Algorithms are generally understood and broadly defined by Merriam-Webster’s dictionary as a “step-by-step procedures for solving problems or accomplishing some ends.” In the modern computing context, algorithms can be understood as a series of steps that make up operations, which in turn make up a particular module or executable piece of software that accomplishes a specific task. In simpler terms, algorithms are executable code that accomplish something. As modern companies become increasingly reliant on computers to increase their efficiency and profitability, computer algorithms are implemented and relied upon to perform all manner of tasks in industries of all different levels of technological sophistication. Tech startups may be relied upon to create and service the algorithmic needs of existing, legacy industries, or they may create new and innovative algorithms to solve previously unknown or unfulfilled needs. Either way, the same question manifests in many tech executives’, engineers’, and employees’ minds:
“Can this algorithm be patented?”
Patent Eligibility Criteria for Algorithms and Software Patents
To answer the question of whether an algorithm can be patented, it is important to first explore what qualifies for patent protection. In the United States a patent can be granted for technological advancements or discoveries that fall into one of several categories that have been codified in 35 U.S.C. 101. These categories of patentability are:
- Manufactures, and
- Compositions of Matter.
As previously discussed, an algorithm is a series of steps that accomplish an end. Therefore, you might think that algorithms fall squarely into the processes category and are therefore obviously patentable. However, like so many things in the law, things are not so black and white. The United States Supreme Court has identified exceptions to otherwise patentable subject matter which must be considered in any patentability analysis. These exceptions to patentability are for:
- Abstract ideas,
- Laws of Nature, and
- Natural Phenomena.
What does this mean for algorithms? They do not seem to qualify as natural phenomena or laws of nature, but in many instances they do seem to qualify as abstract ideas. Nevertheless, exceptions to the abstract idea exception have been identified by the legal system. These exceptions to the exception provide that if an algorithm can be tied to elements that amount to “significantly more” than a merely abstract idea, the algorithm in question may still qualify as patentable subject matter.
So, what is this “significantly more” and how can a budding (or established) tech company discern whether its innovative algorithm meets or exceeds the standard? This is the question many courts have been grappling with in recent years. The most successful patent claims at overcoming this hurdle have tied their algorithms to real world results that are not pure data transformations. In the context of computer implemented algorithms, these patents include claims that are directed toward improvements in the functioning of a computer, improved computer capabilities, results that provide improvements in other technical fields, and non-conventional arrangements of components. (See MPEP § 2106.05 for further detail)
Can You Patent Artificial Intelligence?
One area of software development that is currently popular is Artificial Intelligence (AI). Broadly defined, AI is the implementation of technical solutions to allow machines to function in a manner similar to humans and mimic human behavior. AI often includes the implementation of algorithms that rely on the use of sensors and feedback loops to capture changing information about the real world and a machine’s place and orientation therein, in order to allow the machine to behave in a particular manner.
One example you can consider is the application of AI software in autonomous vehicles. These vehicles integrate inputs such as landmarks from Google maps and Google Street View and embedded cameras that are mainly controlled using algorithms that employ a variety of different sensors to simulate human and decision and perceptual decision making in the driver control systems. The AI uses the information about the continuous changing environment and street views around them (e.g., identifying upcoming stoplights or crosswalks; people, animals, and objects moving on sidewalks; and other moving vehicles such as bicycles, motorcycles, and automobiles) and utilizes that information to automatically maintain a pre-determined safe distance between cars while continuous centering the vehicle within the lane throughout the transit. While most vehicles are not entirely autonomous and the human driver is still required to enable or override the systems many of these self-driving vehicles are highly autonomous and accomplish their primary task of transporting people or goods safely, timely, and efficiently from one location to another.
The autonomous vehicle example above provides a somewhat straightforward case of an AI that is tied with a real-world machine that is seen every day reducing the risk of accidents for a vehicle by using sensory data and a variety of camera around the vehicle to create a 360-degree view of the environment to perceive object, control steering, and modify speed. However, not all AI algorithms are so linked to everyday machines in the real world. Often, AI algorithms are used to manipulate data and may only result in a specific output on a user interface display or as an input within a larger software system. Many of these types of algorithms may not necessarily qualify for patent protection unless it can be argued that they improve the functioning of a computer or provide some technical advantage in another field. When determining if your algorithm may be patentable, it is important to consider and be able to articulate what real-world, tangible results or computer function improvements the AI algorithm performs. Understanding what technical improvements that software provides over existing technology is crucial when articulating the technical improvements linked to your AI.
Can You Patent a Mathematical Formula?
No article about algorithms would be complete without discussing mathematical formulas. For what does the use of a mathematical formula entail, but a step-by-step procedure to solve a problem. This is very similar to the definition of an algorithm that was previously discussed. Mathematical formulas and their use then logically falls under the process category of patentable subject matter. However, unlike algorithms that are usually analyzed only as abstract ideas, mathematical formulas can be understood as abstract ideas (i.e., relations between scientific concepts including constants, mass, weight, speed, acceleration, and numerous others) but are equally as likely to be understood as expressions of laws of nature or natural phenomena. One prominent example is that an object’s energy equals the mass of the object times the speed of light squared is expressed by the mathematical formula E=MC2. This begs the question; can a mathematical formula be coupled with something “significantly more” to be patentable in a similar manner to non-mathematical formula algorithms?
The answer is potentially yes. While the mathematical formula alone is not considered patentable subject matter under the law, if the formula is implemented in a particular fashion with real-world, tangible results or computer function improvements that are patentable, then a claim including the formula may be patent eligible.
Algorithm Patent Examples
Despite the complications in trying to patent algorithms, many companies have been able to find success in growing their IP portfolios based on their proprietary algorithms. Speech recognition, image processing and analysis, physiological profile creation, drones that can determine expressions and gestures, advertising results improvements, and many other examples exist in which algorithms have successfully been patented and used to build the modern digital marketplace. Careful consideration of the legal structures and precedent has helped small and large companies alike to patent and monetize their proprietary algorithms and software.
The major players in this sector are Google, Samsung, and Amazon. Here are three examples of patents from these brands that are related to machine learning:
Samsung’s Drone That’s Controlled Through Face Recognition and Hand Gestures
Samsung’s latest patent is a drone with a flying display that can detect a person’s face, pupils, and hand gestures.
The patent describes the camera as a mechanism that transmits information to the main control unit. Hence, it supplies the inputs.
It’s usefulness, however, is still debated. Many people believe that it’s primary purpose may be related to the advertising industry, potentially projecting customized display ads for users as they walk down the streets of major cities.
Amazon Files a Patent That Can Capture the Details of a Conversation and Save It.
Smart speakers are always paying attention to what’s happening around them. With Amazon’s latest patent, the Alexa smart speaker may be activated by not only a trigger word, but your own interests.
According to the patent, Alexa will register words that have strong meanings behind them. For example: “I love the Italian food.” By saying a phrase with the word “love”, the smart speaker will analyze this data and use it to personalize advertisements. Soon enough, you’ll likely start to see offers for Italian food.
This technology can also be used for negative keywords as well. For example, if you say “I hate sushi”, this will be registered as something that you dislike and giving Amazon advertisers the ability to avoid advertising to you.
Google Wants to Give You Short and Exact Answers.
In the early days Google was very simple. If you entered certain keywords, it would show you web pages that contained those words.
Their mission has always been to provide better results to search queries. However, soon enough, they realized their old method was focusing more on web pages – and not giving meaningful answers.
To solve this problem, they created an algorithm where If you type a simple question, you would get a simple answer.
To take things a step further, Google updated its algorithm and filed a patent to include rich media in these types of search results.
For example: when you search “listen to We Will Rock You by Queen” it will give you the following result:
This technology is one of the most widely used in today’s search landscape and has also been the basis of providing the best results for voice search.
Who Has The Most Patents Related To AI & Machine Learning?
Not surprisingly, the majority of AI & machine learning patents come from the biggest American and Japanese tech companies. In recent years, Chinese companies like Baidu have also been growing their patent portfolio. The problem, however, lies in their quality.
Over the past 5 years, there was a huge surge in patenting artificial intelligence, according to the World Intellectual Property Organization (WIPO)
According to WIPO, the number of AI-related patent applications worldwide skyrocketed 193% from 2013 to 2017. The director-general of WIPO stated the surge in patenting “means we can expect a very significant number of new AI-based products, applications and techniques that will alter our daily lives — and also shape future human interaction with the machines we created”.
When analyzing corporate acquisitions in the AI sector, WIPO found that 434 companies have been acquired since 1998, with over half of those taking place after 2016.
Today AI and Machine Learning are driving forces behind innovation in all industries and will continue to yield massive value to the companies who are wise enough to protect their intellectual property.
Consult With an Experienced Software Patent Attorney
An IP attorney with extensive experience in algorithms and the software they drive can assist you in protecting your innovation by identifying patentable subject matter, creating technical drawings, and drafting your patent application.
At The Rapacke Law Group, we offer patent services to tech startups on a transparent, flat-fee basis, without the hassle of hourly billing or charges for calls or emails.
Still have questions about what type of IP protection is right for your situation? Take our Intelligent IP Quiz or schedule your free phone consultation at to speak with an experienced IP attorney about protecting your software innovation.