ethics

Countering Hateful and Offensive Speech Online - Open Challenges

In today’s digital age, hate speech and offensive speech online pose a significant challenge to maintaining respectful and inclusive online environments. This tutorial aims to provide attendees with a comprehensive understanding of the field by …

Metrics for What, Metrics for Whom: Assessing Actionability of Bias Evaluation Metrics in NLP

This paper introduces the concept of actionability in the context of bias measures in natural language processing (NLP). We define actionability as the degree to which a measure’s results enable informed action and propose a set of desiderata for …

A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation

Recent instruction fine-tuned models can solve multiple NLP tasks when prompted to do so, with machine translation (MT) being a prominent use case. However, current research often focuses on standard performance benchmarks, leaving compelling …

What about ''em''? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns

As 3rd-person pronoun usage shifts to include novel forms, e.g., neopronouns, we need more research on identity-inclusive NLP. Exclusion is particularly harmful in one of the most popular NLP applications, machine translation (MT). Wrong pronoun …