In this paper, we review algorithmic bias in education, discussing the causes of that bias and
reviewing the empirical literature on the specific ways that algorithmic bias is known to have …

High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …

There has been rapidly growing interest in the use of algorithms in hiring, especially as a
means to address or mitigate bias. Yet, to date, little is known about how these methods are …

While rapid advances in artificial intelligence (AI) hiring tools promise to transform the
workplace, these algorithms risk exacerbating existing biases against marginalized groups …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Content creators are instructed to write textual descriptions of visual content to make it
accessible; yet existing guidelines lack specifics on how to write about people's appearance …

Large language models produce human-like text that drive a growing number of
applications. However, recent literature and, increasingly, real world observations, have …

Access to digital images is important to people who are blind or have low vision (BLV). Many
contemporary image description efforts do not take into account this population's nuanced …

Speech datasets are crucial for training Speech Language Technologies (SLT); however,
the lack of diversity of the underlying training data can lead to serious limitations in building …

In society today, people experiencing disability can face discrimination. As artificial
intelligence solutions take on increasingly important roles in decision-making and …