Many companies say they want to diversify their workforce. Far fewer have actually succeeded in doing so, even if they're earnestly trying. And one of the first hurdles can come before any candidates have even been interviewed: The language used in recruiting emails or job postings is often full of unconscious biases—phrases like "gentlemen's agreement" or even "ninja" can deter women or people of color from even applying in the first place.
But how do we check our unconscious biases when, by definition, we don't know what they are? A Seattle startup called Textio says it’s using machine learning to help eliminate those biases in real time, by literally changing the writing of hiring managers who are composing the job postings.
This week on Gadget Lab, WIRED senior writer Lauren Goode talks with Textio CEO Kieran Snyder about the way the software works, how tracking language patterns over time can reveal deep insights about how we see the world, and how this kind of “augmented writing” software could eventually be used in applications beyond job postings.
Show Notes:
Read more about Textio here. Check out other conversations from WIRED25 here.
Lauren Goode can be found on Twitter @LaurenGoode. Michael Calore is @snackfight. Bling the main hotline at @GadgetLab. The show is produced by Boone Ashworth (@booneashworth). Our consulting executive producer is Alex Kapelman (@alexkapelman). Our theme music is by Solar Keys.
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