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D3CODE: Disentangling Disagreements in Data across Cultures on Offensiveness Detection and Evaluation
While human annotations play a crucial role in language technologies, annotator subjectivity has long been overlooked in data collection.
Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates
More importantly, we find that individual moral values play a crucial role in shaping these variations: moral concerns about Care and Purity are significant mediating factors driving cross-cultural differences.
Evaluating the Social Impact of Generative AI Systems in Systems and Society
We move toward a standard approach in evaluating a generative AI system for any modality, in two overarching categories: what is able to be evaluated in a base system that has no predetermined application and what is able to be evaluated in society.
Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media
Online social media platforms increasingly rely on Natural Language Processing (NLP) techniques to detect abusive content at scale in order to mitigate the harms it causes to their users.
Diversity and Inclusion Metrics in Subset Selection
The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives.
