The A.I. in your workplace

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In her first feature for Fortune, my colleague Maria Aspan tackles the strange new world of A.I. in hiring and human resources, by far one of the hottest new ideas to hit talent management in ages. It seems like a perfect fit, at first: The tech aims to do everything from helping hiring managers pluck the ideal candidate from a digital stack of 20,000 resumes to identifying valuable employees before they jump ship, to finding the next big corporate star.

And it’s everywhere. From her story:

In a 2018 Deloitte survey, 32% of business and technology executives said they were deploying A.I. for “workforce management.” That share is almost certainly higher today—and it’s spreading to encompass some of the world’s largest companies.

As a job seeker, you might have your application vetted by a Mya Systems chatbot at L’Oréal or PepsiCo. You could respond to an A.I.-crafted job posting vetted by Textio, perhaps at ExpediaGroup or ViacomCBS. You could be asked to play Pymetrics games not only at Kraft Heinz but also at Unilever or JPMorgan Chase. You could record one of the automated HireVue video interviews used by Hilton and Delta Air Lines.

Your relationship with A.I. may extend past the job offer too. Once hired, you might find yourself filling out employee-engagement surveys designed by Microsoft’s LinkedIn, where your answers could help set your manager’s performance targets. Your employer could tap you for promotion opportunities identified by Workday’s A.I. If you work at an Amazon warehouse and miss your productivity goals, in-house systems could recommend that you be fired. On the other hand, if you work at IBM and plan to quit, in-house systems might guess your plans and warn your managers that they should try to make you happy.

So, what could go wrong?

“This was the central question I asked everyone for the piece,” Aspan tells raceAhead. “Not just how do you think about unconscious bias in A.I., but how do you make sure your technology is eliminating it?”

And therein lies the rub. “Everyone, of course, said they were thinking about it, and most say they’re checking for discriminatory results or disparate impact through internal or external audits of their A.I. systems,” she says. But as her story points out, these self-audits have no external teeth, the technology is unregulated, and it’s functionally too late—A.I. in HR is out there, at scale.

From a mitigation perspective, system makers can make certain accommodations.

Pymetrics, a startup that offers cognitive and behavioral tests, has modified versions of its games for job candidates with color blindness, ADHD, and dyslexia. But A.I. systems can’t mitigate what it doesn’t know to look for.

Quoted in the piece is Ifeoma Ajunwa, an assistant professor at Cornell who studies automation in hiring. She offers as an example a hiring algorithm designed to scan resumes and reject any with unexplained gaps in employment. “That seems like a pretty straightforward way to make sure you’re getting a committed workforce,” she told Aspan, but “you’re going to exclude formerly incarcerated people, possibly veterans, and women who had to take a break for childcare or eldercare.”

Please read and share with your executive team—think of it as a creative way to earn a coffee meeting with your Chief Talent Officer! And if you’d like to hear Aspan’s formidable voice on the subject, check out her recent interview on raceAhead’s favorite radio show, Career Mix with Torin Ellis on Sirius XM Urban View, Channel 126.

Ellen McGirt
@ellmcgirt
Ellen.McGirt@fortune.com

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