A Patents and Trade Secrets

At first glance, obtaining patent protection for an AI-generated invention appears straightforward; such an invention would be patentable if it meets the definition as set out by Article 27.1 of the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement and domestic legislation:

Thus, in order to qualify for protection, an invention must meet the following conditions:

• novelty – meaning it is not part of the state of the art (as defined by the relevant patent law);

• inventiveness (or non-obviousness); and

• utility (or industrial applicability) – which means, among other things, that it is capable of actually working in the real world (e.g. an invisibility cloak, similar to what one might see in Star Trek or Harry Potter, would not meet this test).

These conditions distinguish an invention from a mere discovery of, say, a naturally occurring phenomenon or equation.Footnote ¹³ Thus, discovering that a wave coming from the earth’s core that interferes with satellite broadcasts is useful, but not patentable, whereas inventing a device which filters the interference would be a patentable invention.

Inventiveness (and novelty) are judged from the standard of a person skilled in the art (i.e. the “skilled person”) standard.Footnote ¹⁴ The skilled person is a legal fiction of a person who knows everything about a particular field yet is not creative or imaginative. While the standard of the skilled person differs across jurisdictions,Footnote ¹⁵ Laddie, J. discussed the nature of the skilled (but non-inventive) person in the art in the case of Pfizer Ltd.’s patent:

AI potentially challenges the standard of inventiveness in three ways. First, many AI systems work by sifting through vast amounts of data to find patterns, which some liken to the process of discovery, which is problematic as it is generally accepted that utilizing something that already exists in nature is a “discovery”, and therefore not patentable.Footnote ¹⁷ Second, as an AI has far greater capacity to analyse vast amounts of data trained with specific data from designated fields of art than any human, such an AI not only will more easily find inventions obvious but, if taken to its logical extreme, it could not only become a skilled person but might also find all inventions obvious.Footnote ¹⁸ Third, as AI is increasingly employed in research and development (R&D), there is the potential to raise the standard of inventiveness of developers and those skilled in the art. What these potential issues mean is that in order to accommodate AI, there may have to be a re-think of the inventiveness standard – this will be difficult and lead to many unintended consequences. For example, raising the bar for inventiveness would ensure information and discoveries are not locked away but may make it harder for ordinary human inventors to acquire a patent.Footnote ¹⁹

In addition to the three standards of patentability, a patent application must also provide for sufficient disclosure of the invention to enable a skilled person to reproduce the invention.Footnote ²⁰ This is in keeping with the patent system’s other goal to promote social and technical advancement and increase public welfare through the disclosure of inventions to the public for the benefit of the public at large. AI-related issues pose a significant challenge to the system in this regard – simply stated, what does one need to disclose when dealing with an AI-generated invention? The answer is not as simple as one might think given that the outcomes of an AI invention might change depending on the input data and/or the algorithms.Footnote ²¹ Additional questions involve unique complexities and will lead to divergences of opinion, such as: must algorithms used by the AI be disclosed as part of a patent application by an AI? Should data used by the AI also be disclosed as well, and if so, how much data? Does the human expertise used to select and curate the data and train the algorithm be disclosed, and if so, to what extent? Requiring strict standards which demand inventors to supply greater detail and precise information may mean inventors simply bypass the patent system in favour of maintaining the invention as a trade secret. This in turn may not be to society’s benefit. In short, the difficulties with enablement/disclosure should not be underestimated given the potential size of the data sets involved.Footnote ²²

Finally, the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement allows (but does not require) members to create exceptions to patentability, such as inventions “necessary to protect ordre public or morality, including to protect human, animal or plant life or health or to avoid serious prejudice to the environment”,Footnote ²³ and diagnostic, therapeutic and surgical methods for the treatment of humans or animals as well as plants and animals other than micro-organisms, and essentially biological processes for the production of plants or animals other than non-biological and microbiological processes.Footnote ²⁴ While these lines may appear straightforward, the reality is not quite so simple and distinctions can be blurred.Footnote ²⁵

Compounding the issue is the fact that exceptions from patentability are defined at the regional and national level. In regard to AI, this raises issues involving software and business methods. These forms of invention are excluded from patentability in some nations, meaning that software or computer program-related inventions may be patentable in one jurisdiction but not in another.Footnote ²⁶ The result of disunity could be more forum shopping whereby organizations, inventors or creators actively seek jurisdictions whose laws are more favourably disposed to protecting their inventions or creations, in this case created or generated by AI. Moreover, this connects to the issue of broader societal benefits resulting from inventions; if AI applications or algorithms are excluded from patentability, developers and organizations would essentially have no choice but to keep such AI as a trade secret, thereby undermining the goal of the patent system to disseminate technical knowledge.

To date, applications for patent protection when the inventor is named as an AI system have been rejected. For instance, the UK Intellectual Property Office (UKIPO), European Patent Office (EPO) and US Patent and Trademark Office (USPTO) all recently denied applications for patents that named an AI, called DABUS, as the inventor in December 2019, January 2020 and April 2020, respectively. These applications, for a warning light and food container, were made on behalf of Stephen Thaler, CEO of Imagination Engines, by the Artificial Inventor Project.Footnote ²⁷ In rejecting the application, the UKIPO hearing officer decided that the UK Patents Act 1977 requires an invention by a natural person.Footnote ²⁸ The EPO likewise rejected the applications on procedural grounds as an application for a European patent must designate an inventor and “state the family name, given names and full address of the inventor”. In so holding, the EPO found this requirement was consistent with a “clear legislative understanding that the inventor is a natural person” and consistent with EPO and national decisions.Footnote ²⁹ Similarly, the USPTO held that the US patent statutes preclude interpretation of “inventor” to cover machines because “the plain reading” of words such as “whoever”, “himself”, “herself” and “individual”, as well as the requirement that an inventor executes an oath, is as a “person”. The USPTO also cited US case law which holds that inventors cannot be states or corporations.Footnote ³⁰

This leaves trade secrets as the more likely avenue for protection of AI inventions. Trade secrets protect information that is secret, of commercial value, imparted in a situation of confidentiality and subject to reasonable efforts to protect its secrecy. In some ways, trade secrets better suit the companies which develop AI as such inventions do not require registration and can last indefinitely, provided they are kept secret.Footnote ³¹ Moreover, given the fast pace of development and difficulty in reverse engineering AI systems, companies are in fact increasingly relying on trade secrets to protect investments and developments in AI. AI companies also rely on trade secrets to protect their valuable algorithms given their inability to acquire patent protection for algorithms and reluctance to disclose the algorithm in a patent application,Footnote ³² and because copyright law protects expression and not the underlying idea behind an algorithm, effectively rendering copyright unsuitable for protecting the functional aspects of algorithms.Footnote ³³

While one cannot register a trade secret – doing so would itself alert others to its presence and provide for public disclosure – there are systems in place to prove the existence of a trade secret without disclosing the secret. An example of this is WIPO Proof, which provides tamper-proof evidence of the existence of a trade secret by providing a data- and time-stamped digital fingerprint of a digital file containing the trade secret and a repository of these fingerprints (which WIPO refers to as tokens).Footnote ³⁴

B Copyright

The TRIPS Agreement (Article 9.2) states that copyright attaches to original works which are “expressions and not to ideas, procedures, methods of operation or mathematical concepts as such.” In the context of software, this makes clear that expressions are protected, whereas the underlying ideas in the software or computer programs – that is, the AI algorithms and other processes – would not be eligible for protection.

Originality (which is different from the novelty standard in patent law which requires that the invention not be part of the prior art) – the aspect of a created or invented work that makes it new or novel, and thereby distinguishes it from reproductions, clones, forgeries or derivative worksFootnote ³⁵ – remains a basic prerequisite in copyright law.Footnote ³⁶ The question in regards to our inquiry is whether an AI-generated work can be regarded as original. The Berne Convention references “authors”,Footnote ³⁷ which may not be determinative but perhaps lends itself to the conclusion that there must be a human involved in the process. Indeed, courts in several countries have interpreted originality as requiring a fairly significant degree of human ingenuity. For instance, in the famous case of Naruto v. Slater, the 9th Circuit Court in the USA held that “[t]o qualify as a work of ‘authorship’ a work must be created by a human being”.Footnote ³⁸ In that case, it was not enough for a photographer to place cameras in strategic locations and tempt the animals to pick up the camera and take pictures. Likewise, in Acohs Pty Ltd v. Ucorp Pty Ltd the Full Federal Court of Australia found that data sheets created by a computer program (a simple data-collecting mechanism) were not subject to copyright because there was not a sufficiently involved human author.Footnote ³⁹

These judgments indicate that copyright over computer programs and software will generally vest with whoever created the source code of that software. Likewise, content generated by “AI-like” software which performs functions based on programmed rules but without exhibiting true intelligence or originality, for example a “smart-home” device that can dim lights or check the weather forecast on command, would likely remain the copyright of the author of the program’s code or the person making the input. The same would likely apply for programs used as part of an artistic or technical process but which are ultimately controlled by human choices.

That being the case, while the creator of the AI program would retain copyright over original source code, that individual may have no rights to original work created by the software that they did not envision or program. Thus, for instance, while the source code of an AI program designed to create original music or generate business recommendations would be subject to copyright, the decisions and work generated by that AI may not be copyrightable if there is not a sufficient level of human input. The more distant the human involvement from the ultimate original work (as the AI continues to evolve), the less likely it would be that copyright would attach to the individual.

Whereas the US Copyright Office and others apply a “human authorship policy” that prohibits copyright protection of works that are not generated by a human author,Footnote ⁴⁰ not all jurisdictions concur with this interpretation. For instance, UK law acknowledges the possibility that works could be “computer-generated”Footnote ⁴¹ and provides that the author of a computer-generated work is deemed to be the person “by whom the arrangements necessary for the creation of the work are undertaken”.Footnote ⁴² Interestingly, China may also be heading towards protection for AI as a court decision in Guangzhou in January 2020 awarded RMB1500 in damages for infringing a financial article written by Tencent’s robot Dreamwriter without authorization: “the article’s form of expression conforms to the requirements of written work and the content showed the selection, analysis and judgment of relevant stock market information and data … the article’s structure was reasonable, the logic was clear and it had a certain originality”.Footnote ⁴³ What remains unclear in jurisdictions which hold that AI-generated work can enjoy copyright protection is, among other things, whether such protection extends to other related copyright rights such as sound recordings, broadcasts, performances or adaptations. This is an important question, but as of yet undecided and untested.

Yet another interesting question is whether copyright law ought to be used to regulate deep fakes – the generation of simulated likenesses of persons and their attributes, such as their appearance or voice.Footnote ⁴⁴ Deep fakes raise complicated copyright questions such as whether deep fakes created by information that may be copyright protected should benefit from copyright, and if they should, to whom the copyright in the deep fake should belong; and whether the person whose likenesses and performances are used in the deep fake ought to receive compensation, and if so, how this could be done.

More fundamentally, other questions involving the term of protection and liability of the copyright owner will also need to be addressed. In terms of the former, many copyright laws provide specific periods of time during which the work and the rights arising thereof are legally protected that are usually determined in reference to the lifetime of the work’s author, and exceptionally the work’s first publication or transmission. The life of the author cannot be used when AI is the author, given the theoretically indefinite lifespan of the system,Footnote ⁴⁵ but consensus has not yet emerged on the appropriate length of protection. In regards to liability, unlike an original work written by a person, some AI systems store their information in a form that cannot easily be read by humans or reverse engineered. Given this, it may be impossible to discover why a system made a particular decision or produced a particular output. In such cases, liability will likely attach to the person or entity that controls or directs the actions of the AI. This is difficult, however, and may not always be apparent where one party has created the AI and another has decided what data to put into it or what questions to ask it. In the interim, the practical reality is that business entities will need to ensure that there are contractual indemnities in place for any actions of the AI that infringe copyright work.Footnote ⁴⁶

C Intellectual Property in the Data

A thorough discussion of AI and IP cannot ignore the important issue of data, as there may be IP in the data and there certainly is IP in the systems that manage and handle data. Developers rely on vast troves of data in the initial training of AI systems as well as for personalization, product improvement or localization (i.e. adapting AI systems to work in a variety of different local conditions). Considerable resources must be spent finding suitable training data, correcting training errors or ensuring the data has not been corrupted (for example, by a cyberattack).

Yet IP protections for data are limited save for some sui generis legislation and the limited protection offered by copyright law for databases as collections.Footnote ⁴⁷ In the USA, for example, databases may be protected by copyright law not as such but as compilations which are defined as a “collection and assembling of preexisting materials or of data that are selected in such a way that the resulting work as a whole constitutes an original work of authorship”.Footnote ⁴⁸ Such protection is of limited value, however, as the US Supreme Court held that a compilation of facts is copyrightable only if the selection or arrangement “possesses at least some minimal degree of creativity”.Footnote ⁴⁹ Pre-existing materials or data included in the database therefore may be protected by copyright, or may be unprotectable facts or ideas.Footnote ⁵⁰ In contrast, Europe grants copyright protection to databases which, as such, by reason of the selection or arrangement of their contents, constitute the “author’s own intellectual creation”. However, additional sui generis protection afforded under the Database DirectiveFootnote ⁵¹ is granted to reward the substantial investment of the database maker in creating the database and prevent free-riding on somebody else’s investment in creating the database, and exists in parallel to the copyright protection on the structure of the database.Footnote ⁵²

That there is weak IP protection for data and no system of property rights raises numerous questions regarding the equity of current setups among AI companies that take freely provided data from individuals, then use this data to create products that those same individuals are charged to use.Footnote ⁵³ This situation is analogous to the one lesser-developed countries experienced decades ago when they complained that developed countries had appropriated their traditional knowledge (TK)Footnote ⁵⁴ without adequate compensation, thereby exacerbating the wealth gap between developed and developing countries.Footnote ⁵⁵ TK does not enjoy IP protection, though sui generis legislation in some countries does grant protection. But unlike the international north–south divide that characterized the TK debates decades ago, the current debate on remuneration to data providers is both international and intra-national (though the challenge now could be characterized as a struggle between the tech giants who have both the data and the technological infrastructure and those companies who do not possess such assets).

Granting property rights in the data raises a host of challenging issues, which are raised but not analysed here, including adequate compensation for use, restriction on use (and whether prevention of data transfer without compensation falls afoul of obligations undertaken in free trade agreements) and whether and the extent to which property rights in data hinder innovation. Another IP-related aspect to data worth considering is that there is IP in the form of know-how (or other trade secrets) in the use of data for AI. Because of the growing liability concerns and other issues associated with faulty AI systems,Footnote ⁵⁶ organizations employing AI systems will need to become more careful about the implementations of such systems, and will need to ensure the quality of the data used to train and update such systems to ensure that the data is appropriate for the task at hand, that it was not tampered with and that it is accurate (the last point is a problem given that the sources of data companies rely upon for, say, digital marketing may be suspect).Footnote ⁵⁷ Thus there is IP in the curation of data – to ensure the data has been validated, is appropriate for the purpose at hand and has not been tampered with – as well as IP in the creation of AI applications and deployment of AI technologies (that may be protected by IP rights or block their use by others’ IP rights). The importance of these IP-related data issues will only grow in relevance, yet current levels of protection are limited and it is uncertain whether greater levels of protection would lead to clearer outcomes or enhanced levels of innovation.

D The Profound Question

IP refers to creations of the mindFootnote ⁵⁸ used in commerce, and the IP system is designed to encourage creation and invention and reward creators and inventors through IP rights. As per Stephen Thaler’s claim that an AI is capable of autonomously creating a patentable invention (DABUS) without any human intervention, the most fundamental question which requires resolution is whether AI’s lack of corporeal existence is sufficient to deny it IP rights. This conundrum forces us to confront a related question – is the IP system, which until now has been intimately associated with the human creative and inventive spirit with its respect and reward for the encouragement of human innovation and creativity – more about advancing creative and technological progress or upholding human rights?

Dr Francis Gurry, immediate past Director General of WIPO, noted that “intellectual property is key to economic development”,Footnote ⁵⁹ and studies have shown that IP rights benefit developing as well as developed nations.Footnote ⁶⁰ There have always been developmental and commercial aspects to IP, even with the fundamental objective of the patent system being to encourage investment of human and financial resources and risk taking in generating inventions that may positively contribute to the welfare of a society, promote creations, distinguish the origin of goods and services and prevent consumer confusion.Footnote ⁶¹ Even national constitutions promote IP; for example, the American Constitution’s Patent and Copyright Clause states that “[The Congress shall have power] to promote the progress of science and useful arts, by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries”;Footnote ⁶² AI could undoubtedly increase the pace of innovation and creation.

There is potential benefit to the signalling value of protecting the IP of AI-generated creations and inventions, including that jurisdictions which permit the registration of IP rights to an AI for its inventions or creations would be seen as pro-innovation and perhaps attract more development, investment and employment opportunities. Likewise, a lack of IP protection for AI-generated inventions might discourage companies from investing in AI technologies and prevent breakthroughs in important areas like drug discovery.Footnote ⁶³

What is certain is that a lack of protection will lead to greater use of trade secrets, which could serve to further retard innovation and knowledge dissemination. While limiting the use of trade secrecy could potentially mitigate this potential problem, attempts to do so could violate obligations undertaken in free trade agreementsFootnote ⁶⁴ and would definitely meet fierce resistance by tech giants and other AI companies dependent on the protection of confidential algorithms and other information for business pursuits. Moreover, countries considering weakening trade secrecy laws would do well to remember India’s past attempt to emasculate trade secrecy – when India attempted to force Coca-Cola to release its secret recipe under its Foreign Exchange Regulation Act of 1973, Coca-Cola refused and simply left the country.Footnote ⁶⁵

But the question remains unanswered whether prioritizing innovation and creation over people is fair or wise. As AI continues to increase in sophistication, society may be unwilling to sacrifice individual rights at the altar of innovation. Industry promises to protect the rights of marginalized groups and individuals, but such promises often ultimately ring hollow as history has shown that such self-regulation can be woefully inadequate at protecting people, particularly those in marginalized communities who are frequently targeted by manipulation campaigns.Footnote ⁶⁶ Furthermore, in times of global economic crisis the priority may be coping with the significant socio-economic challenges brought about by the COVID-19 health crisis.Footnote ⁶⁷

In sum, there are countless legal, technical and policy arguments for and against ownership of IP by an AI in the areas of patents, copyrights, design rights and trade secrets, as well as questions regarding property rights in the data or whether to establish a sui generis system for original content, and posing one question in one area can generate many others elsewhere. At one level, there is no practical need to let an AI become an IP holder. After all, one could simply name a human in an application the way some companies designate their chief engineer in patent applications, even though the actual inventors were other employees; or it has been suggested that the system could treat AI as we would treat a pet, arguing that pets have intelligence and a certain level of autonomy but not legal personhood. Similarly, the AI operator legitimately controls, confines and possesses the AI during conception and thus ownership of the AI invention should be held by the AI operator, their employer (work-of-hire) or successor.Footnote ⁶⁸ While the latter approach allows for easy identification of the origin of the invention and a true entity entitled to the exclusive right, it does not suffer from problems of wrongful credibility (i.e. truthfully showing the involvement of an AI, and avoiding divisive discussions of legal personhoodFootnote ⁶⁹). This model, however, may not work or may seem unfair where human intervention is minimal.

The final challenge to address is how the question of IP rights affects business investment. Some have claimed that the USA’s more permissive software patenting regime than Europe is a primary reason why more software development took place in America.Footnote ⁷⁰ This may be overblown, as the USA did not see an outflow of investment, innovation or talent following the effective raising of standards after the US Supreme Court’s decision in Alice Corp. v. CLS Bank International, where the court avoided giving a clear definition of the expression “software patent” and held that “merely requiring generic computer implementation fails to transform [an] abstract idea into a patent-eligible invention”.Footnote ⁷¹ Similarly, the 2018 report on the impact of the Database DirectiveFootnote ⁷² made no mention of any great new flows of technological investment into the European Union as a result of the Directive.