Patent Office asks if artificial intelligence should be allowed to obtain patents

Whether or not an artificial intelligence (AI) ought to be granted patent rights is a timely dilemma given the increasing proliferation of AI in the workplace. AI technology has been applied effectively in medical advancements, psycho linguistics, and tourism and food preparation. Even a film written by an AI recently debuted online, and AI has sneaked into the legal profession.

In 2014, the US Copyright Office updated its Compendium of US Copyright Office Practices with, inter alia, a declaration that the Office will not register works produced by a machine, or, “mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author.”

To grant or not to grant: A human prerequisite?

One might argue that an AI is not human, therefore not a legal person, and thus not entitled to apply for, much less be granted, a patent. New Zealand’s Patents Act, for example, refers to a patent ‘applicant’ as a ‘person’. Yet this line of argument could be countered by an assertion that a legal ‘person’ need not be ‘human’, as is the case of a corporation, and there are many examples of patents assigned to corporations.

Big data models can be used to discover patterns in large data sets, but can also, as in the case of translation systems, exploit statistically significant correlations in data. None of this, however, suggests that current AI systems are capable of inventive or creative capacity.

Patentability?
This is an important consideration because, in order to get a patent, an invention must:
• Be novel in that it does not form part of the prior art
• Have an inventive step in that it not obvious to a person skilled in the art
• Be useful
and it must not fall into an excluded category that can include discoveries, presentations of information, and mental processes or rules or methods for performing a mental act.

Therefore in order to get a patent, an AI must first be capable of producing a patentable invention but, given current technology, is this even possible?
A thought exercise
Consider the following:
• You believe that as a person exercises more, he/she consumes more oxygen. You have therefor tasked your AI with analyzing the relationship between oxygen consumption and exercise.
• You provide the AI with a model suggesting that oxygen consumption increases with physical exertion, and data that shows oxygen consumption among people performing little, moderate, and heavy exercise.
• The AI reviews the data, refines the model, collects more data, and comes up with a predictive model (e.g. when a person exercises X amount, he/she consumes Y amount of oxygen, and when the person doubles his/her exertion, his oxygen consumption rate triples).

As this is essentially a statistical regression, the model will not always be completely accurate in its predictions due to differences between individuals (i.e. for some persons the model will predict oxygen consumption fairly accurately, for others its results will be far off).

If one were to feed this model data of persons who have collapsed or died during exercise (and thus, in the latter case, not consume any oxygen), would the AI be able to ‘think outside its box’ and:
• Question the cause of these data discrepancies and have the initiative to conduct further investigation?
• Note and correct the limitation in the original model (which would require a significant amendment)?
• Or would it simply alter the existing model by changing the slope of the regression line?
SMT and other AI have similar limitations. In the case of SMT, once the system is built, linguistic knowledge becomes necessary to achieve perfect translation at all grammatical levels. And SMT systems presently cannot translate cultural components of the source text into the target language. They lack creativity and provide literal, word for word translations that do not recognize idioms, slang, and terms that are not in the machine’s memory. To correct this would require a change to the underlying machine translation model, and the question arises whether this would have to be done by the human creators of the SMT, or whether the SMT itself would be able to make the necessary corrections and adjustments to the model.

Returning to the original question about patent rights for an AI: Perhaps the question we should ask is not whether an AI should be able to get a patent, but whether an AI, given current technology, can create a patentable invention in the first place. And if the answer to that question is ‘no’, then the question of granting patent rights to an AI is moot.

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