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The Future of Patent Automation

At Fenix.AI, our vision is to change the way patents are drafted across the world. To understand where we are, where we have been, and where we are going, it is useful to think of patent automation in terms of different stages. For example, you may be familiar with the 5 levels of autonomous vehicles:

Each of the levels will be described in terms of the impact on claims, specification, and drawings. So, without further ado:

Levels of Patent Automation

Level 0 — No Automation

Self-explanatory. A patent lawyer drafts claims and specification from scratch, and often pays a draftsman to do drawings.

Level 1 — Templates

Level 2 — Claim Propagation

Level 3 — Dynamic Description

Level 4 — Intelligent Assistance

Level 5 — Full Automation

Where We Are Now

Although there are a few patent attorneys remaining that make no attempt to systematize their efforts, I believe that the vast majority of us operate somewhere within Level 1. This is what I found when I started working as a patent attorney. The system I learned on included quite sophisticated set of templates and libraries.

Still, I got bored pretty quickly by the hours of cutting and pasting that were typically required once you had drafted an initial claim set. So, within about six months I had developed my first Level 2 system. Others have been working on similar projects for years. Here is an example of a patent for an early patent automation system.

Initially, my system worked from within a MS word document. It identified the claims and generated some additional content based on them. In fact, the first version I wrote was in Visual Basic, and was affectionately referred to as “The Macro” by colleagues who knew what I was doing.

Currently, the growing patent automation industry has mostly moved from Level 2 to Level 3. One of the key things to look for in a Level 3 system is identification of a correspondence between apparatus components and steps. Providing the system with information about which parts perform which functions is the first step toward generating more substantial content for the detailed description. Then instead of just repeating the claims, new sentences can be generated describing the function of each component.

Another thing to look for in a Level 3 system is whether system takes into account relationships among components and method steps. For example, can it identify that a dependent claim is describing substeps for a particular limitation of an independent claim instead of just adding additional steps on the end?

We haven’t really reached Level 4 yet, but some of these features are within reach, and they aren’t too far off. Level 4 basically represents the application of cutting edge AI capabilities to the patent automation context (i.e., instead of off-the-shelf NLP tools).

Level 5 is probably a ways off. Drafting claims is an art, and it might just require sophisticated artificial general intelligence to match the skill of an experienced patent attorney. And since a lot of the skill of a patent attorney goes into crafting claim 1, it will be a while before computers can outperform humans in this area. Of course, for some lower tier patents, outperforming humans might be the wrong standard.

So, given this framework for understanding the past, present, and future of patent automation, it is time to ask where you are in your own practice? And where do you want to be 2 years from now? Tools for Level 3 automation are becoming widely available. Those who insist on preparing every aspect of a patent manually will soon find it difficult to remain competitive.