Artificial Intelligence Systems Are Not Inventors… Yet.

Recently, an Artificial Intelligence (AI) named DABUS (“Device for Autonomous Bootstrapping of Unified Sentience”) made international media buzz when it was listed as an inventor on patent applications filed in the United States Patent and Trademark Office (USPTO), United Kingdom Intellectual Property Office (UKIPO) and the European Patent Office (EPO).  While there have been thousands of patent applications for various AI systems, from machine learning (ML) systems, to neural networks, generative adversarial networks (GANs) and beyond, this is at least one of the first AI systems to be listed as the inventor itself.

What is DABUS

Developed by Stephen Thaler, a well-known expert in the field of AI, DABUS is an implementation of a type of generative adversarial network (GAN), where two or more neural networks are used to play against one another in order to improve the outputs of at least one of the neural networks to create something different and new.

In the most common implementation, a GAN comprises two neural networks.  The first is a generator, which is used to generate new data (e.g., images, text).  The second is a discriminator, which is used to determine whether the data generated by the generator is real or fake.

In order to determine fakes, the discriminator is given a (preferably large) dataset of real data to compare the data generated by the generator against.  Like a high-tech game of cops and robbers, the discriminator is trying to identify the fake data provided to it from the generator.  Each time the generator fails to convince the discriminator of the validity of its generated data, it learns.  This process is repeated at the incredible rate that computing does these days.  The results, can be stunning.   In fact, a piece of artwork generated by such GANs recently sold at Christie’s for $432,000.

DABUS operates on this same principal.  Give a dataset to a discriminator as a training model and let the generator try to fool the discriminator.  Now, of course, Dr. Thaler uniquely calls his generator an Imagitron, and his discriminator a Perceptron, but ultimately it is still a GAN, doing what a GAN does.

What did DABUS “Invent”

Without getting into the debate or hype over what was actually “conceived” by DABUS, the actual products that were more aptly described as “designed” by DABUS are: 1) an interlocking food container; and 2) a light that flashes in a particular way that mimics neural activity.  I do not intend to go into the details of these inventions, as they have been discussed ad nauseum elsewhere.

Regardless of what DABUS designed, the inventions themselves were based on datasets and information provided to it.  As was said excellently elsewhere, “[DABUS] was ‘mentored’ by Dr. Thaler over a two month period to produce increasingly complex concepts.”  Put differently, DABUS did not set out on its own to solve the problem of interlocking containers or calming pulsating lights; rather, DABUS was tasked with solving these concerns.

The Patent Applications

The three patent applications were submitted by a group led by Ryan Abbott, a professor of law and health sciences at the University of Surrey in the United Kingdom.  Not unsurprisingly, a novel question of law has been raised by an academic.  And that is not a criticism, but rather an acknowledgement that patent law will have to address certain pressing questions about the patentability and ownership of inventions in a world that is increasingly being influenced by artificial intelligence and its effects.

The question at issue here is whether, given the “creative” output of DABUS qualifies it as an “inventor” under the laws of the patent offices the applications were filed in.  For instance, in the USPTO, the Manual for Patent Examining Procedure defines an inventor as a person who contributes to the conception of the invention.

Here, Dr. Abbott and his team are suggesting that DABUS, through its processing of the data into a useful invention, contributed to its conception in such a manner that it would have to be considered an inventor under that definition.  Others, such as Dr. Noam Shemtov, state that DABUS, and other AI systems are merely tools.  In a 2019 report commissioned by the EPO, Dr. Shemtov writes:

When it comes to a human actor that uses an AI system, whose identity may be inconsequential to the invention process, who simply uses a machine learning technique developed by another, the inventor may be the person who “tooled” the AI system in a particular way in order to generate the inventive output. Hence, under such circumstances the person that carries out the intelligent or creative conception of the invention may be the one who geared up the AI system towards producing the inventive output, taking decisions in relation to issues such as the choice of the algorithm employed, the selection of parameters and the design and choice of input data, even if the specific output was somewhat unpredictable[i].

While I tend to agree with Dr. Shemtov’s analysis of current AI systems as tools that individuals use to provide useful output, that is not to say that it is impossible to conceive that an AI system in the future will able to identify a problem, identify available materials/components/data, and solve the problem on its own, all without human intervention or direction.  And herein lies where Dr. Abbott’s filing of the patent applications with DABUS as an inventor is truly aimed at addressing – AIs as inventors.

AI Inventorship

Dr. Abbott’s true intention appears to be raising the debate over whether current statutory regimes at the various patent offices would allow for an AI to be listed as an inventor, given that even at present, it could be rationalized that the AI is part of the conception of the invention.  However, in the case of DABUS, it seems that there is a strong argument that the conception was at the hands of Dr. Thaler, and DABUS merely reduced the invention to practice.

Regardless, the issues related to having an AI system as an inventor are definitely worth bringing to light.  Dr. Abbott told BBC News, “These days, you commonly have AIs writing books and taking pictures – but if you don’t have a traditional author, you cannot get copyright protection in the US.”  And Dr. Abbott is not incorrect.  The United States Copyright Office published an opinion in 2014 stating that, “[O]nly works created by a human can be copyrighted under United States Law.”

Dr. Abbott continued, stating to BBC News, “So with patents, a patent office might say, ‘If you don’t have someone who traditionally meets human-inventorship criteria, there is nothing you can get a patent on.’ In which case, if AI is going to be how we’re inventing things in the future, the whole intellectual property system will fail to work.”  And again, Dr. Abbott is not incorrect.  35 U.S.C. § 100 defines an “inventor” as the “individual” who invented or discovered the subject matter of the invention.  If an AI system conceived of both the problem and the inventive solution to that problem, it becomes more difficult to say that the inventor of the AI system itself was the inventor of that invention, leaving that IP unable to be secured by patents under the current regime.

Similar inventorship issues arise in both the UK, where the UK Patents Act of 1977 requires an inventor to be a person, and the EPO, where in the EPO’s published opinion written by Dr. Shemtov states, “[I]t has been shown that is is unambiguously implicit that AI systems cannot be identified as inventors.”

All three patent offices where these DABUS patent applications have filed are aware of the issue and are reviewing options and requesting input from the community.  In fact, On August 27, 2019, the USPTO just released a Request for Comments on Patenting Artificial Intelligence on the Federal Register, asking for input on whether current US patent laws 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.

 Conclusion

While lofty news articles have hyped the filing of these patents in DABUS’s name, let us not fall for the smoke and mirrors associated with the current state of AI systems.  At least in the vast majority of existing AI systems, they are not inventors as we define them for the purpose of patents in the US.  They are advanced tools that assist in the reduction to practice of inventive concepts and inventions themselves.  DABUS is not an inventor for the purpose of US patent law.  However, using the leverage and momentum of a good news cycle, DABUS has been able to push forward the conversation on what will inevitably be questions about ownership and protection of all forms of Intellectual Property generated by AI systems in the future.

[i] Dr Noam Shemtov, “A study on inventorship in inventions involving AI activity” (2019)

Patenting and Protecting Artificial Intelligence in the United States

Advancements in Artificial Intelligence (AI) have been occurring at an ever-increasing rate, impacting almost every field of technology, from medical diagnosis and analysis, to driverless cars, to automated securities trading platforms, all the way to home security[i].  The arms of AI can be felt in every industry, in one way or another. Given the speed of advancement and the very nature of AI itself, it is important to consider the complex landscape around how to protect improvements in the AI space.

At first, it is important to note the types of intellectual property (IP) protection that can apply to inventions in the AI space.  The definition of IP generally comprises the core four – patents, copyrights, trademarks and trade secrets.  In the case of AI, each of these may apply, and each has its own particular usefulness and advantages.  Further, each of these types of IP has its own concerns with respect to the timing of obtaining the protection.  For this article, we will primarily be focusing on the two areas of protection that generally are of the most concern – patents and copyrights.

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Patenting AI

AI, in almost all cases, exists as a software component.  Depending on what the use case for the AI is, there may also be a hardware component (e.g., vision system, sensors, actuators), but these hardware components are generally peripheral to the core AI, which is software based.  While AI inventions based in combined software and hardware solutions or standalone software-based solutions may both be patentable, the analysis for whether an AI based system constitutes patent eligible subject matter does take into consideration what is actually involved.

Where there is a corresponding hardware component in use with the software-based AI component, the subject matter eligibility analysis is usually relatively simple, favoring eligibility over not.  For instance, if an AI system is used to automatically control a series of vision systems (e.g., security cameras) and detect intruders, the invention is likely eligible for patent protection from a subject matter perspective, assuming the application is drafted appropriately.

Where the AI system solely exists as a software solution, an examiner at the USPTO will likely give the invention more scrutiny under the subject matter eligibility tests.  We have written more on the patentability of software-based inventions in a separate article that you can find here. However, while patent applications directed to software only inventions may receive additional scrutiny, true AI inventions likely are sufficient to overcome these rejections.  In fact, USPTO Director Andrei Iancu has even discussed the patentability of AI, through discussions of “[H]uman-made algorithms”, during a hearing regarding the oversight of the USPTO in April of 2018.   Again, the critical point in securing a patent in a solely software based AI invention is appropriate drafting of the application.

With respect to patenting AI based inventions, particularly as it relates to the software component of the AI, it is important to note that a utility patent covers the functionality of the software, through defining the software in terms of systems and methods.  What patents do not cover is the actual code.  Source code is covered largely by copyright, which can protect direct copying of the code, but not those who write their own code to perform the same functionality.

In defining what an inventor wants to protect with respect to their software-based AI invention, it is important to look at the invention in terms of a method, or a series of steps.  Considering everything a computer does is generally a series of steps involving processing some data, framing the inventive aspects of the software-based AI invention in such a methodological manner is generally straightforward.

What inventors want to avoid is viewing the invention in the abstract, or very high-level depiction.  For instance, you cannot get a patent on the idea of “an AI based dating platform”, but you could potentially get a patent on the methods performed by the AI in order to find compatible matches (e.g., based on training models and predictive analytics).  So, a focus needs to be on what actual occurs in order to make the invention possible, not solely focusing on a conclusory statement about what problem is being solved.

Another important thing to remember when seeking patent protection for AI inventions, or any invention, is to do so sooner rather than later.  There are two main drivers for this.  First, the USPTO, and most if not all other national patent offices are “first-to-file” for priority on inventions.  What this means is that, even if you get to the market first with your invention, or conceived of the idea before another inventor, if another party’s application gets to the patent office before yours, then the patent rights will be theirs, and you will be prevented from getting a patent on the invention.

The second reason is that your ability to get a patent on an invention, even without worrying about what others are doing, can be jeopardized if you offer for sale or otherwise disclose your invention publicly before filing.  The USPTO gives you one year from making a public disclosure of the invention to file your patent application.  However, the rest of the world is not so nice, with many jurisdictions making it a bar on patentability if you publicly disclose your invention prior to filing a patent application in at least one jurisdiction first.

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Copyrighting AI

With respect to copyrighting all or portions of an invention based in AI, there are certain aspects of these inventions which are protectable and those which are not.  Copyrights cover artistic works, which includes everything from literary works, to graphical/visual works (e.g., paintings, movies, photographs), to musical works and even choreographed dances.

When considering copyrighting portions of an AI based invention, the focus is generally on copyrighting the source code.  Source code is considered a literary work for the purposes of copyrights, and inventors can receive a federal copyright registration in the uncompiled source code.

What is protected by a copyright registration on source code is the copying of the actual code.  It does not prevent others from creating code of their own that performs the same functions.  However, it does restrict the copying of subsets of the whole code, such as the copying of a module, or a series of functions.

One issue when considering copyrighting source code is how frequently the source code is updated.  Rarely is there a piece of software that is static for very long.   Updates in source code, while they may be considered derivative works of the originally copyrighted code, may not be independently covered by the initial registration.  Inventors should consider at what point they want to secure additional copyrights on later versions of a software-based invention.

It is important to note that while a copyright registration can be done at any time, as the works form in the author upon creation, statutory damages and attorneys fees are generally only available if the copyright registration is filed within 3-months of publication of the work[ii].  Filing your registration after that point will limit damages to “actual damages” (e.g., lost profit), which can be harder to prove.

Separately, more and more we see the question about whether it is possible to copyright the output of AI.  Recently there have been numerous instances of AI generating their own artistic works, such as The Next Rembrandt and Bayou.  The law is currently unsettled as to whether these works would be copyrightable.  For instance, in April of 2018, the Court of Appeals for the Ninth Circuit held that the Copyright Act only provides standing to humans[iii].  The case, involving copyrights associated with a Monkey Selfie, but the same findings would presumably extend to works authored by AI.

Of course, numerous scholarly and legal minds believe that works would be derivative works of the individuals who wrote the code for the AI, and as such those individuals would be the rightful owners of works generated by the AI.  We ultimately will have to wait to see how this plays out in the future.

 

Conclusion

Overall, it is important to understand and analyze what aspects of an AI based invention can be secured early on in the process.  Timing is crucial for both patents and copyrights with respect to being able to secure the rights and receiving the greatest protection available under the laws.  This area of technology is moving quickly, so delay and lack of planning can be devastating. Devoting at least some time to do the analysis may help with providing a roadmap for how and when to protect various aspects of your AI based invention so that you reap the greatest rewards possible.

[i]Check out our client Deep Sentinel: https://www.deepsentinel.com/

[ii] See, 17 U.S.C., 412 https://www.law.cornell.edu/uscode/text/17/412

[iii] Naruto v. Slater http://cdn.ca9.uscourts.gov/datastore/opinions/2018/04/23/16-15469.pdf

 

Protecting Your Game – IP in the Video Game World

As a preface, I am a gamer.  Since playing text based games at the age of 6 on a TRS-80 (Pyramid 2000), to ESO and Fortnite today, video games have always been a part of my life.

fortnite.gif(My Solo win in Fortnite without firing a single shot – Ghillie Suit FTW)

Fifteen years ago, video games were considered obscure things nerds would play in small groups and LAN parties, or perhaps a place to play a game of Madden with your friends.  These days, video games are a massive cultural aspect, with the video game industry accounting for over $100 billion dollars in revenue a year.

In fact, these days video games like Fortnite have crossovers with massive media hits, like Avengers: Infinity War.  It is clear, video games are a cornerstone of our media and entertainment culture.

But as anyone who has ever played a game on the mobile device knows, there is never just one title in any genre.  For every PUBG, there will be a Fortnite.  For every Candy Crush, there will be a dozen tile matching games (or 17).

But why are there so many copycats and how do you protect your game from copycats?

Intellectual Property in the Video Game World

When thinking about protecting a video game, the law turns almost exclusively to intellectual property (IP) rights.

IP rights are a bundle of protections that comprise:

  • Patents;
  • Copyrights;
  • Trademarks; and
  • Trade Secrets.

Each of these various prongs are directed to a different potion of the actual construct of a video game.

PATENTS

There are two separate types of patents – design patents and utility patents.  Design and utility patents protect two very distinct portions of a video game.

Design Patents

First, design patents may be applied for to protect the UX/UI (User Experience / User Interface) of a game.  For instance, if you have a novel layout that is ornamental in nature, you can protect the ornamental appearance of the design.

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US Design Pat. No. D780776 – King Com Ltd.

However, these design patents truly only cover the single ornamental design. So if a competitor changes your cute little fruit to cute little gems, the design patent will not be sufficient to protect your game design.

One advantage of design patents is that they can be obtained quickly, relative to utility patents.

Utility Patents

Utility patents cover the novel aspects of the actual game, such as game mechanics.  A utility patent can cover anything from gameplay mechanics and methodology, to user interface functionality, to how data is received and processed by the underlying computer systems.  Truly, anything that is utilitarian, can potentially be covered by a utility patent.

There are of course limitations, especially when it comes to video games.  First is that for an aspect of the game to be protectable, it must be patent eligible subject matter, and in the case of video games, this means the claimed inventive aspects of the video game must be more than an abstract idea.

While there are a lot of considerations to think about as to whether a utility patent is right for you in protecting your video game, it is definitely still something to consider, and something that large companies are doing, even on the most nuanced portions of their games.

For instance, Zynga Inc., just received a patent on an aspect of their Frontierville (The Pioneer Trail) game.  Namely, using a “Show Me” button in a game to identify to users how to perform tasks in a game that may not be easily apparent until detailed to the user.  (US Patent No. 9,962,612, granted May 8, 2018).  Similarly, Nintendo just received a patent on an aspect of matching players that are close in proximity to one another for providing the ability to share user information with one another.  (US Patent No. 9,967,737, granted May 8, 2018).  As you can see, if it has functionality, or relates to game mechanics, it could potentially be patented.

There are significant considerations to be made with respect to filing a patent.  But we will save those for a series of separate articles, as the actual process of drafting, filing and prosecuting a patent can be quite complex.

One additional benefit of having a patent is that since it covers the mechanics of a game, it is likely to cover other games that copy or lift from your game design.  Further, patents may also be licensed or assigned to others, providing additional streams of revenue, value and capital to your company.

COPYRIGHTS

Copyrights cover the actual expression of the video game.  Copyrights can cover your artwork, the source code, the plot lines, the video cutscenes, the audio elements, and more.  If it is an audio, visual or textual work, it most likely may be copyrighted.  Again, there are limitations, but assuming there is a level of creativity and originality involved, it may be protectable.

The main limitation on copyrights is that they generally only cover the actual expression, not the ideas or concepts behind the expression.  While there are several examples throughout the years, there are two relatively recent cases that we can look at to drive the point home about what is and is not protected via copyright.

The first is Tetris Holdings LLC v. Xio Interactive Inc., 863 F. Supp. 2d 394, 410 (D.N.J. 2012), which involves the venerable classic Tetris, versus a virtual clone, “Mino”.  Below is an image of the two games side by side.

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It is not hard to see the similarities, because Xio’s intent was to copy the game mechanics and gameplay of Tetris.  As noted before, these are aspects of a game that are not protectable by copyright.  However, the court found that Mimo went beyond just copying the game mechanics, but copied the actual expression.  The court even pointed to other examples of how one could create a legal clone without running afoul of copying the expression, noting in particular Nintendo’s Dr. Mario.  So here, if you are truly copying not just the game mechanics, but the overall look and feel, you may be running afoul of copyright laws.

Dr Mario.jpg

 

US Patent 5,265,888 – Dr. Mario Patent!

But what if your game is nothing more than a copy of the game mechanics, with no similar appearances?  Well, we can look to our second case, DaVinci Editrice S.R.L. v. Ziko Games LLC, 183 F. Supp. 3d. 820 (S.D. Tex. 2016), for the answer.  In this case, DaVinci Editrice, maker of the popular card game, “Bang!”, accused Ziko Games of distributing a game, “Legends of the Three Kingdoms” (“LotTK”), that infringed DaVinci’s copyrights.

In this case, the appearances were completely different.  Bang! Was a game situated in the wild west, while LotTK was set in ancient China.  The cards looked different.  The artwork was dissimilar.  Visually, the similarity ended at the fact that they were both card games.  Instead, DaVinci argued that LotTK copied the characters of Bang!.  Bang! had a Sheriff, Deputy, Outlaw and Renegade that had the exact same functionality as LotTK’s Monarch, Minister, Rebel and Turncoat.

However, the court found that this amounted to nothing more than copying of game mechanics, which are not subject to copyright protection.  Notably, the court found that these mechanics are dissimilar to book or movie plot, which would be protectable.

So, when it comes to copyright protection, it is truly the expression that matters.

TRADEMARKS

Trademarks protect the branding of a game.  Trademarks can truly extend to anything that evokes in the consumer the origin of a good or service.  It is not just the game name, studio name, or logos, which are what most people commonly think of when they think of trademarks.  Trademarks can also extend to color (e.g., Tiffany & Co. have a registration for their robin’s egg blue boxes with white ribbons), sound (e.g., NBC has a registration for the three note “NBC Chimes” – you probably just heard it in your head) and even scents (e.g., Hasbro registered the smell of PLAY-DOH).

In the video game world, you can protect identifiers like the game name, studio name, taglines, and logos.  But you can go further, like Microsoft did for HALO’s Master Chief, and trademark certain names and other aspects, to the extent that they identify the source of the product or service.

One main consideration with trademarks is that they cannot be generic or merely descriptive of the underlying goods or services.  You could not get a trademark on the term “First Person Shooter” as that is merely a generic term for a type of game.  Examples of merely descriptive marks may be something along the lines of “Goat Simulator”.  This is actually a good example in that, while you can never get a registration on a mark that is generic, you CAN actually get a registration on a mark that is descriptive IF that mark develops “Secondary Meaning.”  Secondary meaning is when the consuming public comes to know the descriptive mark as an origin of goods or services.  Goat Simulator may have been descriptive of the game at first (i.e. a game that simulates the life of a goat, quite questionably I may add), but with hundreds of thousands of downloads under its belt, it likely has become a name that most people recognize.

Marks that are suggestive, arbitrary or fanciful are able to be protected without any evidence of secondary meaning, and may be registered immediately, assuming the mark is in use.  That is, assuming it is not confusingly similar to another mark in use.

TRADE SECRETS

Trade secrets are the secret sauces kept under lock and key.  These are things like the recipe for Coca-Cola or the KFC’s 11 Herbs and Spices, at least until they were revealed.  Which is the crux of trade secrets.  They are only trade secrets for so long as they remain a secret.  Here, the real priority is ensuring that you properly keep access to these trade secrets as limited as possible.  Once out of the bag, there is nothing you can do to put them back in the bag.

For trade secrets, developing policies around access, maintenance and security of the information is crucial.  Sure, you may be able to sue the employee or company who stole your trade secrets, but after that, it is in the public domain for good.

TAKEAWAY

There are numerous aspects of intellectual property that apply to video games.  It is important to come up with a plan to protect those rights, and determine what bag of rights you would like to protect and how to protect them.  Coming up with a strategy that works for your game is crucial, and timing can be very important, as each of the various types of intellectual property has ramifications for not taking action by a certain time.  Speaking with counsel about creating and implementing the strategy should be part of any game development process.