In Silicon Valley, Searching for Diversity in an Algorithm
If any industry were going to use tech-savvy algorithms to hire more minorities, it makes sense it would be Silicon Valley.
With Google (NASDAQ:GOOGL) stirring the pot in the world's largest tech hub by releasing astonishingly one-sided diversity figures last month, one recruiting firm is claiming to have an answer.
Entelo, the three-year-old tech recruiting database that scrapes the Internet for public data to be used by employers for recruitment purposes, says its newly-unveiled diversity tool enables companies to weed through potential job candidates and search for minorities.
While it has been criticized by some as reverse discrimination, CEO Jon Bischke says it is not only completely legal but much in demand by some of Entelo’s major corporate clients as social pressures mount.
“A number of our customers have approached us wanting to know if our data could help them find people from underrepresented groups,” said Bischke in an interview with FOX Business.
Google became the sector’s first heavyweight to voluntarily disclose its diversity stats two weeks ago, revealing a staff comprised of 70% men that is 60% white. It came at the persistent urging of Rev. Jesse Jackson, who for months has been pressuring Silicon Valley to be more transparent.
“We’ve always been reluctant to publish numbers about the diversity of our workforce at Google,” said Laszlo Bock, senior vice president of people operations at Google. “We now realize we were wrong.”
Mountain View, Calif.-based Google said its 46,000-person workforce is “miles” away from where Google would like to be. It blamed education, and touted its efforts to try and fix the problem such as sending engineers to historically black colleges to reinvent IT curriculums and investing in education for girls.
It gave little color as to how it would improve its actual recruiting efforts, but Google has a robust recruiting team that will likely hone in on this goal for the tech darling. The path is less clear for smaller companies that don’t have as many resources.
“My concern is the 99% of other companies who want and need diverse teams but don’t have the team to recruit them,” Bischke said. “This could help level the playing field.”
What Entelo provides is more than 20 million profiles of potential employees filled with publicly-available data pulled from sites like Twitter (NYSE:TWTR) and LinkedIn (NASDAQ:LNKD).
Its proprietary algorithms then sort through this information using big data, predictive analytics and social cues, to determine the likelihood that people fall into a number of demographic subsets: female vs. male, white vs. black, etc.. It also identifies U.S. military veterans.
"We realized we could do this with a high degree of accuracy,” Bischke said.
The idea is that it would help companies to more cost-effectively and efficiently scour a wider group of potentially ethnically-diverse and qualified candidates, freeing up resources to focus on innovation, training, and ideally develop these people into future industry leaders.
After all, Marissa Mayer, who started at Google (NASDAQ:GOOG) in 1999 as the company’s 20th employee and first female engineer, is now CEO of Yahoo (NASDAQ:YHOO).
As for the critics, Bischke says diversity recruiting is something employers have been doing “for years.” Entelo, he adds, is not set up in such a way that it fosters discrimination. Rather, he says it assists in finding less represented candidates.
“Our response [to the critics] is always, ‘We believe you should always hire the best person for the job,'" he said. "But we also believe you should hire a diverse person from a diverse group of applicants."
Elizabeth Ames, a vice president at the Anita Borg Institute for Women and Technology, told FOX Business she applauds Entelo's intention and believes there is a place for "applying computer science to assist in this process."
However, she also believes these efforts can and should stretch far beyond just algorithms.
For example, companies can write job descriptions to be gender neutral, use blind resume screening and accept referrals from women and minority employees.