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Machines are biased. Why? Because humans are biased and humans teach machines. With artificial intelligence being integrated into HR departments in an effort to take the bias out of hiring, we need to take a step back and ensure we’re taking the bias out of AI.
HiringSolved, a startup that created the first “Siri-like” AI-powered assistant to help recruiters identify talent and build a diverse workforce, is working on just that with an update to their tool, RAI (Recruiting Artificial Intelligence, pronounced “Ray”). Used by companies such as Staples and Luxottica, RAI has now integrated voice recognition features to make it easier for recruiters to verbally set parameters to identify candidates, whether it’s by gender, skill, job experience or even veteran status. But how can we be sure the AI doesn’t have implicit biases?
On today's tech podcast, HiringSolved’s founder Shon Burton talks about inherent bias in artificial intelligence and how HiringSolved has worked to eliminate bias in their recruiting tool.
By Neil C. Hughes5
200200 ratings
Machines are biased. Why? Because humans are biased and humans teach machines. With artificial intelligence being integrated into HR departments in an effort to take the bias out of hiring, we need to take a step back and ensure we’re taking the bias out of AI.
HiringSolved, a startup that created the first “Siri-like” AI-powered assistant to help recruiters identify talent and build a diverse workforce, is working on just that with an update to their tool, RAI (Recruiting Artificial Intelligence, pronounced “Ray”). Used by companies such as Staples and Luxottica, RAI has now integrated voice recognition features to make it easier for recruiters to verbally set parameters to identify candidates, whether it’s by gender, skill, job experience or even veteran status. But how can we be sure the AI doesn’t have implicit biases?
On today's tech podcast, HiringSolved’s founder Shon Burton talks about inherent bias in artificial intelligence and how HiringSolved has worked to eliminate bias in their recruiting tool.

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