162 citations · 585 across the 42 of their papers we have counts for
6 papers · 1 filter
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy
Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
Differentially private (DP) mechanisms have been deployed in a variety of high-impact social settings (perhaps most notably by the U.S. Census). Since all DP mechanisms involve add…
Setting the Right Expectations: Algorithmic Recourse Over Time
Joao Fonseca, Andrew Bell, Carlo Abrate +2
Algorithmic systems are often called upon to assist in high-stakes decision making. In light of this, algorithmic recourse, the principle wherein individuals should be able to take…
Social network modeling and applications, a tutorial
Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction
Falaah Arif Khan, Julia Stoyanovich
In this paper we revisit the bias-variance decomposition of model error from the perspective of designing a fair classifier: we are motivated by the widely held socio-technical bel…
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
Andrew Bell, Lucius Bynum, Nazarii Drushchak +3
The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and…
An Epistemic and Aleatoric Decomposition of Arbitrariness to Constrain the Set of Good Models
Falaah Arif Khan, Denys Herasymuk, Nazar Protsiv +1
Recent research reveals that machine learning (ML) models are highly sensitive to minor changes in their training procedure, such as the inclusion or exclusion of a single data poi…