AI recruitment software is 'automated pseudoscience' Cambridge study finds
Claims that AI-powered recruitment software can boost diversity of new hires at a workplace were debunked in a study published this week.
Advocates of machine learning algorithms trained to analyze body language and predict the emotional intelligence of candidates believe the software provides a fairer way to assess workers if it doesn't consider gender and race. They argue the new tools could remove human biases and help companies meet their diversity, equity, and inclusion goals by hiring more people from underrepresented groups.
"The fact that changes to light and saturation and contrast affect your personality score is proof of this," Kerry Mackereth, a postdoctoral research associate at the University of Cambridge's Centre for Gender Studies, toldhow wearing glasses and a headscarf in a video interview or adding in a bookshelf in the background can decrease a candidate's scores for conscientiousness and neuroticism, she noted.
Mackereth also explained these tools are likely trained to look for attributes associated with previous successful candidates, and are, therefore, more likely to recruit similar-looking people instead of promoting diversity. "Machine learning models are understood as predictive; however, since they are trained on past data, they are re-iterating decisions made in the past, not the future. As the tools learn from this pre-existing data set a feedback loop is created between what the companies perceive to be an ideal employee and the criteria used by automated recruitment tools to select candidates," she said.
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