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Oct 17, 2022Legal
A Computer Method Claim Must Improve the Functions of the Computer to Survive § 101

INTERNATIONAL BUSINESS MACHINES CORP. v. ZILLOW GROUP, INC.

Before Hughes, Reyna, and Stoll.  Appeal from the United States District for the Western District of Washington.

Summary: A patentee’s allegation that computer method claims made data analysis more efficient, without reference to the function or operation of the computer itself, was not sufficient to overcome a challenge under 35 U.S.C. § 101.

International Business Machines (“IBM”) sued Zillow for infringement of several patents directed to the graphic display of data on a computer.  Zillow moved for judgment on the pleadings, arguing that several of the asserted patents were directed at ineligible subject matter under 35 U.S.C. § 101.  The District Court granted Zillow’s motion as to two patents, finding the patents ineligible.  After applying the two-step framework in Alice, the District Court found the patents were “directed to abstract ideas, contain[] no inventive concept, and fail[] to recite patentable subject matter.”  IBM appealed.

On appeal, IBM argued that the District Court erred in finding that the claims lacked an inventive concept under the second step of the Alice framework.  IBM pointed to an expert declaration stating that the claimed method allowed for better visualization of data, which in turn resulted in more efficient data analysis.  The Federal Circuit disagreed, finding that any improved efficiency came from the mere application of an abstract idea rather than an improvement to the functions of the computer itself, as the claims could be performed by hand and would yield the same improved efficiency.  Accordingly, the Federal Circuit affirmed the District Court’s finding that the two patents were ineligible under 35 U.S.C. § 101.

Judge Stoll dissented in part, arguing that IBM had adequately alleged that two of the claims were patent eligible.  Judge Stoll reasoned that the claims addressed physical limitations with computer displays wherein large datasets would be “densely packed” and rendered “incomprehensible.”

Editor: Paul Stewart

Written by: Steven N. Friedland & Justin J. Gillett

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