Mitigating bias in algorithmic systems is a critical issue drawing attention across
communities within the information and computer sciences. Given the complexity of the …

Pretrained neural language models (LMs) are prone to generating racist, sexist, or otherwise
toxic language which hinders their safe deployment. We investigate the extent to which …

Hundreds of millions of people now interact with language models, with uses ranging from
help with writing, to informing hiring decisions. However, these language models are known …

Operating at a large scale and impacting large groups of people, automated systems can
make consequential and sometimes contestable decisions. Automated decisions can impact …

Abstract The study of Online Social Networks offers growing opportunities to examine a
number of aspects of the real world and to better understand how human society works at …

To investigate opinions and attitudes of medical professionals towards adopting AI-enabled
healthcare technologies in their daily business, we used a mixed-methods approach. Study …

The way we talk carries information about who we are. Demographics, personality, clinical
conditions, political preferences influence what we speak about and how, suggesting that …

Implicit biases and stereotypes are often pervasive in different forms of creative writing such
as novels, screenplays, and children's books. To understand the kind of biases writers are …

The irreplaceable key to the triumph of Question & Answer (Q & A) platforms is their users
providing high-quality answers to the challenging questions posted across various topics of …

Psychological studies on morality have proposed underlying linguistic and semantic factors.
However, current empirical studies often lack the nuances and complexity of real life. This …