Ben Mones, chief executive of social media screening startup Fama Technologies Inc., said hiring managers in today’s workplaces are becoming increasingly wary about what prospective employees may be posting online.
“We’ve all seen ‘fired for racist tweet’ headlines,” Mones said. “If you just Google that, you’ll see a litany of stories from over the years.”
Fama provides clients with digital tools that allow them to screen public-facing social media accounts associated with a potential hire. Using language processing and image recognition technology, Fama’s software identifies particularly volatile content, such as posts containing racial slurs or online bullying.
“It’s not a score on an individual, or a thumbs up or thumbs down,” Mones said. “Instead we allow clients to say, ‘Hey, I need to know about any references to threats, intolerance, harassment that this person has been posting online.’ And we enable them to bring those insights into their talent screening process.”
Employer surveys suggest demand is high for this type of service. According to a 2018 report from online recruitment company CareerBuilder, roughly 70% of employers say they use social networking sites to research potential employees before making an offer. Nearly 60% of those employers who do screen candidates’ social media accounts said that they had discovered content that convinced them not to hire someone, according to the same survey.
When Fama launched in 2015, Mones said many companies had already begun looking into the online activity of job applicants, though most were doing this process manually.
Not only is this process slow, Mones said, it can give people making hiring decisions access to information that might unfairly bias them against a candidate.
“If you’re a hiring manager and you see that a person is pregnant or disabled when you’re running that check, you’ve seen something you’re not supposed to see,” Mones said.
Fama’s technology, which can be integrated into background checks provided by established operators like HireRight and Sterling Infosystems Inc., parses through public posts, flagging items based on search parameters defined by clients.