Many firms and businesses utilize some kind of applicant tracking system to whittle down potential candidates from a list of hundreds of applicants. Some startups want to take the hiring process one step further with special computer programs that lead to the automated hiring of candidates. These complex algorithms may eventually save firms time, money and hiring snafus.
New companies such as Gild, Textio, Doxa, Entelo and GapJumpers intend to test the notion that computer algorithms can pick out the best possible candidate without human involvement. This automated hiring process has the potential to create several advantages in the workplace, including more diversity, better skills matching and lack of human biases.
Some recruiting firms already have some kind of automated hiring beyond applicant trackers. These companies believe computers can vet potential candidates without managers' bias of potential underlings who attended the same school, lived in the same region or knew the same people. These criteria do not necessarily mean someone is a good fit for a company. Instead, this may mean the person wants to hang out with the candidate 40 hours per week because they feel comfortable with the new hire.
Yet other firms would rather rely on gut instinct and whether a person simply "feels" right for the job. Automated hiring algorithms cannot get inside someone's thoughts, feelings and charisma as they sit in front of interviewers to make a case for a position. Potential hires can fool an applicant tracking system with stuffed keywords that do not jive with someone's actual background. Once candidates realize the entire hiring system contains automated systems, someone may eventually find ways around those programs as well. An applicant tracker — along with a hiring algorithm — must have the right amount of limiting and disqualifying criteria to work properly without going overboard. Finding this balance takes time and tweaking for each piece of software.
Middle-of-the-road researchers take a combination view. They believe interviewers should observe potential hires in on-the-job scenarios, while vetting them with computer data, to make a final assessment. Interviews should have structure so that interviewers ask the same questions of every candidate regardless of someone's background.
Gild focuses its automated hiring algorithm on finding candidates that fit criteria regardless of socioeconomic background. These tech startups want to discover hires for tech companies since the industry has a ton of job openings without potential candidates. The industry could use diversification, as women comprise just 10 percent of Twitter's technical employees, and just 15 percent at Facebook. Some women and minorities claim they feel uncomfortable in these company cultures that have a lot of homogeneity rather than diversity. Many large tech firms vow to change hiring practices, and these new algorithms represent one way to accomplish that feat.
When more companies use automated hiring programs to make decisions, firms can use the data to improve the system, make more money and keep employees longer. Recruiters, HR managers and hiring specialists should expect to see more of these types of computer programs in the coming years if these startups prove their success.
Photo courtesy of sakhorn38 at FreeDigitalPhotos.net
Become a member to take advantage of more features, like commenting and voting.
Register or sign in today!