Jun 16 2021
To print this article, simply register or connect to Mondaq.com.
A question that is often asked is why are there so many lawyers? The question is often associated with questions about why lawyers spend so much time on seemingly insignificant tasks and why they are always busy and have a poor work-life balance.
While this issue is not unique to the legal industry, it tends to be particularly important to lawyers due to the level of detail required by the job. Most tasks require a plurality of checks to ensure that there are no errors. For example, in patent lawsuits, filing responses to Office actions issued by the United States Patent and Trademark Office and preparing preliminary amendments for new patent applications often requires many detailed steps. .
When preparing responses to each Office action, the main focus is on amending claims and / or arguing against Office action to overcome objections and rejections. When amending claims, word choice and phraseology are very important, and many checks are made to ensure that USPTO formality requirements are met. For example, it is important to check claim identifiers, antecedent base, and grammar to ensure that claims conform to drafting arguments. In the arguments, every sentence and every paragraph will be considered to ensure that the discussion and reasons presented are concise, yet compelling, fully addressing the points raised in the Office’s action.
Even so, each case is unique with different steps required to draft the documents. Since each case may require different approaches, the prioritization of steps may vary. To effectively prioritize these steps and work efficiently, practitioners are increasingly turning to artificial intelligence to manage some of the steps in patent prosecution.
For example, there is a service that provides AI-based patent writing software that automates and improves patent writing for practitioners. There is also software that can recognize “terms” used in the specification, claims and drawings, throughout an application, so that the same terms are automatically suggested and consistently updated throughout the application. ‘application. In addition, there is software that can perform automated claim renumbering when constructing a set of claims.
Law firms are also developing AI-based drafting software in-house. Examples include AI patent drafting tools, which use machine learning and artificial intelligence to consistently draft high-quality patent applications. At Oblon, we internally created an AI model using Python to predict § 101 releases by merging two USPTO datasets: USPTO PatentView and the USPTO Office Action Research dataset. Oblon’s AI tool predicts § 101 rejections with a 90% confidence level.
In addition to taking charge of drafting requests, artificial intelligence can assist in drafting office action responses and draft amendments. Checking claim IDs and resolving basic background issues are great for automation because these tasks are repetitive and require consistency. However, artificial intelligence is capable of more than just automated tasks. For example, it may be possible to use machine learning to learn a writer’s writing habits and to automatically suggest words (verb tenses, punctuation, etc.) to the writer while writing arguments. .
However, there are many substantive issues, such as word choice in claim modifications and the development and flow of arguments, that will still require human decisions at this time. Other tasks also require a human. For example, to increase the chances of compensation, practitioners often conduct interviews with reviewers to understand how reviewers read and interpret the language of the claim. Since each reviewer has unique personalities and preferences, it is important and beneficial to interview reviewers to develop arguments in Office Action responses. While artificial intelligence may one day interface with reviewers, for now human interactions and communication are required.
For the foreseeable future, it looks like the use of artificial intelligence in the legal field will remain as an assistive tool helping practitioners to perform tasks such as drafting patents while leaving some more abstract tasks to be carried out. of the practitioner. This application of artificial intelligence to the legal field will help lawyers manage transactional work such as patent lawsuits in a much more effective and efficient manner.
The content of this article is intended to provide a general guide on the subject. Specialist advice should be sought regarding your particular situation.
POPULAR POSTS ON: US Technology