The Role of AI in the Workplace: Should managers rely on hiring algorithms?

Newswise — Managers often use AI systems to aid in the hiring, and sometimes firing, of employees. These AI tools are used to screen resumes, evaluate and make predictions based on candidate video responses to AI, among other talent recruitment efforts. Sometimes these AI tools are better at predicting an employee’s potential than even managers who’ve had the chance to interview the candidate. 

However, relying on hiring algorithms alone to make these decisions is not the answer. One expert at the George Washington University examined the issue and concluded that humans still must play a key role in the hiring process.

Vikram R. Bhargava is an assistant professor of strategic management and public policy at the George Washington University School of Business. His research centers around topics including artificial intelligence, the future of work, technology addiction, mass social media outrage, autonomous vehicles, and other topics related to digital technology policy.

Bhargava and his co-author published, “Hiring, Algorithms, and Choice: Why Interviews Still Matter,” in the journal Business Ethics Quarterly. The paper underscores the value of maintaining human choice in hiring processes rather than relying on AI alone.

“Much of the discomfort of HR managers deferring to algorithms are due to worries about bad outcomes: Did the algorithm make the right call? Was there bad data? Were there any untoward racial or gender biases reflected in the data?” Bhargava says. “But even if these outcomes are ultimately improved through an engineering solution, it still doesn’t settle the question of whether HR managers should defer to algorithms. This is not because our gut instincts are far superior—often they’re not.”

“Rather, this is because there are important (and overlooked) ethical values created through us making choices—including choices about whom to work with or not work with—that would be jeopardized, were HR managers to abdicate that choice to an algorithm. This is so, no matter how sophisticated algorithms ultimately become at predicting the fit and performance of an employee.”

If you would like to speak with Prof. Bhargava, please contact GW Media Relations Specialist Cate Douglass at [email protected].

-GW-