A.I. for Hire: 4 Ways Algorithms Can Boost Diversity in Hiring

A.I. for Hire: 4 Ways Algorithms Can Boost Diversity in Hiring

Artificial intelligence can be a “black box”—mysterious and more than a little intimidating. Meanwhile, new permutations of the tech are sprouting up like mushrooms, especially for recruiting and hiring. Yet as employers have increasingly tried to make their workforces more diverse and inclusive, the A.I. industry itself has taken some flak for being almost exclusively white and male. For instance, a recent study by New York University researchers points out that at tech giants like Facebook and Google, such tiny percentages of employees are female or nonwhite that the whole business is suffering a “diversity crisis.”

The irony there is that A.I., used correctly, has “a shot at being better at decision-making than we humans are, particularly in hiring,” says Aleksandra Mojsilovic. A research fellow in A.I. at IBM, Mojsilovic holds 16 patents in machine learning, and helped develop algorithms that can check other algorithms for unintended bias. An essential part of using A.I. to encourage diversity, she notes, is making sure the teams that build what goes into the black box are themselves a diverse group, with a variety of backgrounds and points of view.

“Any A.I. tool can only be as good—and as impartial—as the data we put in,” Mojsilovic says. “It’s not about replacing human intelligence, but rather about complementing it.”

A.I. has helped companies find and attract new hires of all sexes, ages, and ethnicities. Here are four main ways it’s helped them to do that:

A.I. knows how to speak to your best candidates

The words in job postings matter, not least because they often unwittingly discourage some potential hires from applying. “We as humans take our best guess at what will resonate with job seekers, but we’re often wrong,” notes Kieran Snyder, cofounder and CEO of the A.I. firm Textio.

Using a dataset of about 500 million actual job ads, and A.I. that analyzes the real-life responses they got, Textio advises companies on which words to use—and avoid. At client eBay, for instance, the phrase “prior experience” drew a 50% increase in male applicants. “But the phrase ‘demonstrated ability’—even though it means essentially the same thing—attracted 40% more women,” Snyder says.

Language that is neutral across sexes, races, and ethnicities “changes rapidly. There is no ‘use-these-10-words’ list,” she adds. “But the right word at the right moment does attract the most diverse possible group of applicants.”

A.I. widens the pool of eligible workers

A.I. also has the power to cast a wider net across unmanageable geographies. Take, for example, campus recruiting. Employers can send only so many humans to a limited number of campuses—but what if the perfect hire skipped the job fair, or goes to a different school entirely?

“A student at an obscure college where you’d never send a recruiter could be every bit as good as, or better than, graduates of the ‘right’ schools,” observes Loren Larsen, chief technology officer at A.I. firm HireVue, which lists IntelOracle, Dow Jones, Dunkin’ Brands, and many others among its clients.

 

To find out more go to: http://fortune.com/2019/06/01/ai-artificial-intelligence-diversity-hiring/