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Artificial Intelligence for Mitigating Patent Process Hurdles

Authors :
Deepti Hegde
Suneeta Hegde
Source :
International Journal of Engineering Research in Computer Science and Engineering. 9:50-53
Publication Year :
2022
Publisher :
Technoarete Research and Development Association, 2022.

Abstract

New thrust by the government to develop skill sets and entrepreneurship has resulted in massive inventions and rapid advancement of science and technology. complexity in monitoring, managing adapting, and registering innovations is becoming increasingly difficult due to a massive number of inventions. Maintaining standards for new innovations along with increased time for their scrutiny is causing delays in the adaptation of new inventions. The Intellectual property rights scrutiny towards judging the uniqueness of a particular innovation and prior art search has been made considerably easy by using artificial intelligence and machine learning. This latest technology can help to overcome the cumbersome processes for the allotment of intellectual property rights. This technology eases the burden of managing a large number of innovations filed as patent applications. Data mitigation becomes easy in the area of prior art searches. The world trade organization has announced certain stipulations in the form of law to avoid overlapping of the inventions and grant patents in line with the geographical restrictions. This article makes a concrete proposal to understand the complex interrelationship between trade law, jurisprudence, and the application of artificial intelligence in overcoming the hurdles concerning the patent grant process. The paper also proposes the use of artificial intelligence for patent-related dispute settlement in line with Trade-related aspects of intellectual property rights agreements. The paper advocates the use of artificial intelligence in the area of application and grant of patents.

Details

ISSN :
23942320
Volume :
9
Database :
OpenAIRE
Journal :
International Journal of Engineering Research in Computer Science and Engineering
Accession number :
edsair.doi...........8b317c5c5bef15c5a3becc78bd5b9c69
Full Text :
https://doi.org/10.36647/ijercse/09.10.art011