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 …

While algorithm audits are growing rapidly in commonality and public importance, relatively
little scholarly work has gone toward synthesizing prior work and strategizing future research …

Many recent technological advances (eg ChatGPT and search engines) are possible only
because of massive amounts of user-generated data produced through user interactions …

We initiate a principled study of algorithmic collective action on digital platforms that deploy
machine learning algorithms. We propose a simple theoretical model of a collective …

Many powerful computing technologies rely on implicit and explicit data contributions from
the public. This dependency suggests a potential source of leverage for the public in its …

The increasing prevalence of large-scale labor aggregation platforms, worker analytics, and
algorithmic decision-making by management raises the question of whether workers can …

Increasing demands for fact-checking have led to a growing interest in developing systems
and tools to automate the fact-checking process. However, such systems are limited in …

Article 5 (1)(c) of the European Union's General Data Protection Regulation (GDPR)
requires that" personal data shall be [...] adequate, relevant, and limited to what is necessary …

A growing body of work has highlighted the important role that Wikipedia's volunteer-created
content plays in helping search engines achieve their core goal of addressing the …

A large body of research has attempted to ensure that algorithmic systems adhere to notions
of fairness and transparency. Increasingly, researchers have highlighted that mitigating …