The field of mobile and wearable computing is undergoing a revolutionary integration of
machine learning. Devices can now diagnose diseases, predict heart irregularities, and …

Studies conducted on Western, Educated, Industrialized, Rich, and Democratic (WEIRD)
samples are considered atypical of the world's population and may not accurately represent …

Fields such as medicine and public health attest to deep conflict of interest concerns present
when private companies fund evaluation of their own products and services. We draw on …

Recent advances in artificial intelligence (AI), especially in generative language modelling,
hold the promise of transforming government. Given the advanced capabilities of new AI …

The AI Ethics community faces an imperative to empower stakeholders and impacted
community members so that they can scrutinize and influence the design, development, and …

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 diffusion models and large language models have underpinned a new
generation of powerful and accessible tools, and some of the most publicly visible …

Fairness, accountability, and transparency are the three conceptual foundations of the
FAccT conference. Transparency, however, has yet to be scrutinized to the same degree as …

Recent work in algorithmic fairness has highlighted the challenge of defining racial
categories for the purposes of anti-discrimination. These challenges are not new but have …

Machine learning (ML) algorithms are still a novel research object in the field of media
studies. While existing research focuses on concrete software on the one hand and the …