Startup Headstart is Getting Rid of Recruitment Bias in the Job Market

The company's AI algorithms take human bias out of the recruitment process, aiming to help all applicants get a fair shot.

19.11.2019 | by Reve Fisher
Photo by Cytonn Photography on Unsplash
Photo by Cytonn Photography on Unsplash

Diversity in teams often leads to great benefits for a company. Research has shown that diverse groups can be better at making decisions, and that companies that are highly diverse in terms of gender, race or ethnicity enjoy financial returns that are above the average in their industries.

However, recruiters often discriminate against job applicants, even without being consciously racist, sexist, ablest or otherwise discriminatory.

“In some ways people who have been successful in roles in the past become a prototype or reference point for success in our minds,” Siri Uotila, a research fellow at the Women and Public Policy Program at the ‎Harvard Kennedy School, said in an interview with the BBC. “If the majority have been white men, then it is more difficult to actively diversify the population.”

As the world’s first diversity-driven applicant matching and management system, London-based Headstart wants to “make recruitment fair for everyone.” According to the company’s website, Headstart isolates the potential for bias at every stage of the recruitment process and has reduced bias by 15 percent for Asian applicants and 18 percent for Black applicants.

Headstart’s platform has also been designed to expedite candidate screening and reduce the time to hire by up to 70 percent.

“The machine — the algorithms and models — does this without emotion; fatigue; or overt subjective, conscious, or subconscious opinion or feeling. Unlike a human,” co-founder and chair Nicholas Shekerdemian told VentureBeat.

First, Headstart gathers information from the hiring company, including the job description and current employee data. The internal information is then reviewed for built-in bias to be addressed in future hiring campaigns. The platform also collects publicly available data from across the web, such as job descriptions and roles, as well as demographic and social-oriented data.

“We use this data to determine if any individual has had any obvious social disadvantage and [has] possibly outperformed their social norm group,” Shekerdemian explained.

Then, the candidates’ information is incorporated into the programme, such as their CVs, psychometric assessments and other screening tools.

“The machine doesn’t consider the candidate’s name and, subconsciously, degrade that applicant’s value because of unconscious bias toward ethnic origin or gender,” Shekerdemian said. However, he recognises that algorithms need to be iterated, trained, retrained and reviewed to be as fair and effective as possible, citing the Amazon recruitment case that ultimately trained its AI recruitment tool to prefer men.

Humans make the final decisions, but Headstart claims that up to 20 percent of human bias is removed through the platform and that all applicants are given a fair shot.

“The technology, used appropriately, can expose and largely eliminate this bias, simply because it doesn’t get to the 50th CV it’s seen that day and then skip through the next 100 because they are tired and need to get a shortlist to the hiring manager and a bunch of the first 50 were ‘good enough,'” Shekerdemian said.

The Y-Combinator alum has raised $7 million in a seed round of funding led by FoundersX with participation from Founders Factory.

“When we came to market two years ago, we were probably the only technology company talking about fairness and diversity,” said Headstart CEO Gareth Jones. “For me, this represents an investment in diversity, not just our company.”

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