Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

In this work, we survey a breadth of literature that has revealed the limitations of
predominant practices for dataset collection and use in the field of machine learning. We …

As AI-powered systems increasingly mediate consequential decision-making, their
explainability is critical for end-users to take informed and accountable actions. Explanations …

In On the Inconvenience of Other People Lauren Berlant continues to explore our affective
engagement with the world. Berlant focuses on the encounter with and the desire for the …

In response to growing concerns of bias, discrimination, and unfairness perpetuated by
algorithmic systems, the datasets used to train and evaluate machine learning models have …

In the spirit ofNickel and Dimed, a necessary and revelatory expose of the invisible human
workforce that powers the web--and that foreshadows the true future of work. Hidden …

Research in machine learning (ML) has argued that models trained on incomplete or biased
datasets can lead to discriminatory outputs. In this commentary, we propose moving the …

A growing number of people are working as part of on-line crowd work. Crowd work is often
thought to be low wage work. However, we know little about the wage distribution in practice …

Angèle Christin, Metrics at Work. Journalism and the Contested Meaning of Algorithms (Princeton
University Press, 2020) Navigation – Plan du site Sociologie AccueilVie de la revueComptes …

Technology companies continue to invest in efforts to incorporate responsibility in their
Artificial Intelligence (AI) advancements, while efforts to audit and regulate AI systems …