267 citations · 506 across the 14 of their papers we have counts for
15 papers
From Network Inequality to Network Fairness: A Perspective on Responsible Decision-Making
Lisette Espín-Noboa, Tina Eliassi-Rad, Pak-Hang Wong +5
Social networks shape how individuals make decisions and how opportunities are distributed. However, the mechanisms that generate these networks often reflect pre-existing inequali…
Reducing Access Disparities in Networks using Edge Augmentation
Ashkan Bashardoust, Sorelle A. Friedler, Carlos E. Scheidegger +2
In social networks, a node's position is a form of \it{social capital}. Better-positioned members not only benefit from (faster) access to diverse information, but innately have mo…
Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolina
Mohsen Abbasi, Suresh Venkatasubramanian, Sorelle A. Friedler +2
Voter suppression and associated racial disparities in access to voting are long-standing civil rights concerns in the United States. Barriers to voting have taken many forms over…
Repairing Regressors for Fair Binary Classification at Any Decision Threshold
Kweku Kwegyir-Aggrey, A. Feder Cooper, Jessica Dai +3
We study the problem of post-processing a supervised machine-learned regressor to maximize fair binary classification at all decision thresholds. By decreasing the statistical dist…
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
Michelle Bao, Angela Zhou, Samantha Zottola +5
Risk assessment instrument (RAI) datasets, particularly ProPublica's COMPAS dataset, are commonly used in algorithmic fairness papers due to benchmarking practices of comparing alg…
Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instability
Pegah Nokhiz, Aravinda Kanchana Ruwanpathirana, Neal Patwari +1
When it comes to studying the impacts of decision making, the research has been largely focused on examining the fairness of the decisions, the long-term effects of the decision pi…
A Research Ecosystem for Secure Computing
Nadya Bliss, Lawrence A. Gordon, Daniel Lopresti +2
Computing devices are vital to all areas of modern life and permeate every aspect of our society. The ubiquity of computing and our reliance on it has been accelerated and amplifie…
Interdisciplinary Approaches to Understanding Artificial Intelligence's Impact on Society
Suresh Venkatasubramanian, Nadya Bliss, Helen Nissenbaum +1
Innovations in AI have focused primarily on the questions of "what" and "how"-algorithms for finding patterns in web searches, for instance-without adequate attention to the possib…
Information access representations and social capital in networks
Ashkan Bashardoust, Hannah C. Beilinson, Sorelle A. Friedler +6
Social network position confers power and social capital. In the setting of online social networks that have massive reach, creating mathematical representations of social capital…
Evolving Methods for Evaluating and Disseminating Computing Research
Benjamin Zorn, Tom Conte, Keith Marzullo +1
Social and technical trends have significantly changed methods for evaluating and disseminating computing research. Traditional venues for reviewing and publishing, such as confere…
Fair clustering via equitable group representations
Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian
What does it mean for a clustering to be fair? One popular approach seeks to ensure that each cluster contains groups in (roughly) the same proportion in which they exist in the po…
Problems with Shapley-value-based explanations as feature importance measures
I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger +1
Game-theoretic formulations of feature importance have become popular as a way to "explain" machine learning models. These methods define a cooperative game between the features of…
Equalizing Recourse across Groups
Vivek Gupta, Pegah Nokhiz, Chitradeep Dutta Roy +1
The rise in machine learning-assisted decision-making has led to concerns about the fairness of the decisions and techniques to mitigate problems of discrimination. If a negative d…
On the (im)possibility of fairness
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
What does it mean for an algorithm to be fair? Different papers use different notions of algorithmic fairness, and although these appear internally consistent, they also seem mutua…
Certifying and removing disparate impact
Michael Feldman, Sorelle Friedler, John Moeller +2
What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcome…