Artificial Intelligence (AI) is making waves in every corner of the world, and women are playing a significant role in this revolution, especially in the field of biotechnology AI, according to a recent study published in Nature. The study, titled Discovering value: women’s participation in university and commercial AI invention, used PatentsView data to identify the gender of inventors before using World Intellectual Property Organization categories to determine which patents contain AI. 

It was written by Alexander Giczy, Nicholas Pairolero, and Andrew Toole.

More Women are Participating in AI Innovation

The study found that women are making significant contributions to AI innovation, but there is still work to be done to ensure that people from many different backgrounds are participating in the development of AI.

The authors analyzed the women as inventors rate (WIR), which is a measure of the number and share of people receiving patents who are women. They found that the overall number of women inventors who received AI-related patents has increased from around 500 per year in 1995 to around 9,000 in 2020. The WIR for AI inventions increased from 10.1% to 12.6% in the same time frame.

“These results show that women are not only participating in AI invention but are doing so at a slightly higher rate than in non-AI technologies,” the authors said in the study.

They found differences in the AI WIR based on sector (e.g., AI and biotechnology), and whether the inventors worked for companies or universities.

The Value of Women Inventors

The authors noted research showing that diverse teams are more likely to improve innovation and business performance by looking at problems from different perspectives. Testing that theory, they found that teams with a higher proportion of women tended to be associated with higher economic value of granted patents. 

“While such an analysis does not imply causation, the value of the patent is higher for teams with relatively more women: a patent with an equal number of male and female inventors has a value approximately $1.038 million higher than a patent with all-male inventors,” the authors said in the study.

How PatentsView Can Help

This study contributes to a growing body of research that shows how important diversity is for innovation and emerging technologies. To thrive and grow in the future, everyone must be able to participate in innovation and patenting, regardless of their background. Tools like PatentsView can help us track our progress and identify areas where we can improve.

You can explore more on this topic on PatentsView’s Gender & Innovation and AI & Innovation pages.

AI & Innovation and Resource Pages Now Available

As we start a new academic year, PatentsView is working to help researchers better understand the relationships across various patents and innovative technologies. To that end, we’ve launched two new pages: a topic page on Artificial Intelligence & Innovation, and a new Resources page.

The Artificial Intelligence & Innovation Patent Dataset

While artificial intelligence (AI) has advanced by leaps and bounds, researchers are still working to understand the many ways AI inventions and innovations have impacted technology and society. To help researchers delve into how this emerging technology is affecting our lives, the United States Patent and Trademark Office (USPTO) released the AI Patent Dataset (AIPD).

The dataset includes an analysis of 13.2 million patent documents published through 2020, identifying which patents contain AI. The AIPD integrates seamlessly into PatentsView, allowing researchers to explore relationships between patents related to AI and the companies and inventors who hold them.

What’s on the new AI & Innovation page?

The new page contains an interactive data visualization that allows users to explore how patents are related to government interest, a deep dive into the machine learning model used to create the AIPD, and the latest AI-related news and reports.

Visit the new AI & Innovation Page now to find out more.

What’s on the new Resources page?

The new PatentsView Resources page provides patent researchers, inventors, and intellectual property afficionados an easy way to find code snippets and packages to better use the PatentsView API, sources to help researchers use BigQuery to explore historical patent and PatentsView data, Zenodo links between patents and scientific articles, and more.

You can also find information about the I3 Collaborative and IPRoduct repositories. I3 and IPRoduct are working groups for users to contribute to data frames and named data projects as well as export collaboratively made datasets. IPRoduct focuses on connecting patents to products in support of intellectual property rights, and I3 is a project to connect citations and patents among patenting groups worldwide.

Get connected on the new Resources page.

Throughout recent decades, the role of artificial intelligence (AI) in the modern world and the lives of its inhabitants has increased drastically. From advancements in cybersecurity and military technologies to AI-driven greenhouses and algorithms that help health-care workers develop better treatments, AI has made its way into nearly every sector of society.

The future of AI innovation and its influence on society will only continue to grow. It is with this in mind that the U.S. Patent and Trademark Office (USPTO), Office of the Chief Economist released a new report, titled Inventing AI: Tracing the diffusion of artificial intelligence with U.S. patents. This report details research conducted by USPTO in which a machine-learning AI algorithm was used to determine the volume, nature, and evolution of AI and its component technologies as contained in U.S. patents from 1976 through 2018.

A main goal of USPTO’s research was to measure the technology diffusion of AI with patent data. Technology diffusion is the process by which a technology is adopted by inventors, organizations, and other innovators as it spreads across different markets. In this report, USPTO details the methods it developed to identify the scope of such diffusion as it relates to AI and its component technologies.

Patent data are extremely useful for such an analysis as they can give direct insight into the spread and adaptation of a technology or method. When a new, powerful innovation or technology such as AI is created, the speed at which it is adopted by inventors and organizations alike can partially be seen by the increase in patent applications filed and granted with reference to said technology. Figure 1 shows the growth of AI-related patents as a percentage of all U.S. patents by year. In the figure we can see a dramatic increase in AI patents, from less than 5% in 1980 to greater than 20% in 2018—a truly staggering growth in just under 40 years.

Figure 1. U.S. Inventor and Owner of AI-Related Patents: Percentages From 1975 to 2020

In addition to the number of patents filed, patent data are useful in this research because each patent document contains detailed information and metadata. The person or organization that filed the patent, the technological classification of said patent, the location the patent was filed in, and so forth can all be found in one document.

The role of AI moving forward will be determined by the willingness and ability of inventors to continue working with and innovating on the technologies of today. Although we cannot know for sure just how much of an impact AI will have on our future, research into the scope and diffusion of its technologies can give us a glimpse of what is to come.

More information on the diffusion of AI as well as the AI method used to identify AI patents is available in the USPTO report.