How machine learning can course-correct inherent biases in recruiting

Machine learning can help mitigate the biases present within organisations’ recruiting practices

Artificial intelligence has often been portrayed as dystopian when it comes to human resources. In one famous example from 2018, Amazon used it significantly in the hiring process but ultimately had to pull the plug when it was revealed that the algorithm was biased against women. The AI was identifying candidates who used masculine words as successful candidates, and instead of addressing this flaw, it reinforced sexism.

Yet technology has come a long way in just the last few years. Machine learning is now being used to tackle the problem of bias within hiring decisions, not just looking coldly at performance metrics. Companies have developed software that can intelligently analyse candidates beyond surface-level use of words. This helps to match capable candidates with the companies that value their skills.

Ilit Raz, the CEO of Joonko, is a leading expert in HR technology. With offices in New York and Alabama, her company is pioneering diversity-driven recruiting, with its own AI-powered solution that helps to match candidates to positions.

Diversity, equity and inclusion (DE&I) is an issue close to her heart, after experiencing firsthand how the odds were stacked against women in the tech industry. It was through conversations with her peers that Raz realised how widespread the concern was and decided to take on the problem of bias in HR decision-making herself.

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