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Request for Comments on Patenting Artificial Intelligence Inventions (federalregister.gov)
116 points by riscy 33 days ago | hide | past | web | favorite | 42 comments



The weird eligibility requirements for the patent bar also encourage this stuff.

Computer scientists are only eligible if they have an undergrad degree from an ABET-accredited program. This rules out people coming from AI powerhouses like CMU and Stanford, as well as Princeton, Yale, etc. Masters and doctoral degrees also don’t count, which is baffling since a PhD involves reading a huge chunk of the literature. The whole process is centered around 1960s “mechanical engineering as the source of all innovation” ideas and seems like it needs a massive update.


There are a couple of other routes to eligibility.

One is by having sufficient coursework in various categories, even if you degree itself was not one they recognize. There are four options if you do it this way.

They are 24 semester hours in physics; or 32 semester hours that includes 8 hours of either physics or chemistry and 24 hours in biology, botany, microbiology, or molecular biology; or 30 hours in chemistry; or 8 hours of either chemistry or physics and 32 hours in chemistry, physics, biology, botany, microbiology, molecular biology, or engineeing.

Under that last option, computer science courses count.

The other route in is by taking and passing the Fundamentals of Engineering (FE) test.

I was once seriously considering becoming a patent agent, but my degree is in math (Caltech, class of '82) which is not on the PTO's list of acceptable degrees, and so looked into these other routes.

The main issue with the coursework route for me was that when I was there Caltech graded all first year courses pass/fail, and the PTO does not count courses taken pass/fail. That knocked a year of physics, a term of physics lab, a year of chemistry, and a year of chemistry lab out of the running.

The FE test route looked quite reasonable. This was a long time ago, and I believe they have changed the format of the test since then, but when I was looking it looked like it would have taken maybe a month or two of spare time prep.


Yeah, I could certainly cram for the FE exam, though only a few states let anyone sit for it. Likewise, it wouldn’t be impossible to take two semesters of chemistry at some community college.

Still, this seems like a massive, unnecessary effort to establish that your Caltech degree, or my Yale one, are at least as good as one from DeVry Tech.


There are alternative means to qualify if you do not have an automatically qualifying degree.


These ML patents are damaging the progress of AI research, and also the commercial use of this intellectual progress.

One way to attack this would be if researchers outside of Google and Facebook started patenting their discoveries, but then immediately released all rights to it under a license that's valid for anyone who does not sue offensively. That way if Google wanted to sue for infringing use of invention A, they would themselves immediately be infringing on invention B and C. Quickly any large player would be entangled into a web where any offensive lawsuit is impossible. If we had standardized licenses with these clauses, we could stand a chance to stop this.


Yet when Facebook tried that, there was intense resistance and they ended up giving up.


The react license had "we won't sue you for violating our patents, except if you sue us first.", which entails "if you use this, you can't sue us for violating your patents, because by using this you guarantee that we have material for a countersuit." People felt that this asymmetrically benefited Facebook. You want Facebook to be on the other side of such an agreement. If a license was made that came with an agreement that neither party can sue anyone in an offensive patent suit, it would limit the destructive power of the big players that hold all the patents.

If BatchNorm, ConvNets, LSTMs, Dropout, ReLUs or any such essential neural net component came with such a clause, I could see the big players accepting the license, especially since it aligns with their publicly stated claim that they only file patents for defensive purposes.


I would argue that patents simply shouldn’t apply to this arena. It’s barely understood enough today, and locking things up with patents will only hold it back for society and concentrate power in the hands of a few.


You could also argue that an AI inventor should have the same rights and protections as a human inventor. Or maybe as a underage inventor represented by their parents.


Am I misunderstanding the subject? I thought it was just asking for comments about patents for AI technology. Are we talking about patents for things invented by computers? That is a really interesting subject that I've never thought about.


Yes they are requesting comments on both and trying to figure out where one starts and the other ends.

From the article:

> 1. Inventions that utilize AI, as well as inventions that are developed by AI

> 3. Do current patent laws and regulations regarding inventorship need to be revised to take into account inventions where an entity or entities other than a natural person contributed to the conception of an invention?


You will misunderstand if you don't read what is linked before you comment.


I hope there’s a similar precedent set to Alice vs. CLS Bank [0], stating that the same idea but implemented on a computer isn’t sufficient for a patent. It seems reasonable to me that solving a problem with artificial intelligence should follow similar rules.

[0] https://www.eff.org/deeplinks/2014/06/bad-day-bad-patents-su...


I think there are two completely different issues conflated here. Inventions in the domain of AI, aka new algorithms, and inventions made by an AI. Once an AI is genuinely capable of new inventions it's arguable that it should have the same protections as its human co-inventors or tutors (assuming AI personhood is not a thing when this happens.).

An invention submitted by a group containing an AI co-inventor or using an uncredited AI as a tool could be in any field, not necessarily a software patent, so the "idea but implemented on a computer" doesn't really come into play here.


How about, stop patenting ideas? Stop granting ridiculous patents when it isn't even certain they re the first inventors? These patents are way too premature and dangerous

If the USPTO has trouble understanding a technology, they should err on the side of caution and NOT grant the patents, instead of asking for comments ex post-facto

Take for example Dropout. This is a ridiculous thing to patent. Dropout is essentially half your network malfunctioning. A computer that randomly caught fire could "come up" with the same "algorithm". How can the USPTO judge that patenting this thing in any way would help innovation (that's the purpose of patents). In fact, most researchers will now be discouraged from researching dropout-like techniques any further


>Dropout is essentially half your network malfunctioning. A computer that randomly caught fire could "come up" with the same "algorithm".

This is so incredibly wrongheaded I don't even know where to begin.


in as much as it's wrong in the ML sense (I seem to have become a network engineer for an ML company) it's a pretty funny analogy.


> How about, stop patenting ideas? Stop granting ridiculous patents when it isn't even certain they re the first inventors? These patents are way too premature and dangerous.

For all the faults of patents (and there are many), one of the great benefits is that when you patent something, you must publish it for all to see. If we want to keep innovation moving along quickly, there needs to be incentives to publish your findings for everyone to review and build on.

The lawsuits don't really start until someone starts making big money. Yes, they are burdensome and expensive, but I'd rather keep innovation moving quickly and having the winner pay a tax than not having any innovation at all.


The publication benefit is gone. Most patents are worthless for gaining understanding. They're written to be deliberately vague so as to encompass as much as possible. There may be some details, but a store knowledge they are not.


And what's worse, the legal advice I've often been given is not to read patents at all. It's considered a liability to have read a patent.


> For all the faults of patents (and there are many), one of the great benefits is that when you patent something, you must publish it for all to see.

Do people tend to learn things from patent filings, or from other sources?

I've looked at a few patents, and they don't read like anything that tries to educate the reader.


> Do people tend to learn things from patent filings, or from other sources?

When you file for a patent, it usually does not get published to the public for 18 months. In those 18 months, the inventors usually publicly announce themselves (they have patent protection, so there's little harm doing so). If they didn't have patent protection, there would be much more resistance to publishing your work.


> If we want to keep innovation moving along quickly, there needs to be incentives to publish your findings for everyone to review and build on.

There is more than plenty of open research in NNs. There is absolutely zero insights in these patents that is not already published.

I also find it a very weak argument in favor of patents. You can reverse-engineer anything, no need to read the filings


> There is absolutely zero insights in these patents that is not already published.

The general procedure for many about to publish a research paper in a growing field is to get a patent application on file first. There wouldn't be nearly as many publications if there were no patent protection.


this may have been true traditionally but most AI research is completely out in the open, so this seems redundant at best.


> most AI research is completely out in the open, so this seems redundant at best.

It wouldn't be as open if there were no patents. When researchers working for a big company are about to file a research paper, their corporate sponsors get the patent application containing their work on file first.


Patents are absurd, in general, any kind of patents.


Google patenting backprop is quite ridiculous. Since most if not all ML researchers come across this at some point and is used in many commercial applications. Not sure why they did it in the first place, but it's likely impossible to regulate.

Here's their patent: https://patents.google.com/patent/US5052043A/en


They did it to protect themselves from patent trolls.


That's a ridiculous argument. Google has patented way more than this (most recently all kinds of recurrent nets for sequences). As long as these patents belong to alphabet they 're dangerous. Google could have set up a nonprofit for them if they really cared. What if google is bought out in 5 years? What if they get real competition and decide to go full evil?

These patents are overly broad, overly premature. They should never have been granted in the first place.

I think the NN pioneers who are first names in these patents should set up a nonprofit themselves. Hopefully many of them still seem to believe in the ethic of science , having lived decades in which nobody cared about NNs


Google is not the only company who accumulated a patent portfolio to be used defensively. If they start suing people they can expect to be sued back. It would also potentially ruin Google's relationship with other companies who would be reluctant to work with them if it could lead to a chance to be sued: e.g. If you sell some technology to Google to use they can discover that it has something that looks like something that they patented, which is enough grounds to sue you. This is too much risk for companies who don't have the money to mount a legal defense, even if they don't actually violate any patents.

The current state is sort of a patent cold war where both sides have weapons but they don't use them. So we get the advantages of patents (disclosure) without many of the potential disadvantages.


If OTOH, USPTO had rejected these applications there would be no need for this cold war


Sure, but then a lot of developed technology would remain secret forever.


That’s an expired patent from 1990 assigned to Kodak.

It’s also not as broad as patenting backdrop.


It was very inconsiderate to waste other readers' time with this easily checked misinformation. What was the point?


I have worked with several AI/ML inventions. In the patent applications I am familiar with, the AI/ML components are often treated as black-boxes. Because the AI/ML components of the system are not really novel. Not unlike how a processor or memory component doesn't contribute to novelty either.

Also, the AI/ML parts of inventions I have seen are based on conventional/non-patentable AI/ML techniques.

It is the combination of AI/ML components with other components, such as, the bits about managing the inputs, outputs, feedback loops, model selection/management, training optimizations, or the like, that make a patentable AI/ML invention. Further, IMO, it would be poor patent drafting to draft a patent application that relies on particular AI/ML techniques. If your AI/ML techniques are really novel and patentable, you should still draft the patent such that other AI/ML techniques could be substituted into the system as well as claiming the unique AI/ML technique.


Can an AI patent itself?


This question is also asked in the RFC by adopting a rather philosphical stance towards assigning a patent to an 'AI based entity'.

4. Should an entity or entities other than a natural person, or company to which a natural person assigns an invention, be able to own a patent on the AI invention? For example: Should a company who trains the artificial intelligence process that creates the invention be able to be an owner?


>Do current patent laws and regulations regarding inventorship need to be revised to take into account inventions where an entity or entities other than a natural person contributed to the conception of an invention

Well, this seems a little dangerous. I would argue that any invention or innovation generated by an AI should be made public domain.

As we rapidly approach the possibility of genuine AI, the gap between the haves and have nots will increasingly be defined not by accumulation of capital but by accumulation and control of information. If the explosion of technical progress we've seen in ML recently continues, it's quite likely that future designs and breakthroughs will eventually come from neural nets themselves - and if we define these innovations as IP and afford the usual legal protections to the nets that generated them, as the question seems to imply ("other than natural persons"), then I imagine by proxy the ultimate owner of the patent is the owner of the net. Which forms the foundation of a dystopia defined by unprecedented "wealth" inequality where one or a handful of first movers become irreversibly entrenched as the gap between AI powered innovation and human powered innovation will widen exponentially once that door is unlocked.

I think much of the progress in the ML explosion is owed to the beauty of open source and open access publishing on arxiv, and I can't help but feel like getting neural network designs mixed up with patent law would stymie the iterative collaboration that defines ML research.


Technology should be free


AI will be a curse for humanity.


But the curse will be patented




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