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 …

Automation has profoundly transformed the operational landscape of companies across
various industries. As organizations strive to adapt to this rapidly evolving technology, it …

Most prior work on human-AI interaction is set in communities that indicate skepticism
towards AI, but we know less about contexts where AI is viewed as aspirational. We …

The issue of youth unemployment is a global concern, with active initiatives, policies, and
technologies in place to support employment seekers. Despite these efforts, youth …

The topic of algorithmic fairness is of increasing importance to the Human–Computer
Interaction research community following accumulating concerns regarding the use and …

Recent advances in Artificial Intelligence (AI) suggest that AI applications could transform
healthcare delivery in the Global South. However, as researchers and technology …

Data-driven approaches that form the foundation of advancements in machine learning (ML)
are powered in large part by human infrastructures that enable the collection of large …

Over the past few decades, a small but growing group of people have worked remotely from
their homes. With the arrival of the coronavirus pandemic, millions of people found …

Care workers are increasingly using digital technology in their daily lives, for monitoring,
financial compensation, training, coordination, and more. State and corporate actors have …

Artificial intelligence is becoming more widely available in all parts of the world. This has
created many previously unforeseen possibilities for addressing the challenges outlined in …