One of the key questions in the field of exclusive rights is how the Artificial Intelligence (AI) will impact in the assessment and application of those rights.
Specially, dealing with patents and copyright works, experts wonder if AI is likely to alter some of the most fundamental pillars of exclusive rights. Think just for a moment in the fulfilment and finding of novelty and non-obviousness requirements (patent’s basic issues) or the authorship of machines or robots with respect to literary or artistic works or even performances.
Not to mention the ethical consequences of the use of AI.
How to conceptualize the AI?
The concept of AI takes us to a reality other than just a computerized routine. First thought on AI leads us to a machine that mimics cognitive functions that may be associated with human minds. Even if we go further and think of deep or advanced AI, the fact is that AI engineers irremediably work hard to evoke the human feeling and to imitate human characteristics such as love, sense of humor, wrath, mercy, sense of justice, and above all abstract reasoning.
But unavoidable is that the human behavior and the appearance of a human-a-like is achieved thanks to extreme complicated software routines and artificial nets. As a result, in many people’s view, AI is really identified with technical or technological procedures to mimic the human beings and with the computerization of code source based on previously programmed reactions, which run as specific external causes appear.
However, the question remains: can a feeling be programmed?
Can a human feeling be programmed? If so, would it not be just a technology routine (e.g. when identifying a smile in a child, the reaction must also be that of a smile)? To that question we may agree that the response of an AI to an external stimulation may be aprioristically programmed, but just as we human beings have also been previously educated.
What makes the difference between a pre-programmed mimetically response, and a spontaneous human reaction is the key question in order to upgrade the status of androids or robots and, eventually, to establish a rule of law that they also deserve rights.
The difference is an AI being programmed with a number of pre-established responses, but with the capacity of learning and deducting by itself when faced with external experiences (not to speak when faced with inner experiences, like to believe in God) not previously taken into consideration by the human programmer.
These computerization programming is being achieved nowadays (see IBM Watson or Apple’s Siri) and will be probably be standardized in the next coming decades. This is the real boundary of AI in our days.
In the end, AI is part of our lives, and in some cases even AI-based robots are like citizens (see, for instance, Deep Knowledge, which is a Japanese company naming a robot to its board of directors in 2014).
But how is AI actually impacting on IP rights?
Patents on AI. AI as an essential resource to evaluate novelty and non-obviousness patent requirements
AI is patent subject-matter. This is irrefutable. DeepMind is an example of this, a leading AI research company, which, founded in 2010, was acquired in 2014 by Google.
DeepMind has applied for several (PCT) patents.
Claims of these applications are mainly focused on neuronal nets and the achievement of a similar outcome to a rational human thinking, as well as procedures of machine learning.
Obvious to say that these PCT applications have not been granted yet, as they have not entered into the national phase. However, also unarguable is the fact that Deep Mind will not have to fight with the examiners in order to defend the novelty and non-obviousness requirement, especially if the neuronal net seems a like to the human beings’ neuronal system. This example makes us think about the perspectives of patents’ rules.
Not to forget is that machine learning systems are not always patent subject matter (at least in the EU and the US). A consistent consensus statement on this possibility should be reached by Patent’s Offices, especially when their filters of what is and what is not patentable differ.
But the fact is that some examples of AI have been patented, like the Creativity Machine developed by Stephen Thaler in 1994, which was capable of generating new ideas through artificial neural networks (US Patent No. 5,852,815, granted on May 1998), and John Koza’s invention, based on AI, which was patent granted on January 2005 (US Patent 6,847,851).
This leads us to the question of what is the subject-matter eligibility standard for AI.
US Supreme Court Alice decision doctrine has been interpreted in the sense that patent claims which subject matter could be performed through “an ordinary mental process”, “in the human mind” or by “a human using a pen and paper”, with the limited exception for claims that specifically provide procedures to achieve technological improvements over the tasks previously performed by people (e.g. containing an “inventive concept”) are to be excluded from patent claims.
And US courts have already discussed on this issue, since they have refused the patentability of AI patents on the grounds that AI patent applications are based on replication of human thinking. Similarly, see Blue Spike, LLC v. Google, Inc., stating that the intended patent application had just the purpose of covering “an abstract idea long undertaken with the human mind”, because the claims sought to model the highly effective ability of humans to identify and recognize a signal” on a computer.
Further applications of AI Patents have been granted in the field of medicine (e.g. by advising on the existence of skin tumors), as well as to help doctors in assessing right treatment to cancers. IBM Watson (AI on computer) successfully diagnosed a woman suffering from leukemia.
Also to be taken into account is the Natural Language Processing (NLP), that is, AI algorithms that enable computer to understand and process the human languages; or the Natural Language Searchs (NLS), algorithms that identify contents that matches topics and machine learning algorithms, a method of data analysis that automatizes analytical model building, by using algorithms that iteratively learn from data. Machine learning allows computers to find hidden areas of research without being explicitly programmed to do so.
An example of this is Cloem, a French company, which has applied to NLP technologies to assist patent applicants in inventing variants of patent claims. This is achieved by using NLP algorithms and text mining to artificially compose text for infinite patent claims, which cover potential thousands of new patents.
Patentability and inventorship. AI inventions-
Another topic is whether AI should be considered legally as inventor of those inventions. Should this be the case, notwithstanding that said inventions have not actually been invented by a human being?
Under current legal framework, assuming that this type of AI inventions has not been invented by the human being primarily, inventor cannot be, legally grounded, an AI being. But should the law be changed so that it recognizes AI as inventor, as the case may be? Some argue that this step forward would accelerate innovation and promote economic richness, whereas many others contend that supplanting human invention by means of autonomous intelligence could lead to the suppression of highly qualified researchers.
Assessment on Patent’s rights. Patent Offices using AI
Another field where AI is gaining importance Patent’s Offices using AI in order to assess on novelty and non-obviousness requirements.
Patent’s Offices are really facing a hard task when they have to evaluate those requirements. Not to forget is the fact of the vast increasingly information on patents’ applications and already existing patents. Some figures give us a better understanding of this titanic effort: US applications have climbed up to 10,000,000 in mid ’18. More than 100 million patent documents are related, and there are more than four billion indexed web pages needed to be examined in order to duly assess on the novelty requirement.
This overwhelming task of any Patent Office to search in previously-known state of art is even worse when we realize that approximately 60% of the patent documentation worldwide is published either in Korean, Chinese or Japanese.
Japan Patent Office has publicly announced that is looking into AI technology “to automate processes such as screening patent, trademark and desing applications”. This deployment is intended to take into action as from April 2018 up to March 2019 fiscal year.
Other Patents’ Offices (Europe, China, Korea, Japan and US) have correctly considered AI in the field of patents’ assessment as a top strategic priority.
Copyright and AI. Authorship and creativity
There are already examples of AI created works of art. Is this copyrightable even if created by an algorithm? If so, who is to be considered its author, the AI or the programmer of it?
Google has created an AI program, which is capable of writing news articles. In 2016, museums and researchers in the Netherlands unveiled a portrait entitled , an AI work of art created by a computer, which process of creation was due to the analysis of thousands of works by the 17th-century Dutch artist Rembrandt.
A short novel written by a in 2016 reached the second round of a national literary prize. And the Google-owned AI company Deep Mind has created software that can by listening to recordings.
In my view, the issue is whether or not an AI should be called author in the sense of a copyright creator of a work.
The problem is that for many legislations, authorship is essentially associated to the human condition. In addition, court’s decisions refuse the condition of author to works created by software.
On the contrary, however, some legislations recognize the authorship to the programmer, and going beyond the traditional legal frameworks (see Section 9(3) of the UK Copyright, Design and Patents Act, which states: “In the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken”. Moreover, section 178 of the same Act, which defines a computer-generated work as one that “is generated by computer in circumstances such that there is no human author of the work”.
Will the day come in which an AI will be named creator of a work?
On the limitations of AI. Rules stated by the European Parliament
One final example on the importance of AI and how this intelligence is being taken seriously by parliaments and governments, is that on February 16, 2017 the European Parliament approved a resolution with recommendations to the Commission on Civil Law Rules on Robotics (2015/2103(INL).
The European Parliament is conscious that humankind is on the threshold of an era where AI will surpass the human being’s skills and capacities, and this special moment requires to establish fundamental directives on how a future relationship between human beings and AI should be conducted.
This resolution is of a significant importance because it establishes a series of rules, in particular those governing liability and accountability which must guide the construction of AI, as well as ethical principles to be respected in the development, programming and use of robots and AI, so that this technology serves humanity and the benefits of AI is shared broadly.