Coding More Women And Minorities Onto Tech Rosters

The media has recently latched onto the idea that the tech industry needs more diversity, publishing story after story on the hardships and outright sexism of the valley. [...] affirmative action is again a national talking point after a divided U.S. Supreme Court this week ruled that states can bar public universities from raced-based admissions. Next week, the company plans to start a service that allows companies to identify potential candidates who are female, Latino, African American or military veterans, among other groups, by mining data from social media sites like Facebook, Twitter and LinkedIn, or profession-specific networks like GitHub, a popular destination for engineers. According to a recent study by the Center for Talent Innovation research firm in New York, 32 percent of women in science, engineering and technology say they are likely to quit their jobs within a year partly because of "isolation." Entelo has created an algorithm that determines the probability that potential candidates come from a certain background by analyzing the data they upload to social media sites. Bischke won't say what exact factors influence the results, but cited some intuitive examples like membership in certain professional organizations or whether they attended women's colleges, like Barnard, or historically black universities, like Howard.