Korean Intellectual Property uses AI to improve digital patent trial and appeal systems and increase procedural review efficiency

The Korean Intellectual Property Office KIPO will improve the digital patent trial and appeal system on December 18, 2023, with the purpose of improving services and work efficiency. The new functions provided by the digital system make online patent review more convenient. Applicants can fill out and submit forms online to submit patent trial applications and procedural reviews to the Korean Intellectual Property Trial and Appeal Board IPTAB. KIPO plans to establish a highly advanced patent trial system through artificial intelligence, automation and other emerging digital technologies within three years from 2023 to 2025.

KIPO has improved its electronic filing website Patent-Ro and added new features that allow applicants to easily and accurately fill out the fields of the electronic form. Once the applicant enters key information, such as the number of the patent applicant, trial case or documentary evidence, proof If you are the legal right holder or party, the system will automatically use the saved information to enter the field. In addition, the system checks for errors and notifies applicants of any spelling errors or missing documents before they hit submit, features that reduce revisions or corrections due to poorly prepared document formats. It is allowed to upload evidence materials not exceeding 200M at one time.

KIPO uses AI to improve IPTAB’s work efficiency and productivity. Before the IPTAB decides to accept a case, it will conduct a procedural review of all documents submitted by the parties to determine whether the documents submitted by the parties comply with the regulations and whether the information provided is presented in the correct format or method. There are 171 types of documents that the examiner may want to check. Different types of documents, including some image files that require manual screening, therefore KIP uses OCR technology to automatically identify the information in the image files and generate automatic inspection results for manual review, thereby reducing the workload of the examiner. .