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20142025
most citedFairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

626 citations · 2.7k across the 64 of their papers we have counts for

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Showing 2018Show all

9 papers · 1 filter

cs.SI2018★ 6 cited

Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations

Abhijnan Chakraborty, Gourab K Patro, Niloy Ganguly +2

To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Top…

cs.LG2018

A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity

Hoda Heidari, Michele Loi, Krishna P. Gummadi +1

We map the recently proposed notions of algorithmic fairness to economic models of Equality of opportunity (EOP)---an extensively studied ideal of fairness in political philosophy.…

cs.SI2018★ 94 cited

On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook

Filipe N. Ribeiro, Koustuv Saha, Mahmoudreza Babaei +6

Targeted advertising is meant to improve the efficiency of matching advertisers to their customers. However, targeted advertising can also be abused by malicious advertisers to eff…

cs.LG2018★ 196 cited

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Till Speicher, Hoda Heidari, Nina Grgic-Hlaca +4

Discrimination via algorithmic decision making has received considerable attention. Prior work largely focuses on defining conditions for fairness, but does not define satisfactory…

stat.ML2018★ 31 cited

Blind Justice: Fairness with Encrypted Sensitive Attributes

Niki Kilbertus, Adrià Gascón, Matt J. Kusner +3

Recent work has explored how to train machine learning models which do not discriminate against any subgroup of the population as determined by sensitive attributes such as gender…

cs.AI2018★ 46 cited

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making

Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi +1

We draw attention to an important, yet largely overlooked aspect of evaluating fairness for automated decision making systems---namely risk and welfare considerations. Our proposed…