4 papers
From Vulnerable Data Subjects to Vulnerabilizing Data Practices: Navigating the Protection Paradox in AI-Based Analyses of Platformized Lives
Delfina S. Martinez Pandiani, Ella Streefkerk, Laurens Naudts +1
This paper traces a conceptual shift from understanding vulnerability as a static, essentialized property of data subjects to examining how it is actively enacted through data prac…
QueerGen: How LLMs Reflect Societal Norms on Gender and Sexuality in Sentence Completion Tasks
Mae Sosto, Delfina Sol Martinez Pandiani, Laura Hollink
This paper examines how Large Language Models (LLMs) reproduce societal norms, particularly heterocisnormativity, and how these norms translate into measurable biases in their text…
Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicities
Delfina Sol Martinez Pandiani, Erik Tjong Kim Sang, Davide Ceolin
Internet memes, channels for humor, social commentary, and cultural expression, are increasingly used to spread toxic messages. Studies on the computational analyses of toxic memes…
Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotate
Delfina Sol Martinez Pandiani, Valentina Presutti
In the contemporary world of AI and data-driven applications, supervised machines often derive their understanding, which they mimic and reproduce, through annotations--typically c…