools would boost efficiency and accelerate the patent examination process. The USPTO has already been using the AI system Unity to increase the efficiency of patent examination. The application of Unity seems limited to searching patents, publications, and images, rather than examining patents. In a crisis like the coronavirus pandemic, AI systems could curate the prior art fast and efficiently and they could also analyze the creativity of the patent application from continuously updated databases and circumstantial information. Similar to the way AI systems help the pharmaceutical industry screen drug candidates, AI systems would likewise assist the patent examiners filter away unpatentable applications so as to lighten the workload for human examination.

A legal idealist would desire the perspective of the patent examiner identical to that of a POSITA given that a POSITA’s viewpoint is the golden standard in evaluating whether a pending patent application is patentable. In a realistic way, the human examiners’ opinions can only be, at the best, as close as possible to the POSITA standard. In line with our proposed POSITA standard of “a skilled person using an ordinary AI tool in the art”, patent examiners’ use of AI tools for examination helps maintain their perspective in consistency with the standpoint of a POSITA. The AI tools for patent examination would help evaluate the patentability of AI inventions based on an enhanced understanding of the relevant field and the pending AI patent application.

E. Shortened Patent Lifetime

“In the AI industry, the invention process as well as product life cycles can sometimes be extremely short.” AI patents may not need 20 years lifetime like utility patents. We plead to shorten the patent lifetime for AI patents which would allow the technology to come to the public domain faster for the benefit of knowledge dissemination. We do not agree with a complete suspension of patent rights because it would “throw a wet blanket” over the passion to develop new AI solutions. One may argue that to shorten patent lifetime would deter the effort of AI research and development. We contend that shorten the patent lifetime should still cover the most favorable time to exclusively make, sell, use, and import the invention. Though pharmaceutical companies hope to have their drugs under patent protection for as long as possible, a coronavirus drug, for example, may not need a full span of 20 years for exclusive patent rights on the grounds that the virus may evolve, the drug formula may be upgraded, and other drugs from competitors may be introduced to the market. The privilege of the pharmaceutical industry needs to be balanced with the interests of low-income patients who benefit from cheaper generic drugs that can only be introduced into the market after the expiration of patents allowing.

F. Depository Requirement for the AI Working Models

To solve the “blackbox” conundrum of AI technology which implicates issues with the written description, enablement, novelty, and utility requirements, we propose a depository rule for the AI working models. The deposition requirement has been around for a long time specifically for the patent application involving microorganisms. When an invention involves a microorganism, it is usually impossible to clearly and sufficiently desalinate the structure or component of the matters such as bacteria, yeast, fungi, or viruses. In response to the difficulty in describing living organism, in 1977 World Intellectual Property Organization (WIPO) enacted the Budapest Treaty to codify the depository principle for microorganisms. Each of the state parties agreeing to the Budapest Treaty, including the U.S., is obliged to adopt the deposition rule for microorganisms as part of the patent procedure of that country or region. During patent application, the applicants are expected to mail a sample of microorganisms to the patent office as a record in the office’s sample library.

In analogy to microorganisms, we urge a depository rule for AI systems, which encounter the same difficulty of being inexplicable. The depository AI model may include key components of the AI systems such as codes, data, and output results via a digital submission to the patent office. The deposited AI models could be used as a showcase to illustrate the AI subject matters, and to answer how does the AI system work, how to make and use the AI tools as claimed in the patent application, or what does the components of the AI tools stand for. The demonstration of AI models would address the problem of insufficient description that implicates many patentability criteria including written description, enablement, novelty, and utility requirements; the deposition may also serve as potential evidence in the later infringement case.

Below some potential challenges of the new AI patent track model are laid out and rebutted. First, some may assert that AI patents may prevent the later comers to use the patented technology. For example, since the AI algorithm is fundamental to AI systems, an AI algorithm patent would preempt subsequent applications arising from that algorithm. We reason that the patent right is not equal to the monopoly in the antitrust sense. Indeed, the patent reflects a balance between the need to encourage innovation and the avoidance of monopolies. The demand of incentives to promote new technology may be prioritized in some circumstances, like during the current health crisis when people are dying every day because no approved efficient drugs or vaccine are available.

Patenting AI inventions does not prevent the patent owners from licensing out their advanced technology. The licensees could enjoy the granted privilege to create a subsequent work, e.g., application of the AI creativity system to generate a resulting new invention. The license could be accommodated to the public interests depending on how urgent and essential is the purported use. Recently, some politicians from around the world call for the compulsory patent licensing relating to coronavirus vaccines and treatments in consideration of patent rights that might prevent affordable access to potential cures. Most European countries, India, and Canada have already evoked compulsory licensing under which the governments may authorize themselves or third parties to use a patent without the permission of the patent owner. However, in U.S. there is no general right to force compulsory licensing. The “march-in rights” under the Bayh-Dole Act of 1980 may at most compel licensing of a federally-funded patent rather than a drug or vaccine patent developed by a “Big Pharma”. The best bet in U.S. to use a pharmaceutical company’s patent is still through the consent of the patent owner. In view of the priority of ensuring access to life-saving medicines during pandemic, pharmaceutical companies may be willing to compromise their patent rights temporarily. For example, Gilead owns the patent of the potential coronavirus drug remdesivir and its CEO announced that at the time of crisis “the patent is not at the forefront of our mind” and “[w]e will not get into a patent dispute” even considering that China’s Wuhan Institute of Virology filed a new patent application to use Gilead’s potential coronavirus cure. Gilead emphasized that “it is too early to discuss any compulsory or other types of licensing at this stage” and its priority now is to examine the drug efficacy in clinical trials and to later ramp up the product after confirmed clinical results.

The open source advocate who support the complete elimination of patent rights may allege that patent protection of proprietary information limits the accessibility of knowledge. Despite the current call for harmonized research effort from governments, academic institutions, and industry to develop COVID-19 vaccine, the unwillingness to share patentable information may prevent the collaboration. We argue that patent owners regularly work together under the confidentiality agreement and the open source model provides no incentive for the profit-driven patent owners, e.g. pharmaceutical companies, to develop cures.

Some may question whether patent rights do induce the inventive effort since scientists may work for sense of achievement or personal glory not necessarily in pursuit of economic returns. The degree of the inducement for invention by patent rights varies by fields. An empirical study shows that the manufacturing industry would still have chosen to develop most of their products even if the companies had known the products are not patentable.156 However, executives in the pharmaceutical industry reported without patent protection 60% of the new pharmaceuticals would not have been developed. The pharmaceutical companies may indeed require the patent incentives to induce the research and development activities.

Other kinds of IP rights, such as copyright or trade secrets, may be raised as alternative to patent in the AI context. We contend that the patent right provides much more incentive to innovate for the AI professionals and investors than the alternatives. While the copyright prevents the competitors from copying the codes, the patent right grants a right to bar competitors entirely from the market.158 Trade secrets, on the other hand, do not provide incentive to innovate, nor do they encourage the dissemination of knowledge as the patent disclosure offers upon the expiration of rights. As the patent right is more exclusive, encompassing, and transparent, it is thus more incentivizing to innovation.

The employment worry may emerge that the incentive offered to the AI industry in the form of patent rights would threaten the human workforce.159 A study published by McKinsey Global Institute suggests that up to 800 million jobs around the world could be under threat from automation in the next 12 years.160 We note that the automation, necessitated by the industrial development, is inevitable even without AI. The exponential growth rate of computer performance indicated by Moore’s law has been continuously accelerating the industrialization speed even before the birth of AI and such trend would keep eliminating human workers who are conducting only routine repetitive work. Indeed, the job market created by AI cannot be ignored. The work force may adapt to the expanding AI industry as the McKinsey study indicates “when some tasks are automated, employment in those occupations may not decline but rather workers may perform new tasks” by switching occupations or upgrading skills to accommodate the job market.161 The employer demand for AI-related role has more than doubled from 2015–2018.162 It is expected that from 2018 to 2022, AI would create 58 million new jobs around the world.163

In the coronavirus pandemic, there is concern that granting a 20-year patent monopoly to a coronavirus drug would boost price gouging and hinder the iterative innovation by a second comer who later develops a similar drug. We contend that stripping patent rights from a pharmaceutical company would deprive the incentives and make it almost impossible to recoup the decade-long cost in drug research and development. Further, without patent benefits, the scientists and researchers may feel insufficiently rewarded for their fruits of productive labor. We notice a patent maximalist’ view in support of an extension of patent term for coronavirus cures beyond the current norm of 20 years, yet we do not agree with the elongated patent term—under our proposed AI-specific patent track model, we summon a shorted patent lifetime to balance the incentive with the concern of exclusive rights. In the coronavirus climate, Senator Ben Sasse’ takes a compromised position to support patent incentives. In his recent bill Facilitating Innovation to Fight Coronavirus Act, the Senator suggests a delay of patent rights during the pandemic and offered, as compensation for the delay, an extension of a patent term by 10 years. This legislation may address the current urgency to provide a cure and meanwhile offers a longer time of patent protection to incentivize future to lever for innovations.