14 citations · 19 across the 3 of their papers we have counts for
3 papers
Articulation Work and Tinkering for Fairness in Machine Learning
Miriam Fahimi, Mayra Russo, Kristen M. Scott +3
The field of fair AI aims to counter biased algorithms through computational modelling. However, it faces increasing criticism for perpetuating the use of overly technical and redu…
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo +3
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief te…
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms
Organizers of QueerInAI, Nathan Dennler, Anaelia Ovalle +11
Bias evaluation benchmarks and dataset and model documentation have emerged as central processes for assessing the biases and harms of artificial intelligence (AI) systems. However…