Per il ciclo di incontri “i Mercoledì di Nexa” (ogni 2° mercoledì del mese)

163° Mercoledì di Nexa – We need to talk about data work for machine learning

Milagros Miceli

Weizenbaum Institute for the Networked Society, The DAIR Institute

Centro Nexa su Internet & Società
Politecnico di Torino, via Boggio 65/a, Torino (1° piano)

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Data quality plays a pivotal role in the performance of machine learning (ML) models. Over the past decade, considerable research and industry efforts have focused on addressing biases and minimizing personal subjectivities in data collection, curation, classification, and labeling by data workers. In this talk, I propose a shift of perspective to emphasize the importance of labor in data production and explore power imbalances inherent in data work that significantly shape datasets and systems. I argue that enhancing labor conditions in data work and leveraging data workers’ expertise can improve data quality and help develop ML systems that are more inclusive and just. Starting from the assumption that power imbalances are the problem, not just bias, leads to fundamentally different research questions and methods of inquiry. In this sense, I highlight the need for interdisciplinary dialogue and cooperation in the study of data quality and data work.


Milagros MICELI is a sociologist and computer scientist. Her research is centered on exploring the production of ground-truth data for machine learning, with a specific focus on labor conditions and power dynamics involved in data generation and labeling. Dr. Miceli is interested in analyzing the underlying questions of meaning-making, knowledge production, and symbolic power embedded within machine learning data. Dr. Miceli’s work sheds light on the ethical and social implications of AI development, especially data work. Her research has significant implications for the responsible design and deployment of machine learning technologies. Dr. Miceli leads the research group “Data, Algorithmic Systems, and Ethics“ at the Weizenbaum Institute. She is also a research fellow at the DAIR Institute, where she is actively investigating ways to engage communities of data workers in AI research.

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Video dell’incontro