The Case for Patenting AI: U.S. Patent Laws Better Get Smart or Get Left Behind

“We might never get to [patenting] advanced machines if we do not patent machine learning processes.” idea of patented inventions brings to mind machines fully realized – flying contraptions and engines with gears and pistons operating in coherent symphony. When it comes to artificial intelligence (AI), there are no contraptions, no gears, no pistons, and in a lot of cases, no machines. AI inventors sound much more like philosophers theorizing about machines, rather than mechanics describing a machine. They use phrases like “predictive model” and “complexity module” that evoke little to no imagery or association with practical life whatsoever. The AI inventor’s ways are antithetical to the principles of patent writing, where inventions are described in terms of what does what, why, how, and how often.

But our patent laws were written for machines and widgets, not this predictive model stuff. It is hard to patent AI because AI is not a machine – it is a brain for a machine. And the brain needs to learn, to become educated before it can be usefully applied to a machine. Those machine philosophers who design AI? They are teaching the brain. It’s clear that the U.S. Supreme Court does not want us to teach that brain. Machine brains do not exist in their eyes, only machines.

American Innovation is Being Left Behind

The rest of the world sees things differently. Unfettered by similar legal constraints, China is forging ahead in the AI development sphere, crafting examination guidelines specifically for big data processing and mathematical formulas, the tools for which to build advanced machine learning and deep learning capabilities. Europe requires only a technical purpose for patentability of computer-implemented inventions, rather than a technical improvement.

In the United States, big data processing and mathematical formulas are practically per se non-patentable subject matter, being considered abstract ideas lacking technical improvements necessary to overcome the Alice 2A/2B analysis. Technical improvements require improvements to the way the machine functions, which is the standard at both the United States Patent and Trademark Office (USPTO) and the U.S. Court of Appeals for the Federal Circuit.

The problem is that almost all machine learning and deep learning inventions will be considered not patentable under our current laws because machine learning cannot survive the current technical improvement analysis. In the field of radiology, advanced image processing that can detect early onset cancer from ultrasounds depends on vast amounts of datasets of images being fed to a machine for processing – datasets accounting for age, ethnicity, body type, and a myriad of confounding factors that can affect the image. Eventually, the machine will become smart enough to account for all the confounding factors and be able to identify critical issues for the healthcare provider. For autonomous vehicles, in order to have an autonomous vehicle brain that will not drive you into a ball pit, the AI inventor needs to teach the brain everything—literally every road condition for every navigation scenario possible. Advanced AI capable of predictive and decision-making capabilities is built using big data processing (which relies on cloud computing) and mathematical formulas (coding). We need cloud computing and coding to build advanced neural networks. The courts consider all of these processes as implementing only a generic computer to act in a conventional way.

The problem is that our lawmakers are assuming that denying the patenting process to the machine learning phase is not equivalent to cutting off innovation in machine execution. There seems to be some notion that we can bypass the big data processing and mathematical formulas stage, but once we get to the good machines – those really smart ones that can find cancer – well, we can patent those.

That assumption is flawed because we might never get to the smart machines for the following reasons:

1) The commercialization problem: Effective machine learning modules need to be implemented into commercialized products in order to be viable. In the autonomous vehicle case, AI machine learning modules need to be implemented in existing non-autonomous vehicles first. We cannot expect to have a programmer feed scenarios to the autonomous vehicle brain and expect that brain to be any good. The brain needs to encounter the unquantifiable real-world scenarios of road navigation in order for it to safely direct the vehicle to make that left turn at the next light.

It’s no secret that companies are in competition with one another, and they do not want to disclose their inventions through commercial use just for it to be pawned off by their competitors, especially inventions that will require years of research and development investment like building a smart self-driving machine. Subject matter eligibility denial discourages these types of investments and further downstream investments.

2) The joint collaboration problem: Radiologists do not code! Even if they do, they’re probably bad and incredibly   expensive. But radiologists understand imaging. When radiologists collaborate with programmers and coders, together they can build machine learning modules for digitally labeling vast amounts of imaging data that is needed to develop advanced imaging AI in healthcare. We need joint collaborations between members of different technological sectors in order to build and implement AI across different sectors. These joint collaborators want to preemptively establish the ownership of their outputs. Our subject matter eligibility laws can discourage joint collaborations by inserting a blind spot in these deals.

We might never get to advanced machines if we do not patent machine learning processes. We are witnessing the advent of the Fourth Revolution’s greatest enabling technology in AI, which will impact all the great technological spheres from cleantech to advanced telecommunications. Yet even now, the Supreme Court refuses to rectify the deficiencies in U.S. law with American Axle. The Supreme Court has made it clear that they do not intend to change course with respect to their views on American innovation policy. Unless Congress takes leadership, we in the United States should prepare ourselves to become the land where imagination and machine philosophy remain just that – mere ideas.


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Join the Discussion

16 comments so far.

  • [Avatar for Anon]
    July 20, 2022 10:22 am

    This thread may be a better fit for a link to the final (detailed) decision on DABUS in the UK:

  • [Avatar for Anon]
    July 15, 2022 09:50 am

    Mr. DeLassus continues his religious crusade against accepting that Innovation laws as being Sovereign-centric.

    Here, he wants to purposefully confuse the fact that there well may be other variables to be concerned with in an attempt to nullify the plain fact that advances in particular to aspects permitted under one Sovereign’s set of rules drew that type of development TO that Sovereign.

    His Globalist view though conflicts with his attempted obfuscation.

    Pause for a moment and think what accepting HIS viewpoint dictates. His viewpoint dictates that NO amount of Sovereign-specific rules CAN make a difference — no matter how many confounding variables there may be.

    His penchant for outright dismissal – rather than any mere “To ask those questions is to answer them. ” is what indicates the presence of “is trying to sell you something.

  • [Avatar for C.W.]
    July 15, 2022 09:08 am

    @ DeLassus


    “If the U.S. patent laws are operating suboptimally (and boy, howdee are they!), then the effect of …”

    Note: Laws don’t operate. Laws do nothing of their own accord so any fuel who blames laws, is exhibiting fuelishness. It is Men and Women and some others, who “operate”. All battles are battles for the mind, and if ya don’t see that, there may be hope in its tragedy.

    US patent laws were the model for the world, that’s why so many copied them, but copying American Law is not enough. One must think like an American, which is FREEEEDO. “Walls in your mind” by Red Beckman

  • [Avatar for Greg DeLassus]
    Greg DeLassus
    July 14, 2022 05:45 pm

    … an examination of patent laws in India and an examination of patent laws related to industries and the size of the industry in the country.

    Pause and consider what one could learn about the incentive effects of local patent laws from a data set that included rates of innovation and details about what is and is not patentable in a given jurisdiction. Are all nations basically the same, except for their patent laws? Might there be confounding variables in such an international comparison that would frustrate the ability to tease out any conclusions related specifically to patent laws?

    To ask those questions is to answer them. It is not possible to measure empirically the incentive effects of one country’s laws on one country’s rate of innovation. Anyone who suggests that you can is trying to sell you something.

  • [Avatar for Anon]
    July 14, 2022 04:56 pm

    Night Writer is correct and Greg is woefullly false.

    Fields of software (which Greg long has insisted on showing his ignorance) is joined by fields of medical applications (which with his Big Pharma background, he should at least be aware of).

    Why the outright fallacies from Greg?

    Most likely, this is due to his extreme religious views of a One World Order and the Liberal Left agenda for such.

    See: for a quick recap by Dr. Lindsay (which of course is backed up literally by hours of in-depth and fact-based [in the Liberal Left’s own publications] that Greg has only sneered at.

  • [Avatar for Greg DeLassus]
    Greg DeLassus
    July 14, 2022 02:10 pm

    There are no historical data (or any other data) that say this patent laws respect borders in their incentive effects. It is not possible for data to speak meaningfully to that point.

  • [Avatar for Night Writer]
    Night Writer
    July 14, 2022 01:37 pm

    Greg repeats over and over again >It is not possible for the U.S. to be “left behind” on account of our patent laws.

    There is historical data that says this is wrong. For example an examination of patent laws in India and an examination of patent laws related to industries and the size of the industry in the country.

    Plus, the USA + China are like 60% of the world economy. Etc…

  • [Avatar for Greg DeLassus]
    Greg DeLassus
    July 14, 2022 12:59 pm

    It is not possible for the U.S. to be “left behind” on account of our patent laws. It is not possible for any country to gain or lose a competitive advantage relative to others based on that country’s patent laws.

    U.S. inventors receive incentive and encouragement from EP/CN/etc patent laws. EP inventors receive incentive and encouragement from US/CN/etc patent laws. CN inventors receive incentive and encouragement from US/EP/etc patent laws. No nation’s patent laws have effect to incentivize or encourage innovation that does not work equally well to incentivize or encourage innovation by foreign innovators and domestic innovators.

    If the U.S. patent laws are operating suboptimally (and boy, howdee are they!), then the effect of that suboptimal operation is to less innovation globally. The suboptimal operation of U.S. patent laws, however, does not create any sort of unique lack of incentive inside the U.S. borders. That is just now how patent law works.

  • [Avatar for C.W.]
    July 14, 2022 11:48 am

    Anon “the known fact that software — as a machine component — improves the machine (the simple logic displaying this is that if this were not so, then software would never be sold)”

    add to this the fact that software marketeers compete fiercely, with products differentiated by their features and the state of that Art has and is constantly advancing. Congress needs to make available AI – related IP protection, to fulfill its charge of promoting progress in the useful arts. Every new, improved piece of software which improves the function of a machine should be fair game, if it’s correctly claimed.

  • [Avatar for Night Writer]
    Night Writer
    July 14, 2022 11:20 am

    Just as a final point, none of these discussions make any sense unless people understand the Church-Turing Thesis. It is like talking about motion and not understanding Newton’s laws.

  • [Avatar for Night Writer]
    Night Writer
    July 14, 2022 11:14 am

    One thing too is that AI is actually quite complicated and the way in which AI is being done is not just add more computational power and data. The fact is that the way in which AI is performed is evolving quickly.

    Plus, it is beyond insane that an application that is working on say helping a person get a job gets dumped into the 36xx graveyard but the same technology that organizes a database goes to 21xx and gets allowed.

    Anyway….what is behind this is corruption where all our politicians are bought off boys and girls and you can’t trust a thing they do or say. They aren’t working to set up a sound structure for the USA but to maximize their personal wealth gain. Note too that the CAFC has a fundamental problem at this point. Most of the judges are about limiting the patent right with judicial activism and don’t care about setting up a comprehensive system for patent law. (Note too that the lobbyist continue their push against patents with Le mle y’s latest “broad functional claiming” where all modern invention must use functional language and this “broad” has been added that has no meaning without an understanding of the ladders of abstraction and what is known in the art.)

    Consider that the CAFC could easily cabin Alice by limiting what is an abstract idea to the words of Alice. The CAFC has broadly expanded Alice and then pretends that they haven’t. The CAFC continues to attack patents in 112 as well.

  • [Avatar for Anon]
    July 14, 2022 11:07 am

    Brain for a machine is still a physical object – a machine component, which falls into the category of machines.

    To pretend otherwise is to violate a fundamental understanding in this art field: the choice of “wares” (be it ‘soft,’ ‘hard,’ or ‘firm’) is merely a design choice, and that choice does not change the patent equivalency of the claims.

    I expect better from this author.

    Further, I would posit that the statement, “ because machine learning cannot survive the current technical improvement analysis” is false. One should not confuse today’s errant analysis in regards to technical improvement (an overweaning emphasis on machine qua machine) versus the known fact that software — as a machine component — improves the machine (the simple logic displaying this is that if this were not so, then software would never be sold).

    Further still, the article omits even mentioning the actual patent law legal crux, of which two immediate items come to mind:

    1) lack of a human inventor that faithfully satisfies the legal definition of inventor (which means that we can place the ‘disputed’ notion that AI IS (at least) one of the inventors to the side); and

    2) the impact to the other non-human juristic person involved in patent law (the one dealing coldly with the State of the Art): the Person Having Ordinary Skill In The Art. What then, of that State of the Art that HAS OCCURRED and to which at least some part of the invention cannot rightfully have an actual human named as inventor? – does such then serve to block other inventions that DO have all human inventors?

    Just as real human inventors cannot possibly know of the actual State of the Art at any one given time (with art that the PHOSITA is not only allowed to know, but is REQUIRED to know), so too, the State of the Art – as may be contained with non-human capture but generated by AI DOES reflect actual State of the Art.

    This second point is also quite separate from the (contentious) AI-IS-THE-INVENTOR direct debate, but still is a point that is (purposefully) ignored.

  • [Avatar for Night Writer]
    Night Writer
    July 14, 2022 10:54 am

    Right now as many have pointed out the 101 analysis is just absurd. It has no grounding in reality. Consider that Alice is about an enabled abstraction, which is an oxymoron.

    Alice can easily be cabined by the Scotus just putting tight controls on what an abstraction is under Alice.

  • [Avatar for Anon]
    July 14, 2022 10:54 am

    You lost me with the very first sentence – which has blatant errors (“and in a lot of cases, no machines“).

    Either this is wrong, or it is deceptively misleading (process claims do not require machines – but such is true for ALL process claims).

  • [Avatar for Anon]
    July 14, 2022 10:18 am

    OT – but thank you (Blog-master) for reinstalling the comment indicator.

  • [Avatar for concerned]
    July 14, 2022 08:10 am

    Thank you IPWatchdog for adding number of responses on the surface of the article before clicking into that article!

    Agree with author, however, I think a hidden agenda is the patent culprit in this country. I learned long ago, when smart people say dumb things, it is a hidden agenda. The person is still smart.

    An observation about the law of the land: If the law is really on the side of the rejection/invalidation, why does evidence need to be tossed, statements made that are illogical on the surface, words added to law will not be defined, hide behind collateral estoppel of judicial exceptions, etc.? If the law is really on their side, why resort to the preceding actions?

    Do I really think an examiner is stupid when he writes the process is routine, well understood, and convention when the evidence on record reflects no end user or authority has ever used the claimed process individually or in combination? Or the Board says mental steps. Let’s prove it and put our money where our mouth is using a real life example inspired by an attorney (Benny) who once said I should NOT get the patent even though I met the law. “This is a recording beep”

    Rhetorical questions.