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 …

Stereotypes, bias, and discrimination have been extensively documented in Machine
Learning (ML) methods such as Computer Vision (CV)[18, 80], Natural Language …

Data-driven algorithms are studied and deployed in diverse domains to support critical
decisions, directly impacting people's well-being. As a result, a growing community of …

Evaluating new techniques on realistic datasets plays a crucial role in the development of
ML research and its broader adoption by practitioners. In recent years, there has been a …

Despite years of heavy criticism, privacy self-management (ie, the principle that people
individually manage their privacy via notice and choice) remains the standard of privacy …

Critical refusal is an active process; an informed practice of investigating power differences
in order to generate more just and equitable alternatives to the status quo. In this paper, we …

With many million users across all age groups and income levels, video games have
become the world's leading entertainment industry. Behind the fun experience they provide …

As time goes by, information and communication technology continue to advance. Since the
pandemic, the need for information and communication technology has risen to aid us in …

Digital technologies are reshaping the global economy and complicating cooperation over
its governance. Innovations in technology and business propel a new, digitally-driven phase …

To ensure that AI-infused systems work for disabled people, we need to bring accessibility
datasets sourced from this community in the development lifecycle. However, there are …