1 code implementation • 6 Jul 2023 • Avijit Ghosh, Pablo Kvitca, Christo Wilson
Our study provides insights into the practical implications of using fair classification algorithms in scenarios where protected attributes are noisy or partially available.
no code implementations • 5 May 2022 • Avijit Ghosh, Matthew Jagielski, Christo Wilson
In this work we explore the intersection fairness and robustness in the context of ranking: when a ranking model has been calibrated to achieve some definition of fairness, is it possible for an external adversary to make the ranking model behave unfairly without having access to the model or training data?
1 code implementation • 22 Apr 2022 • Annie Y. Chen, Brendan Nyhan, Jason Reifler, Ronald E. Robertson, Christo Wilson
Do online platforms facilitate the consumption of potentially harmful content?
no code implementations • ACL 2021 • Shan Jiang, Christo Wilson
Misinformation has recently become a well-documented matter of public concern.
no code implementations • 13 Jun 2021 • Avijit Ghosh, Aalok Shanbhag, Christo Wilson
We incorporate QDD into a continuous model monitoring system, called FairCanary, that reuses existing explanations computed for each individual prediction to quickly compute explanations for the QDD bias metrics.
1 code implementation • 5 May 2021 • Avijit Ghosh, Ritam Dutt, Christo Wilson
Existing fair ranking systems, especially those designed to be demographically fair, assume that accurate demographic information about individuals is available to the ranking algorithm.