Diffbot’s A.I. Engine Draws Global Map of Machine Learning Expertise

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expertise of a candidate through traditional means such as interviews and testing, Tung says.

Once the machine learning experts were compiled as a cohort, Diffbot’s group data could be sorted out by various factors, such as national origin, place of current employment, gender, education, and professional background, Tung says.

For example, Diffbot found that women make up a bit more than 24 percent of U.S. machine learning experts—a gender diversity score that was lower than that in China and four other countries. More than 51,000 women are employed as machine learning professionals in the United States, Diffbot found. Tung says this identified talent pool could be a hiring resource for companies trying to correct a gender imbalance caused by institutional bias.

With its 221,592 experts, the United States employs 30.8 percent of the global talent pool in machine learning, followed distantly by India, where 59,980 are employed, Diffbot found. Ranked next are the United Kingdom, Canada, China, and France. If California were a country, it would rank above India. It employs 74,791 machine learning professionals—more than New York, Texas, and Massachusetts combined.

In U.S. hiring, Google and Microsoft led the pack, with more than 4,000 machine learning experts each. That’s about four-fold higher than Apple’s count of 1,064, Diffbot reported. Tung says that financial analysts who track the market for technologies involving machine learning might use Diffbot’s engine in a search for correlations between expert staff strength and the performance of new products.

The Diffbot data may also provide some insights to add to the public discussion of a possible “A.I. war” between the United States and Asia, Tung says. The company’s report found that five of the top ten universities producing global talent in machine learning are in China. But the employment pattern suggests a “brain drain” from China. Among graduates from those Chinese university programs, more than 62 percent work in the United States, Diffbot found.

“In the study, most of U.S. A.I. research is being carried out by Chinese or Indian nationals,” Tung says. “A.I. development in the U.S. is very co-dependent on Asia.”

Tung raises a caveat to Diffbot’s findings about staff strength in China, however, because A.I. experts in China are less likely than U.S. professionals to create online materials that Diffbot can scan, such as their own Web pages.

Diffbot’s report doesn’t resolve a burning question about the A.I. job market: How big is the shortfall between the number of trained professionals and the number of open jobs? That widely held perception of a significant candidate shortage has helped drive up compensation for A.I. experts.

Tung says Diffbot doesn’t yet capture structured data about jobs and job postings—but it plans to, he says.

“It’s on our roadmap,” Tung says.

Photo courtesy of Diffbot

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