“We are living during an era when, in the last decade, new and powerful technologies are emerging, and boldly so.”
In 1859, Abraham Lincoln noted that the patent system “… has secured to the inventor, for a limited time, the exclusive use of [an] invention; and thereby added the fuel of interest to the fire of genius….”
President Lincoln knew what he was talking about. He’s the only U.S. president who received a patent, No. 6,469, in 1849.
And while others may have suggested it, Lincoln’s words need to be showcased somewhere (anywhere) at the Lincoln Memorial. Visitors to Lincoln’s Memorial should know that he cared about inventors, as well as preserving the Union.
To those words of his, I would note that the number of issued patents has reached to some number that’s 11 million more patents than Lincoln’s No. 6,469, and in only the last 172 years.
Identifying Emerging Technologies
I’m fascinated by emerging technologies. I searched “emerging technologies” on Wikipedia, and found a main article, “List of emerging technologies,” and then a related set of examples.
The examples were Artificial Intelligence (“AI”); 3D Printing; Cancer vaccines; Cultured meat; Nanotechnology; Robotics; Stem-cell therapy; Distributed ledge technology (i.e., blockchain); and Medical field advancements.
I’ve already written about six categories of emerging technologies: AI in the form of deep learning on September 30, 2021; blockchain on November 9, 2021; quantum computing on November 20, 2021; and then three more categories: stem cells, robot, and edge computing on December 11, 2021.
For the sake of credibility, I’m a named inventor on patents that use either deep learning (7) or both deep learning and blockchain (1); and that last patent is the first issued patent – No. 10,095,992 – to use both deep learning and blockchain in the claims. Since then, and as of January 3, 2022, there are a total of 51 such patents. (My search is aclm/(“deep learning” or “deep neural” or “multi-layer neural”) and blockchain.)
For this article, I decided to investigate three additional categories: (“3D Printing” or “Additive Manufacturing,”) (“Genetic or “gene therapy” ) and Nanotechnology (“Nano”), and compute a bar chart for all nine categories.
Now, as you probably know, the Detailed Description in a patent application is intended to be the way that the pieces and parts of an invention are transferred to the public once a patent is in the public domain. Thus, teaching is a part of inventing.
Here’s how I compiled the data I will present. When I do an online search of the patent database that the United States Patent and Trademark Office (USPTO) provides I use the Field Name for “claim(s),” and the associated Field Code, which is ACLM (the lower case version, i.e., “aclm,” will work just as well).
Because deep learning went through several naming conventions over time, I used aclm/(“deep learning” or “deep neural” or “multi-layer neural”).
Next, a forward slash separates the Code from the Name. Thus, to assess how many patents used blockchain in the claims, I used the Advanced Search option and wrote aclm/blockchain, and clicked on the button (in the center of the page) for “Search.”
Note that the heading in the bar chart for Year 2000 & Years Before, I used the overall total from the search which did not include the issue date. Next, I calculated the total – going year by year — from 2001 to the last date in 2021 when new patents were announced (on December 28, 2021) and subtracted that total from the overall total.
Thus, I backed into the number of patents for Year 2000 & Years Before. In the bar chart that I’ll present next, I did not use any data for Year 2000 & Years Before.
Now, here’s where it gets interesting. Patents for either “deep learning” or blockchain have come from very few patents only 10 years ago, circa 2011. In the years since then, the growth has been explosive.
Quantum Computing jumped from 14 patents in 2016, then down to 6 patents in 2017, but then back up to 18 patents in 2018 and then to 45 in 2019, 76 in 2020 and 96 in 2021.
The Innovation Curve
But what I really wanted to see was whether there was an overall pattern by aggregating the nine emerging technologies. Yes, the sample size of nine categories is small. However, anything that’s “emerging” is likely to be small and the question is whether there’s a pattern.
I created a dataset for the categories and added the data vertically for each category and horizontally for each year.
Here’s the bar chart for the year-by-year pattern that I’ll call the Curve of Innovation Technologies, or C.I.T., as a tip-of-my-cap to one of my alma maters, the California Institute of Technology:
Note that the number of patents is under 1,000 for each year from 2001 to 2005, is just above 1,000 patents from 2006 to 2009; and barely reaches 2,000 in 2011.
But then the curve starts an upward trend and never stops growing. It goes over 4,000 patents in 2017, almost reaches 8,000 patents in 2020, and touches 9,000 patents in 2021.
That’s a jump from 1,928 patents in 2011 to over 9,000 patents in 2021 (9,030). Over the 21 years, the total number of patents in the bar chart is a whopping 60,569.
Conclusion: Taken together, there is a pattern, and we are living during an era when, in the last decade, new and powerful technologies are emerging, and boldly so.
Since this article is likely the conclusion of my effort to build up to an overall pattern, and likely my last article, at least for now, I’d like to thank Eileen McDermott for her editing prowess and IPWatchdog for publishing my efforts. Comments are welcome.
Image Source: Deposit Photos
Join the Discussion
3 comments so far.
Nick BrestoffJanuary 7, 2022 03:18 pm
To Greg, thanks for your question. First, the new categories were (genetic or “gene therapy”) and “Nano,” for a total of eight, not nine. I miscounted (“3D Printing” or “Additive Manufacturing”) because I had broadened the category.
Now to your question. I reviewed the datasets I compiled for each of the eight categories.
As for (1) 3D Printing or Additive Manufacturing, (2) Blockchain, (3) Deep Learning, and (4) Robot, the number of issued patents has gone up in each category and in every year since 2011.
(5) The number of issued patents for (Genetic or “gene therapy”) in the claims went down in 2015, then up or no change in every year between 2016 and 2020, and went down in 2021.
(6) Quantum Computing (as noted in the text) went down once in 2017 but has gone up in every year since then.
(7) As for “Nano” in the claims, the number of issued patents when down in 2016, up in 2017, down in 2018, up in 2019, and then down in 2020 and down again in 2021.
(8) Last but not least, the number of issued patents with “stem cells” in the claims was up in every year from 2011 to 2017, then down in 2018, up in 2019, down in 2020, and back up in 2021.
That said, the total of the number of patents issued to each of the emerging technologies was always dramatically up from their respective starting points in 2001.
As I was never a patent attorney, my only concern as an inventor was Alice. My fear evaporated after reading Bascom Global v. AT&T Mobility (CAFC, June 27, 2016) which noted that an alternative way to satisfy Alice was Step Two. With an “inventive concept,” an inventor could satisfy Alice. I thought I had an “inventive concept,” and started the filing process four days later, on July 1st. Thereafter, eight applications in 2017-2018 became eight issued patents.
In the data I compiled, and as I’ve recounted above, I do NOT see an internal pattern which, across the board, could be tied to the years when the KSR, Mayo, Alice or Oil States decisions were announced.
AnonJanuary 6, 2022 10:26 am
Mr. DeLassus sounds out in his inane view yet again.
The Alfred E. Neuman What Me Worry award for 2022 has an early favorite.
Greg DeLassusJanuary 5, 2022 04:10 pm
N.B., the more-than-linear growth rate in that bar chart. Do you see any discernible inflections in that growth rate following KSR, or Mayo, or Alice, or Oil States? Neither do I. Evidently, tech progress is much less sensitive to US patent law changes than some might fear.