18 citations · 54 across the 31 of their papers we have counts for
7 papers · 1 filter
Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling
Clay H. Yoo, Ashiqur R. KhudaBukhsh
This paper makes two key contributions. First, it argues that highly specialized rare content classifiers trained on small data typically have limited exposure to the richness and…
Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit Large Language Models
Arka Dutta, Adel Khorramrouz, Sujan Dutta +1
This paper makes three contributions. First, it presents a generalizable, novel framework dubbed \textit{toxicity rabbit hole} that iteratively elicits toxic content from a wide su…
Disentangling Societal Inequality from Model Biases: Gender Inequality in Divorce Court Proceedings
Sujan Dutta, Parth Srivastava, Vaishnavi Solunke +2
Divorce is the legal dissolution of a marriage by a court. Since this is usually an unpleasant outcome of a marital union, each party may have reasons to call the decision to quit…
Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning
Tharindu Cyril Weerasooriya, Sarah Luger, Saloni Poddar +2
Human-annotated data plays a critical role in the fairness of AI systems, including those that deal with life-altering decisions or moderating human-created web/social media conten…
For Women, Life, Freedom: A Participatory AI-Based Social Web Analysis of a Watershed Moment in Iran's Gender Struggles
Adel Khorramrouz, Sujan Dutta, Ashiqur R. KhudaBukhsh
In this paper, we present a computational analysis of the Persian language Twitter discourse with the aim to estimate the shift in stance toward gender equality following the death…
Quantifying the Academic Quality of Children's Videos using Machine Comprehension
Sumeet Kumar, Mallikarjuna T., Ashiqur Khudabukhsh
YouTube Kids (YTK) is one of the most popular kids' applications used by millions of kids daily. However, various studies have highlighted concerns about the videos on the platform…
Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive
Tharindu Cyril Weerasooriya, Sujan Dutta, Tharindu Ranasinghe +3
Offensive speech detection is a key component of content moderation. However, what is offensive can be highly subjective. This paper investigates how machine and human moderators d…