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Can AI Reduce Workplace Bias?

It’s easy for organizations to hire the wrong people if they’re looking at the wrong criteria. New data-driven tools are helping companies find the right hires—where they least expect them.

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Once upon a time, Americans aspired to work for a single company all their lives. Turnover averaged less than 20 percent between 1955 and 1965. But between 2017 and 2021, it soared to nearly 50 percent. Many people, especially in Silicon Valley, argue that this is a positive development: Job mobility transfers knowledge, they say. It drives innovation.

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But so much turnover has “huge human costs,” says Amir Goldberg, associate professor of organizational behavior at the Stanford Graduate School of Business. People may not invest themselves in jobs they regard as temporary.

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Companies expecting employees to move on may not fully invest in them, which makes finding the right hire as crucial as it is challenging. Turnover costs U.S. companies more than $1 trillion annually.

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What if companies have already hired the right person—but don’t yet realize it? New artificial-intelligence tools are helping us see that employees’ capabilities may extend far beyond what employers think they know about them.

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Hitch Works—a skills-intelligence firm recently acquired by ServiceNow—uses AI to discover untapped employee skills and aptitudes and match them with internal opportunities.

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“There is so much wasted talent inside today’s organizations. AI helps make talent supply chains more visible, mitigates bias, and unlocks organizational capacity.”

Kelley Steven-Waiss, Head of Workforce Innovation Products and Founder of Hitch Works, Inc.

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In 2020, Dolby Labs suddenly found itself with 14 open positions. Instead of searching far and wide for new hires, Dolby implemented Hitch’s AI technology. Within 24 hours, it had filled every job internally.

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When HERE Technologies, a location-data company based in Chicago, deployed Hitch’s tools, employee engagement jumped 9 percent. Full-time equivalent capacity increased by 1.6 percent—for a savings of $14 million.

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Amid widespread skepticism today about organizations’ commitment to diversity, equity, and inclusion (DEI), a data-centric approach can also contribute to making workplaces more equitable and merit-based. AI tools can help identify the best person for the job—whoever they may be and whatever their current role is.

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“AI-powered skills intelligence can help companies match employees to work based on their abilities and interests—rather than who they know.”

Heather Jerrehian, VP of product management at ServiceNow and former CEO of Hitch Works

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“AI can sort through large datasets and analyze equity by race, gender, geography, tenure, and other factors, then compare across departments. It gives leaders totally new levels of insight not previously available.”

Dave Wright, ServiceNow’s chief innovation officer

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Research shows that more diverse workforces perform better, hire superior talent, have more engaged employees, and retain workers longer. As a female-founded, -funded, and -led company, Hitch is a prime example of diversity leading to innovation.

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“I think companies have a strong incentive to use AI to de-bias their processes,”

Amir Goldberg, associate professor of organizational behavior at Stanford Graduate School of Business.

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“They may reap huge rewards. They will get these amazing players that nobody realizes are amazing players, in the same way that Billy Beane figured it out with the Oakland A’s.”

Amir Goldberg, associate professor of organizational behavior at Stanford Graduate School of Business.

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Much as Beane’s baseball scouts did, some companies have resisted. “There has been an element of fear—that statistical analysis will never be as good as ‘gut feel,’ that people cannot be rated based on numbers,” Wright says. “This may well be true, but augmenting your gut feel with actual data can only reinforce the potential to make the right decision.”

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Data analytics, used properly, will profoundly shape the future of the American workplace, Goldberg asserts. “Companies that learn how to use their data to improve their bottom line are just going to be winners,” he says. “It's as simple as that.”

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