Value kaleidoscope: Engaging ai with pluralistic human values, rights, and duties
Human values are crucial to human decision-making.\textit {Value pluralism} is the view that
multiple correct values may be held in tension with one another (eg, when considering\textit …
multiple correct values may be held in tension with one another (eg, when considering\textit …
Harmful speech detection by language models exhibits gender-queer dialect bias
Trigger Warning: Profane Language, Slurs Content moderation on social media platforms
shapes the dynamics of online discourse, influencing whose voices are amplified and …
shapes the dynamics of online discourse, influencing whose voices are amplified and …
From dogwhistles to bullhorns: Unveiling coded rhetoric with language models
Dogwhistles are coded expressions that simultaneously convey one meaning to a broad
audience and a second one, often hateful or provocative, to a narrow in-group; they are …
audience and a second one, often hateful or provocative, to a narrow in-group; they are …
''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text
Language serves as a powerful tool for the manifestation of societal belief systems. In doing
so, it also perpetuates the prevalent biases in our society. Gender bias is one of the most …
so, it also perpetuates the prevalent biases in our society. Gender bias is one of the most …
Cobias: Contextual reliability in bias assessment
Large Language Models (LLMs) often inherit biases from the web data they are trained on,
which contains stereotypes and prejudices. Current methods for evaluating and mitigating …
which contains stereotypes and prejudices. Current methods for evaluating and mitigating …
Leveraging machine-generated rationales to facilitate social meaning detection in conversations
We present a generalizable classification approach that leverages Large Language Models
(LLMs) to facilitate the detection of implicitly encoded social meaning in conversations. We …
(LLMs) to facilitate the detection of implicitly encoded social meaning in conversations. We …
Social intelligence data infrastructure: Structuring the present and navigating the future
As Natural Language Processing (NLP) systems become increasingly integrated into human
social life, these technologies will need to increasingly rely on social intelligence. Although …
social life, these technologies will need to increasingly rely on social intelligence. Although …
Don't Take This Out of Context! On the Need for Contextual Models and Evaluations for Stylistic Rewriting
Most existing stylistic text rewriting methods and evaluation metrics operate on a sentence
level, but ignoring the broader context of the text can lead to preferring generic, ambiguous …
level, but ignoring the broader context of the text can lead to preferring generic, ambiguous …
Biasx:" thinking slow" in toxic content moderation with explanations of implied social biases
Toxicity annotators and content moderators often default to mental shortcuts when making
decisions. This can lead to subtle toxicity being missed, and seemingly toxic but harmless …
decisions. This can lead to subtle toxicity being missed, and seemingly toxic but harmless …
Polarized Opinion Detection Improves the Detection of Toxic Language
Distance from unimodality (DFU) has been found to correlate well with human judgment for
the assessment of polarized opinions. However, its un-normalized nature makes it less …
the assessment of polarized opinions. However, its un-normalized nature makes it less …