Collaborative Research: DASS: Designing accountable software systems for worker-centered algorithmic management

Software systems have become an integral part of public and private sector management, assisting and automating critical human decisions such as selecting people and allocating resources. Emerging evidence suggests that software systems for algorithmic management can significantly undermine workforce well-being and may be poorly suited to fostering accountability to existing labor law. For example, warehouse workers are under serious physical and psychological stress due to task assignment and tracking without appropriate break times. On-demand ride drivers feel that automated evaluation is unfair and distrust the system's opaque payment calculations which has led to worker lawsuits for wage underpayment. Shift workers suffer from unpredictable schedules that destabilize work-life balance and disrupt their ability to plan ahead. Meanwhile, there is not yet an established mechanism to regulate such software systems. For example, there is no expert consensus on how to apply concepts of fairness in software systems. Existing work laws have not kept pace with emerging forms of work, such as algorithmic management and digital labor platforms that introduce new risk to workers, including work-schedule volatility and employer surveillance of workers both on and off the job. 

To tackle these challenges, we aim to develop technical approaches that can (1) make software accountable to existing law, and (2) address the gaps in existing law by measuring the negative impacts of certain software use and behavior, so as to help stakeholders better mitigate those effects. In other words, we aim to make software accountable to law and policy, and leverage it to make software users (individuals and firms) accountable to the affected population and the public. This project is developing novel methods to enable standards and disclosure-based regulation in and through software systems drawing from formal methods, human-computer interaction, sociology, public policy, and law throughout the software development cycle. The work will focus on algorithmic work scheduling, which impacts shift workers who make up 25% of workers in the United States. It will take a participatory approach involving stakeholders, public policy and legal experts, governments, commercial software companies, as well as software users in firms and those affected by the software's use, in the software design and evaluation. 

The research will take place in three thrusts in the context of algorithmic scheduling: (1) participatory formalization of regulatory software requirements, (2) scalable and interactive formal methods and automated reasoning for software guarantees and decision support, and (3) regulatory outcome evaluation and monitoring. By developing accountable scheduling software, the project has the potential for significant broader impacts by giving businesses the tools they need for compliance with and accountability to existing work scheduling regulations, as well as the capacity to provide more schedule stability and predictability in their business operations.

Min Kyung Lee
Agency
National Science Foundation (NSF)
Grant Dates
-
Funding

The award is $249,999 over the project period.

Award Number

NSF Award # 2217721