For example, if a company's goal is to not push away qualified female candidates, it's useful to learn from Textio that phrases like "under pressure" (as in, "we're looking for a candidate that works well under pressure") tend to drive women job hunters away, while phrases like "passion for learning" tend to attract women to jobs.
Some of the "gender biases" that Textio ferrets out with its big-data crunching are puzzling, but they can be verified statistically. For example, more women are more likely to apply for a job if the word extraordinary is used in the listing instead of the word exceptional.
Gender bias in job postings is one problem Textio claims to help with. The other is the need to simply hire better candidates, regardless of gender.
Textio costs $59 per user per month. After you sign up, you can just copy and paste a job posting into the Textio Web form, and the system will spit out its analysis.
Textio will highlight words and phrases known to turn away candidates, either because they're too jargony or too cliché, or because they contain keywords that Textio's analysis has determined will result in inferior candidates or unsuccessful hires.
Before Textio got into the business of detecting gender bias, the company used its analytical kung fu to try to predict which Kickstarter projects would be funded. And in the process, it discovered that the way a Kickstarter page was built and worded had a bigger influence on funding than what the product was.
Even now, according to Textio CEO and co-founder Kieran Snyder, who has a Ph.D. in linguistics and worked at both Microsoft and Amazon, people use Textio's service to evaluate all kinds of communications, even though the system is optimized on a huge set of job listings.
Unlike Watson Tone Analyzer, Textio could be significantly useful even to the most skilled writers, such as professional novelists or, say, tech journalists.
Even great writers can (and often do) write in a way that's unappealing to one gender or another, or in a way that will unintentionally push away prospective employees or crowd-funding investors.
The reason Textio works is that it doesn't try to understand human language -- something far beyond even the most advanced A.I. Instead, it does what computers are good at -- it finds correlations in data sets. It knows that the word exceptional in a job listing will attract fewer women candidates than the word extraordinary, even though it has no idea what exceptional means or why the correlation exists.
Some people may be tempted to fear that software, supercomputers and algorithms are going to replace us all -- including those of us who write for a living or for whom writing is a major part of how we make our living. Some may be tempted to dismiss these fears and say that software can never replace people in these discipline. Either way, this technology is astounding.
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