New research from Maryland Smith’s Margrét Bjarnadóttir that asks how organizations can leverage AI to build a more equitable workforce has been named the Best White Paper in the 2021 Wharton Analytics Conference.
In the research, Bjarnadóttir and her co-authors examine the roots of those AI biases in human resources applications and offer solutions to the challenges they present – solutions that could unlock the potential of analytics tools in the human resources space. The authors, Bjarnadóttir, David Anderson, a Smith PhD now at Villanova University, and David Ross, of the University of Florida, recommend creating a bias dashboard that parses a model’s performance for different groups, and they offer checklists for assessing your work – one for internal analytical projects, and another for adopting a vendor’s tool.
“We wanted to look at the question of: How can we do better? How can we build toward these more equitable workplaces?” says Bjarnadóttir, associate professor of management sciences and statistics at the University of Maryland’s Robert H. Smith School of Business.
There is a great deal at stake, she explains, with algorithms increasingly making decisions about who gets hired and who gets promoted, they have “life-changing impacts on employees.”
Early attempts to incorporate AI into the human resources process haven’t been met with resounding success. Among the most well-known fails: In 2018, Amazon.com was forced to abandon an AI recruiting tool it built, when it was discovered to be discriminating against female job applicants.
Biases in AI often stem from an organization’s HR history. In Amazon’s AI case, the analytics tool was found to be rejecting resumes from applicants for technical job roles because of phrases like “women’s chess team.” With the technical jobs long dominated by men, the model had taught itself that factors correlated with maleness were indicators of potential success.
For more on the research, read: Can AI Help Create More Equitable Workplaces?