Artificial Intelligence Won’t Achieve Legal Inventorship Status Anytime Soon

Imagine a deposition in which an inventor is questioned about her conception and reduction to practice of an invention directed to a chemical product worth billions of dollars to her company. Testimony reveals how artificial intelligence software, assessing huge amounts of data, identified the patented compound and the compound’s new uses in helping combat disease. The inventor states that she simply performed tests confirming the compound’s qualities and its utility, which the software had already determined. The attorney taking the deposition moves to invalidate the patent on the basis that the patent does not identify the true inventor. The true inventor, the attorney argues, was the company’s AI software.

Seem farfetched? Maybe not in today’s AI world. AI tools can spot cancer and other problems in diagnostic images, as well as identify patient-specific treatments. AI software can identify workable drug combinations for effectively combating pests. AI can predict biological events emerging in hotspots on the other side of the world, even before they’re reported by local media and officials. And lawyers are becoming more aware of AI through use of machine learning tools to predict the relevance of case law, answer queries about how a judge might respond to a particular set of facts, and assess the strength of contracts, among other tools. So while the above deposition scenario is hypothetical, it seems far from unrealistic.

One thing is for sure, however; an AI program will not be named as an inventor or joint inventor on a patent any time soon. At least not until Congress amends US patent laws to broaden the definition of “inventor” and the Supreme Court clarifies what “conception” of an invention means in a world filled with artificially-intelligent technologies.

That’s because US patent laws are intended to protect the natural intellectual output of humans, not the artificial intelligence of algorithms. Indeed, Congress left little wiggle room when it defined “inventor” to mean an “individual,” or in the case of a joint invention, the “individuals” collectively who invent or discover the subject matter of an invention. And the Supreme Court has endorsed a human-centric notion of inventorship. This has led courts overseeing patent disputes to repeatedly remind us that “conception” is the touchstone of inventorship, where conception is defined as the “formation in the mind of the inventor, of a definite and permanent idea of the complete and operative invention, as it is hereafter to be applied in practice.”

But consider this. What if “in the mind of” were struck from the definition of “conception” and inventorship? Under that revised definition, an AI system might indeed be viewed as conceiving an invention.

By way of example, let’s say the same AI software and the researcher from the above deposition scenario were participants behind the partition in a classic Turing Test. Would an interrogator be able to distinguish the AI inventor from the natural intelligence inventor if the test for conception of the chemical compound invention is reduced to examining whether the chemical compound idea was “definite” (not vague), “permanent” (fixed), “complete,” “operative” (it works as conceived), and has a practical application (real world utility)? If you were the interrogator in this Turing Test, would you choose the AI software or the researcher who did the follow-up confirmatory testing?

Those who follow patent law may see the irony of legally recognizing AI software as an “inventor” if it “conceives” an invention, when the very same software would likely face an uphill battle being patented by its developers because of the apparent “abstract” nature of many software algorithms.

In any case, for now the question of whether inventorship and inventions should be assessed based on their natural or artificial origin may merely be an academic one. But that may need to change when artificial intelligence development produces artificial general intelligence (AGI) that is capable of performing the same intellectual tasks that a human can.

Federal Circuit: AI, IoT, and Robotics in “Danger” Due to Uncertainty Surrounding Patent Abstraction Test

In Purepredictive, Inc. v., Inc., the U.S. District Court for the Northern District of California (J. Orrick) granted Mountain View-based’s motion to dismiss a patent infringement complaint. In doing so, the court found that the claims of asserted U.S. patent 8,880,446 were invalid on the grounds that they “are directed to the abstract concept of the manipulation of mathematical functions and make use of computers only as tools, rather than provide a specific improvement on a computer-related technology.”

Decisions like this hardly make news these days, what with the frequency by which software patents are being invalidated by district courts across the country following the Supreme Court’s 2014 Alice Corp. Pty Ltd. v. CLS Bank decision. Perhaps that is why the U.S. Court of Appeals for the Federal Circuit, the specialized appeals court for patent cases based in Washington, DC, chose a recent case to publicly acknowledge that “great uncertainty yet remains” concerning Alice’s patent-eligibility test, despite the large number of post-Alice cases that have “attempted to provide practical guidance.”  Calling the uncertainty “dangerous” for some of today’s “most important inventions in computing” (specifically identifying medical diagnostics, artificial intelligence (AI), the Internet of Things (IoT), and robotics), the Federal Circuit expressed concern that perhaps Alice has gone too far, a belief shared by others, especially smaller technology companies whose value is tied to their software intellectual property.

Utah-based Purepredictive says its ‘446 patent involves “AI driving machine learning ensembling.” The district court characterized the patent as being directed to a software method that performs “predictive analytics” in three steps. In the method’s first step, the court said, it receives data and generates “learned functions,” or, for example, regressions from that data. Second, it evaluates the effectiveness of those learned functions at making accurate predictions based on the test data. Finally, it selects the most effective learned functions and creates a rule set for additional data input. This method, the district court found, is merely “directed to a mental process” performed by a computer, and “the abstract concept of using mathematical algorithms to perform predictive analytics” by collecting and analyzing information.

Alice critics have long pointed to the subjective nature of Alice’s patent-eligibility test. Under Alice, for subject matter of a patent claim to be patent eligible under 35 U.S.C. § 101, it may not be “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea. If it is, however, it may nevertheless be patentable subject matter if the particular elements of the claim, considered both individually and as an ordered combination, add enough to transform the nature of the claim into a patent-eligible application. This two-part test has led to the invalidation of many software patents as “abstract,” and presents an obstacle for inventors of new software tools seeking patent protection for their inventions.

In the Purepredictive case, the district court found that the claim’s method “are mathematical processes that not only could be performed by humans but also go to the general abstract concept of predictive analytics rather than any specific application.” The “could be performed by humans” query would seem problematic for many software-based patent claims, including those directed to AI algorithms, despite the recognition that humans could never perform the same feat as many AI algorithms in a lifetime due to the enormous domain space these algorithms are tasked with evaluating.

In any event, while Alice’s abstract test will continue to pose challenges to those seeking patents, time will tell whether it will have “dangerous” impacts on the burgeoning AI, IoT, and robotics industries suggested by the Federal Circuit.


Purepredictive, Inc. v. H2O.AI, Inc., slip op., No. 17-cv-03049-WHO (N.D. Cal. Aug. 29, 2017).

Smart Systems Innovations, LLC v. Chicago Transit Authority, slip. op. No. 2016-1233 (Fed. Cir. Oct. 18, 2017) (citing Alice Corp. Pty Ltd. v. CLS Bank, 134 S. Ct. 2347, 2354-55 (2014)).