Guidelines for Ethical Data Work in Research
07/09/2025How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research.
The growing integration of machine learning (ML) into academic research is driving an increasing demand for large, labeled datasets. More and more, this work is being carried out by platform workers who often face precarious working conditions. In a new Discussion Paper Tianling Yang, Christian Strippel, Alexandra Keiner, Dylan Baker, Alexis Chávez, Krystal Kauffman, Marc Pohl, Caroline Sinders, and Milagros Miceli explore the ethical challenges of data work and propose standards for fair and responsible collaboration with data workers in academia.
The publication is the result of two workshops held in 2024, where an interdisciplinary team of scholars, practitioners, and data workers came together to discuss key issues related to the commissioning and execution of data work. The focus was not only on ethical implications, but also on practical ways to build equitable and sustainable systems for both data workers and requesters.