UNIVERSITY PARK, Pa. — Benjamin Hanrahan, assistant professor of information sciences and technology and Penn State Institute for Computational and Data Sciences affiliate, will explore how digital tools to automate and remotely manage workers may negatively impact those workers and their rights.
The new research project is funded by a five-year, $485,000 National Science Foundation (NSF) Faculty Early Career Development (CAREER) award, which supports faculty members as they establish their careers as outstanding researchers and leaders in knowledge sharing. It is one of the most prestigious recognitions awarded by the NSF.
The project will focus on ride-sharing platforms, which use algorithmic management to automatically assign and evaluate work. According to Hanrahan, the proprietary nature of these platforms has limited researchers from studying and making suggestions to improve the algorithms and platforms, exposing both drivers and customers to unfair outcomes. For example, biases may lead passengers to poorly rate minority drivers, or for drivers to decline rides to certain categories of customers.
“Algorithmic management is likely going to cover more jobs in the future, and we don’t understand a lot about it,” said Hanrahan. “This project is going to reimagine algorithmic managers as a more empowering force than they currently are.”
He added, “The isolated cases that we have been able to study, point to a larger and urgent need to reimagine these platforms as equitable workplaces, where we hold our algorithmic managers, and the people that develop them, to the same standard that we hold human managers.”
Hanrahan aims to develop an experimental ride-hailing platform that gives drivers and customers control over parameters that impact algorithmic outcomes. Then, he will evaluate the platform to understand how both individuals and groups interact with algorithmic managers, as well as analyze self-governance of organizations that utilize algorithmic management.
One part of the study will imagine the platform being owned by the drivers themselves.
“What would that look like?” said Hanrahan. “There would still probably be a fee for customers to use it, but what could drivers do with that fee? Maybe they could pay for sick days or insurance.”
Hanrahan hopes that the project’s outcomes could widely impact how work is managed by algorithms and the creation of human-centered algorithms and platforms for the gig economy.
“Ride sharing is somewhat unique because it’s geographically bound, but there are other gig platforms that use algorithmic management, like freelance writing, photography and writing code,” said Hanrahan. “We need to walk into this thing with our eyes wide open.”