Employers are adopting algorithmic hiring technology throughout the recruitment pipeline.
Algorithmic fairness is especially applicable in this domain due to its high stakes and …

Research into explainable artificial intelligence (XAI) methods has exploded over the past
five years. It is essential to synthesize and categorize this research and, for this purpose …

Artificial Intelligence (AI) based technologies are increasingly being integrated into public
sector programs to help with decision-support and effective distribution of constrained …

AI-driven tools are increasingly deployed to support low-skilled community health workers
(CHWs) in hard-to-reach communities in the Global South. This paper examines how CHWs …

This study examined the perspectives of Ghanaian higher education students on the use of
ChatGPT. The Students' ChatGPT Experiences Scale (SCES) was developed and validated …

This paper explores the lived experience of using ChatGPT in HCI research through a month-
long trioethnography. Our approach combines the expertise of three HCI researchers with …

Explainable AI (xAI) methods are important for establishing trust in using black-box models.
However, recent criticism has mounted against current xAI methods that they disagree, are …

Data practices shape research and practice on fairness in machine learning (fair ML).
Critical data studies offer important reflections and critiques for the responsible …

Explainable AI (XAI) is often promoted with the idea of helping users understand how
machine learning models function and produce predictions. Still, most of these benefits are …

With its potential to contribute to the ethical governance of AI, eXplainable AI (XAI) research
frequently asserts its relevance to ethical considerations. Yet, the substantiation of these …