22 citations · 38 across the 4 of their papers we have counts for
4 papers
Bridging Research and Practice Through Conversation: Reflecting on Our Experience
Mayra Russo, Mackenzie Jorgensen, Kristen M. Scott +4
While some research fields have a long history of collaborating with domain experts outside academia, many quantitative researchers do not have natural avenues to meet experts in a…
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…
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness
Jose M. Alvarez, Kristen M. Scott, Salvatore Ruggieri +1
In uses of pre-trained machine learning models, it is a known issue that the target population in which the model is being deployed may not have been reflected in the source popula…
Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation
Alejandra Bringas Colmenarejo, Luca Nannini, Alisa Rieger +5
With increasing digitalization, Artificial Intelligence (AI) is becoming ubiquitous. AI-based systems to identify, optimize, automate, and scale solutions to complex economic and s…