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Artificial intelligence is coming for hiring, and it might not be that bad Posted on Aug 10 - 2018

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Artificial intelligence can make hiring an unbiased utopia, its advocates assert.

There’s certainly plenty of room for improvement. Employee referrals, a process that tends to leave underrepresented groups out, still make up a large part of companies’ hires. Recruiters and hiring managers also bring their own biases to the process, studies have found, often choosing people with the “right-sounding” names and educational backgrounds.

Across the pipeline, companies lack racial and gender diversity, with the ranks of underrepresented people thinning at the highest levels of the corporate ladder. Fewer than 5% of chief executives at Fortune 500 companies are women, and that number will shrink further in October when Pepsi CEO Indra Nooyi steps down. Racial diversity among Fortune 500 boards is almost as dismal, as 4 out of 5 new appointees to boards in 2016 were white. There are only three black CEOs in the same group.

“Identifying high-potential candidates is very subjective,” said Alan Todd, chief executive of CorpU, a technology platform for leadership development. “People pick who they like based on unconscious biases.”

AI advocates argue the technology can eliminate some of these biases. Instead of relying on people’s feelings to make hiring decisions, companies such as Entelo and use machine learning to detect the skills needed for certain jobs. The AI then matches candidates who have those skills with open positions. The companies claim not only to find better candidates but also to pinpoint those who may have previously gone unrecognized in the traditional process.

Stella’s algorithm only assesses candidates based on skills, said founder Rich Joffe. “The algorithm is only allowed to match based on the data we tell it to look at. It’s only allowed to look at skills, it’s only allowed to look at industries, it’s only allowed to look at tiers of companies.” That limits bias, he said.

Entelo recently released Unbiased Sourcing Mode, a tool that further anonymizes hiring. The software allows recruiters to hide names, photos, school, employment gaps and markers of someone’s age, as well as to replace gender-specific pronouns — all in the service of reducing various forms of discrimination.

AI is also being used to help develop internal talent. CorpU has formed a partnership with the University of Michigan’s Ross School of Business to build a 20-week online course that uses machine learning to identify high-potential employees. Those ranked highest aren’t usually the individuals who were already on the promotion track, Todd said, and often exhibit qualities that are overlooked during the recruitment process.

“Human decision-making is pretty awful,” said Solon Barocas, an assistant professor in Cornell’s information science department who studies fairness in machine learning. But we shouldn’t overestimate the neutrality of technology, either, he cautioned. View More


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