Not Yet Evolved? Where is 35 USC §101 going?

Posted on 12/12/2018 by Brittany Knight, in Articles, News and Events, Patent Trends & Activity

Software is a generic term to refer to a collection of data or executing code used by a computer to implement arithmetic operations or logical operations. Back in 1936, Allen Turing, in his landmark paper On Computable Numbers proposed the capable use of instructions (i.e. software) to execute functions through his Turing Machine, an early precursor of the general purpose computer[1]. Today the modern computer is instrumental for complex computations, data analytics, high-powered graphing, simulations, and so on. Although, the development and use of software for these computer functions has become mainstream, determining the patent eligibility of software inventions under 35 USC §101 has been less intuitive.

In the wake of the now famous Mayo and Alice decisions, patent subject eligibility is determined through a 2-step inquiry. The first step asks whether, the patent claim is directed to a natural phenomenon, biological process, or abstract idea. Software is generally categorized as being “abstract” because it does not fulfill the more concrete criteria for being a “thing”: i.e. a process, machine, manufacture, or composition of matter. Because software claims often fail the first step of the Mayo/Alice inquiry, the inquiry is next directed to the second part, which determines whether the patent claims add “significantly more” to bring them back within the fold of eligibility. However, meeting this second step has proven challenging in the court of law when it comes to determining patent eligibility of modern computational tools.

The recent Federal Circuit case of BSG Tech LLC v. BuySeasons, Inc. reiterates these challenges, but also what is needed to overcome them.  BSG Tech sued BuySeasons for infringement on claims for the use of “self-evolving generic indexing of information” (US patents 6,035,294, 6,243,699, and 6,195,652). Indexing software is used to organize and search information based on various parameters and values. The problem, BSG Tech points out in their ‘294 patent is that current indexing methods are incapable of sorting through the enormous amount of information available on the internet in an efficient and accurate way. For instance, if one wants to search for a specific website one most likely would need to know part of the URL unless the subject for the webpage is otherwise included in the web address. Otherwise, one may choose to search by keywords. However, keyword searching can restrict the search to subjects indexed by that keyword (e.g., searching for “red” car would provide only cars that were identified as “red” and not magenta or crimson cars). Additionally, a search for red Mercedes™ might also retrieve irrelevant information such as “a story about a woman named Mercedes wearing a red dress.” To combat this issue of specificity, online stores often use hierarchal indexing to narrow searches based subject themed drop-down menu selection (e.g. All, Books, History, Military, strategy, The Art of War by Sun Tzu). And yet, applying these current “generic” indexing to large databases or searching the internet would require a substantial amount of effort and cost not to mention, a massive list of search parameters since search criteria can vary greatly by subject matter (i.e. make and model are more appropriate for vehicle searches rather than houses or history books).

Therefore, BSG Tech’s ‘294 patent proposes a “self-evolving generic indexing of information” that would permit users to access search parameters based on what other users may have previously conducted. BSG argues this method allows users of varying degrees of knowledge to improve search parameters for the benefit of everyone across the network. As an example, users may access historical usage which would provide the frequency of parameters and values used previously by other users to index different subjects. BSG asserts that their new software provides a significant improvement over current prior art databases. However, the court concluded that these improvements lacked novelty and did not actually add “significant more.” Although, the definition of “significantly more” is technically a “question of law,” the idea is that the claims provide more than conventional or routine standard.

Although BSG described the use of “summary comparison” or “relative historical” as guiding parameters in their indexing software, the court viewed “increasingly narrowing classifications” as inadequate grounds for inventive concept or as a significant improvement upon the current standard. In the past other cases have had more success arguing the validity of their “abstract idea.” In the case between Enfish LLC vs. Microsoft Corporation, the court overturned the District Court’s decision that Enfish LLC’s claims for a “self-referential table” was patent ineligible (US patents 6,151,604 and 6,163,775). For background, Enfish established a logical model that allowed users to create data tables based on a “self-referential” system where by all individual data pieces could be referenced to each other within the same table. In the conventional relational database each entry was referenced individually by type and not as a collective whole. The difference with this case was that Enfish made an effective argument that their claims made significant improvements over the generic method which required individual tables for each comparison of data. Instead their method allowed users to (1) create one table to input and reference data which (2) increased the efficacy for data storage and (3) data retrieval. It was later determined, with the overturn of the District Court’s decision, that the claims instead described an inventive strategy for indexing information that improved upon the current functionality of computers and is therefore, not directed to an abstract idea.

Determining the eligibility of patents is not as strong and fast a rule when it comes to abstract lines crossing into concrete means. With the case of software programs, improving upon a computational machine to facilitate a function may revolutionize an industry, manufacturing of a substance, or provide the ability to accurately measure simultaneous variables at once to execute a process. With BSG, if their product has significant utility like presented in the case between Enfish, their invention of “self-evolving generic indexing of information” may have had a shot at being perceived as more than just an abstract entity and instead, a marketable way for multiple users, across a network, to augment a reference database. However, the claims were seen as an insignificant improvement on conventional indexing standards and denied patent eligibility. Perhaps the speed to which software has been incorporated into our daily lives surpasses our current ability to conceptualize the validity of abstract inventions unless they are presented with concrete strategies. The Mayo/Alice test is clearly not fully evolved.

Brittany Knight  & Dr. Anthony Sabatelli

Brittany Knight is a Ph.D. Candidate in the Biomedical Sciences Ph.D. Program in the Neuroscience Department at the University of Connecticut. Her thesis research focuses on understanding how proteins involved in wound healing can also prevent the onset of pain following inflammation. In addition to conducting research and mentoring students, Brittany has maintained several leadership positions in the Graduate school. Prior to attending UCONN, Brittany obtained her B.S. in Psychology and a minor in Biology with Global Honors with Distinction from Lock Haven University of Pennsylvania.

[1] Turing, A. M. (1937), On Computable Numbers, with an Application to the Entscheidungsproblem. Proceedings of the London Mathematical Society, s2-42: 230-265. doi:10.1112/plms/s2-42.1.230


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