Though the person sitting across the desk (or in a Zoom session) for your last interview may have been flesh and blood, there’s a chance that many of the decisions that led up to your getting the interview and, fingers crossed, the job were made by artificial intelligence. According to a Mercer survey of human resource leaders in the U.S., 55% of them use predictive algorithms in the hiring process.
As we’ve learned time and again, A.I. Is not the unbiased decider it should be. After all, robots learn from the data sets they’re fed, biases and all. And, at times, those biases can leave out entire groups of people, causing far greater harm than one prejudiced HR person could do on his or her own.
So, is there a fix? Can A.I. Play fair?
One thing that might help is “being much more focused not just on doing some superficial bias testing at the end, but a much more rigorous interrogation of the design of these tools at the beginning,” says Alexandra Reeve Givens, president and CEO of the Center for Democracy and Technology, which focuses on civil liberties in the digital age. Another tactic, she adds, is to give job candidates the chance to explain how a certain kind of test may discriminate against them, enabling them to opt for more traditional processes that would make it a “more personalized assessment.”
Givens joins Michal Lev-Ram and Brian O’Keefe, the hosts of Coins2Day Brainstorm, to talk about A.I. In hiring. Each week, the podcast explores how technology is changing our lives.
Also on the show, O’Keefe talks with Jacob Appel, chief strategist at O’Neil Risk Consulting & Algorithmic Auditing (ORCAA).
“We got a lot of calls because companies are scared,” Appel says. “In particular, they’re scared that an algorithm they are using might be doing something that’s either illegal or that might look bad if it came out in a New York Times headline or a Coins2Day headline. They don’t want to be caught unaware.”
The show caps off with an interview with Kieran Snyder, cofounder and CEO of Textio, an augmented writing platform that helps predict who will respond to a job ad or other piece of writing.
“Think of it like a word processor that is hyper tuned for hiring and candidate communication,” Snyder says.
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