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Artificial Intelligence and Subject Matter Eligibility In U.S. Patent Office Appeals
Artificial intelligence is changing industry and society, and metrics at the U.S. Patent and Trademark Office (USPTO) reflect its impact. In a recent publication, the USPTO indicated that from 2002 to 2018 the share of all patent applications relating to artificial intelligence grew from 9% to approximately 16%. See "Inventing AI, Tracing the diffusion of artificial intelligence with U.S. patents," Office of the Chief Economist, IP Data Highlights (October 2020). For the foreseeable future, patent applications involving artificial intelligence technologies, including machine learning, will increase with the continued proliferation of such technologies. However, subject matter eligibility can be a significant challenge in securing patents on artificial intelligence and machine learning.
This article explores USPTO handling of Alice issues involving artificial intelligence and machine learning through a sampling of recent Patent Trial and Appeal Board (PTAB) decisions. See Alice Corp. v. CLS Int'l, 134 S. Ct. 2347 (2014). Some decisions dutifully applied USPTO guidelines on subject matter eligibility, including Example 39 thereof, to resolve appeal issues brought to the PTAB. In one case, the PTAB sua sponte offered eligibility guidance even with no Alice appeal issue before it. These decisions inform strategies to optimize patent drafting and prosecution for artificial intelligence and machine learning related inventions.
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The DOJ's Corporate Enforcement Policy: One Year Later
The DOJ's Criminal Division issued three declinations since the issuance of the revised CEP a year ago. Review of these cases gives insight into DOJ's implementation of the new policy in practice.
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