Bridging the Gap: Between the Abstract and Real Worlds of Patent Eligibility Using the "Guideposts” of Bilski
George Mohler, a mathematician at Santa Clara University in California, believes he can forecast the time and place of crimes using substantially the same mathematical formulas or algorithms1 that seismologists use to predict the time and place of aftershocks from an earthquake.2 To test his idea, he and his team of researchers rewrote a computer program used by seismologists to calculate the likelihood of aftershocks. They seeded the rewritten program with Los Angeles Police Department (LAPD) 2004 burglary data representing thousands of residential burglaries that occurred in a region of the San Fernando Valley, one of the city`s largest districts.
Programmed with the algorithm, a computer calculated which city blocks were most likely to experience the highest number of burglaries the next day. Specifically, the computer predicted which 5 percent of homes within that area were at particular risk of being burglarized. In one test, the program accurately identified a high-risk portion of the city in which, had it been adequately patrolled, police may have been able to prevent a quarter of the burglaries that took place in the area that day.
If Mr. Mohler wishes to patent his idea by filing a patent application, he and his patent attorney or agent must have a clear understanding of how to travel between the world of unpatentable, abstract ideas and the real world of patent eligibility of such ideas. This patent issue was the subject matter of last year`s United States Supreme Court case Bilski v Kappos.3
Read the entire Michigan Bar Journalarticle written by patent attorney Dave Syrowik
Original Publication: Michigan Bar Journal July 2011
1. In mathematics and computer science, an algorithm is a precisely stated method for solving a problem. Webster`s New World Dictionary, College Edition (1966).
2. Rubin, Stopping Crime Before it Starts, Los Angeles Times, August 21, 2010; The Aftershocks of Crime: An idea Borrowed from Seismology May Help to Predict Criminal Activity, The Economist, October 22, 2010.
3. Bilski v Kappos, US ; 130 S Ct 3218; 177 L Ed 2d 792 (2010).