Intelligence – undoubtedly the biggest virtue of humans over all other species – has evolved in true sense in last one decade where we have seen not only accumulation or growth of intelligence but also conferring of the intelligence to Machines by humans. Such is the power of "artificial intelligence" that in certain protocol related decisions based on Gigabytes of data evaluation, the machines possessing "artificial intelligence" is out performing humans by great margins. The performance is even better if we consider bulk data evaluations, which leads us to think about implementing artificial intelligence for issues relating to fact-based decisions or tasks but to be performed in very large numbers. This thought resulted in Governments also now considering effective mainstream use of blockchain, artificial intelligence (AI) and machine learning (ML) in their public processes that are otherwise manual or part-automated.

India's policy think tank organization, National Institution for Transforming India (NITI) Aayog recently issued a discussion paper1 on National Strategy for Artificial Intelligence. The paper explores use of blockchain and Artificial Intelligence (AI) in the governance of different departments of the Government of India and also for enabling several socialist reforms. Once implemented, this will be the world's largest blockchain implementation program in public governance.

The present article is limited to the implementation of the said Strategy by the Controller General in the patent administration. A recent tender2 was posted on the official website of the Indian Patent Office (IPO) giving Notice Inviting Expression of Interest (EOI) for making use of Artificial Intelligence (AI), Blockchain, Internet of Things (IoT) and other latest technologies in Patent Processing system of IPO. The said tender shows the clear intent of the Controller General to not only consider the expeditious implementation of the procedures but also to adopt the latest technology in order to achieve efficiency and high standards of implementation.

The proposed changes in the tender will dramatically improve user experience of IPO services, for instance, the Patent Office hopes to be able to forecast timelines for the applicants / agents during prosecution of the application for patent or trademark registration at different offices. The quality of the examination reports will also improve by use of AI and the examination reports can be more objective and direct. Formal requisites can be automatically checked under AI and the said process would greatly reduce the intervention of man-hours in formality checks at IPO. Similarly, a logically implemented work allocation protocol using the data and AI would greatly help in optimal use of human resources available with the IPO at different offices.

AI is also intended to bring in standardization in the issuance of letters, office actions, reports, and other official data. The same may include adoption of standard formats, tables, spreadsheet layout of information, timelines, etc. which will certainly raise the quality and at the same time speeding up the process considerably. Reduced manual intervention will also result in greater transparency and accountability in the processes in a positive way.

Some of the points where the IPO sees new technology being used in the patents process, stage-wise, has been included by the Controller General in the said tender:

  1. Filing: Potential use of block chain for streamlining registration through encouraging information sharing by rights holders, and assisting users in filing processes.
  2. Electronic Data Processing: Digitization and automation of application filing; improved OCR proofreading; tagging information in drawings; increasing the speed of information retrieval.
  3. Classification: Using natural language processing to understand patent documents and to automatically classify them; Software/machine learning capability to build sophisticated hierarchy of classification models to analyze the contents of each patent specification in unstructured PDF documents.
  4. Screening stage: Screening for specific types of subject matter, e.g., atomic energy; defence related subject matter.
  5. Publication: Automated formal checks and clearing the application for publication.
  6. Allotment: Allotting patent applications to examiners on the basis of technology, the workload of examiners, and so on; Rectifying disparities, such as, allowing processing on the basis of first to file rule as far as possible, keeping in view the different nodes functioning independently of each other.
  7. Prior art search: using AI and machine learning to formulate search queries; as human-assisted or semantic-based prior art searches; deep machine learning for Image searchability; single search interface for patent and non-patent literature
  8. Examination stage: Automatically checking formal requirements as per the Act and Rules; and a substantive examination based on inputs retrieved through the use of AI
  9. Pre-grant and Post-grant Opposition stage: Evaluating the inputs received
  10. Hearings stage: Capability to automatically evaluate amendments
  11. Others: Having an interactive response system for stakeholders; Automated user feedback; Using machine learning to answer IP policy and issues faced by policy makers; Data analysis; ensuring quality control; Determine sufficient evidentiary value to determine the rights of first filer in a First-to-File regime; Machine translation for English into other Indian languages and vice versa; Timeline predictions, and so on.

The tenders would have been submitted by the competing vendors and with the thrust of Government in modernizing or adopting new technologies, the IPO surely would take up the implementation of the above proposals seriously. Only time will tell how these AI and blockchain technologies are used for much required improvement in the examination quality of the patent applications. Nevertheless, one must applaud the brave step taken by the IPO towards becoming a more transparent and efficient patent system.




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