Should We Treat Data as Labor? Moving beyond "Free"

By Imanol Arrieta-Ibarra, L. Goff, Diego Jiménez-Hernández, J. Lanier, E. Weyl. 2018

189 citations recorded by the source corpus.

Subfields: Marketing, Sociology and Political Science, Strategy and Management, AI Ethics, Fairness & Society, Economics & Operations Research

Citations in the corpus

• On the Accuracy of Influence Functions for Measuring Group Effects (2019, unknown): “, 2018); apportion credit between crowdworkers, each of whom generated part of the data (Arrieta-Ibarra et al., 2018); or, in a multi-party learning setting, ensure that no individual user has too much influence on the joint model (Hayes and Ohrimenko, 2018).”
• Behavioral Use Licensing for Responsible AI (2020, unknown): “This approach would be highly in line with calls to empower people who do “data labor” to generate valuable data [12, 66, 67].”
• Data Epistemologies, The Coloniality of Power, and Resistance (2019, unknown): “One proposal to bring balance to the data extractivism model suggests compensating individuals for their contribution to the digital economy and supporting competitive markets (Arrieta et al. 2017; Posner and Weyl 2018).”