Recent U.S. Patent and Trademark Office actions relating to software patents have confused and frustrated many patent applicants. After the U.S. Supreme Court published its opinion in Alice Corporation Pty Ltd. v. CLS Bank Int’l, the USPTO’s application of the Court decision to software inventions has been anything but consistent. Does the USPTO’s action signal a need for Congressional action or another Supreme Court decision with more concrete guidelines?
In Alice, and as explained by the recent USPTO Preliminary Examination Instructions in view of the Supreme Court Decision in Alice, the determination of subject matter eligibility involves a two part test: (1) Is the claim directed to an abstract idea? (2) If so, are there other elements in the claim sufficient to ensure that the claim amounts to significantly more than the abstract idea itself?
However, rather than a rigorous application of any test, in the past few months the USPTO’s patent-eligibility determinations contain little analysis of any specific claim language. Instead, they primarily consist of a boilerplate paragraph stating that the claimed invention is directed to an abstract idea.
To illustrate this problem, the USPTO recently issued a rejection asserting that the following claim was patent-ineligible because it is directed to a “fundamental economic practice:”
8. A device for predicting a future occurrence of a transportation system incident, the device comprising:
a processor; and
a computer readable medium operably connected to the processor, the computer readable medium containing a set of instructions configured to instruct the processor to perform the following:
collect historic operating information related to the previous operation of a vehicle along a transportation route,
determine schedule deviation information for the transportation route based upon the historic operating information and observed schedule adherence for the vehicle along the transportation route, the schedule deviation information comprising at least an identification of a driver and a sequence number for a period of time associated with the historic operating information and the observed schedule adherence,
construct a plurality of models, each of the plurality of models including at least one combination of factors that contribute to schedule deviation,
rank each of the plurality of models according to at least one information criterion,
assess an impact of the driver and the sequence number on a highest ranked model to produce a results set, wherein the results set comprises at least a highest ranked model showing at least one combination of factors that most contributes to schedule deviation, and
present the results set. Continue reading