The pairing of massive data sets with processes—or algorithms—written in computer code to
sort through, organize, extract, or mine them has made inroads in almost every major social …

Current advances in research, development and application of artificial intelligence (AI)
systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of …

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 …

This article introduces the tenets of a theory of datafication of and in the Souths. It calls for a
de-Westernization of critical data studies, in view of promoting a reparation to the cognitive …

This article traces the emergence of a 'decolonial turn'in critical technology and data studies
that analyzes the transformation of society through data extraction for profit. First, we offer a …

Machine learning (ML) depends on data to train and verify models. Very often, organizations
outsource processes related to data work (ie, generating and annotating data and …

Purpose This study aims to conduct a systematic literature review and bibliometric analysis
on the topic of digital labour. The study also identifies the future research directions for the …

Artificial intelligence advancements have reignited job displacement debates that focus on
how the use of artificial intelligence affects labour, without considering how the production of …

This chapter focuses on the role of digital intermediaries in shaping technology, Society, and
economy under what Casilli and Posada call “the paradigm of the platform.” They trace the …

API-based research is an approach to computational social sciences and digital sociology
based on the extraction of records from the datasets made available by online platforms …